Let’s look at a number of positioning charts and positioning statements to see how they can work in tandem.
Celia, Manager of Business Process Engineering
Goal: Promotion as Business Process Engineering Executive
| Target Audience | For the VP Operations and Executive Management Team |
| Problem Statement | Who need to streamline processes and reduce costs to keep competitive, and are concerned about a lack of diversity in engineering |
| Category | I am a business process engineering manager and diversity leader who solves complex business problems. |
| Value Proposition | I have saved millions of dollars through streamlining business processes and have raised our company’s image among women engineers. |
| Competitive Differentiation | Unlike other business process engineering managers, I am the president of a national organization for women engineers, and have recruited and built a diverse high-performing team that has delivered nearly 30 operational cost-cutting initiatives. |


Orthogonal Arrows
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| Package | Description |
|---|---|
| com.opengamma.strata.calc.runner |
The calculation runner.
|
| com.opengamma.strata.measure.credit |
Calculation functions for credit products.
|
| com.opengamma.strata.measure.deposit |
Calculation functions for deposit products.
|
| com.opengamma.strata.measure.dsf |
Calculation functions for DSF products.
|
| com.opengamma.strata.measure.fra |
Calculation functions for FRA products.
|
| com.opengamma.strata.measure.fx |
Calculation functions for FX products.
|
| com.opengamma.strata.measure.index |
Calculation functions for index products.
|
| com.opengamma.strata.measure.payment |
Calculation functions for payment products.
|
| com.opengamma.strata.measure.security |
Calculation functions for futures products.
|
| com.opengamma.strata.measure.swap |
Calculation functions for swap products.
|
| com.opengamma.strata.measure.swaption |
Calculation functions for swaption products.
|
| Modifier and Type | Method and Description |
|---|---|
CalculationFunction<CalculationTarget> |
CalculationTask.getFunction()
Gets the function that will calculate the value.
|
default <T extends CalculationTarget> |
CalculationFunctions.getFunction(T target)
Gets the function that handles the specified target.
|
| Modifier and Type | Method and Description |
|---|---|
<T extends CalculationTarget> |
CalculationFunctions.findFunction(T target)
Finds the function that handles the specified target.
|
| Modifier and Type | Method and Description |
|---|---|
static CalculationFunctions |
CalculationFunctions.of(CalculationFunction<?>... functions)
Obtains an instance from the specified functions.
|
static CalculationTask |
CalculationTask.of(CalculationTarget target,
CalculationFunction<? extends CalculationTarget> function,
CalculationParameters parameters,
List<CalculationTaskCell> cells)
Obtains an instance that will calculate the specified cells.
|
static CalculationTask |
CalculationTask.of(CalculationTarget target,
CalculationFunction<? extends CalculationTarget> function,
CalculationTaskCell... cells)
Obtains an instance that will calculate the specified cells.
|
| Modifier and Type | Method and Description |
|---|---|
static CalculationFunctions |
CalculationFunctions.of(List<? extends CalculationFunction<?>> functions)
Obtains an instance from the specified functions.
|
static CalculationFunctions |
CalculationFunctions.of(Map<Class<?>,? extends CalculationFunction<?>> functions)
Obtains an instance from the specified functions.
|
| Modifier and Type | Class and Description |
|---|---|
class |
CdsTradeCalculationFunction
Perform calculations on a single
CdsTrade for each of a set of scenarios. |
| Modifier and Type | Class and Description |
|---|---|
class |
TermDepositTradeCalculationFunction
Perform calculations on a single
TermDepositTrade for each of a set of scenarios. |
| Modifier and Type | Class and Description |
|---|---|
class |
DsfTradeCalculationFunction
Perform calculations on a single
DsfTrade for each of a set of scenarios. |
| Modifier and Type | Class and Description |
|---|---|
class |
FraTradeCalculationFunction
Perform calculations on a single
FraTrade for each of a set of scenarios. |
| Modifier and Type | Class and Description |
|---|---|
class |
FxNdfTradeCalculationFunction
Perform calculations on a single
FxNdfTrade for each of a set of scenarios. |
class |
FxSingleTradeCalculationFunction
Perform calculations on a single
FxSingleTrade for each of a set of scenarios. |
class |
FxSwapTradeCalculationFunction
Perform calculations on a single
FxSwapTrade for each of a set of scenarios. |
| Modifier and Type | Class and Description |
|---|---|
class |
IborFutureTradeCalculationFunction
Perform calculations on a single
IborFutureTrade for each of a set of scenarios. |
| Modifier and Type | Class and Description |
|---|---|
class |
BulletPaymentTradeCalculationFunction
Perform calculations on a single
BulletPaymentTrade for each of a set of scenarios. |
| Modifier and Type | Class and Description |
|---|---|
class |
GenericSecurityTradeCalculationFunction
Perform calculations on a single
GenericSecurityTrade for each of a set of scenarios. |
class |
SecurityPositionCalculationFunction
Perform calculations on a single
SecurityPosition for each of a set of scenarios. |
class |
SecurityTradeCalculationFunction
Perform calculations on a single
SecurityTrade for each of a set of scenarios. |
| Modifier and Type | Class and Description |
|---|---|
class |
SwapTradeCalculationFunction
Perform calculations on a single
SwapTrade for each of a set of scenarios. |
| Modifier and Type | Class and Description |
|---|---|
class |
SwaptionTradeCalculationFunction
Perform calculations on a single
SwaptionTrade for each of a set of scenarios. |
Copyright 2009-Present by OpenGamma Inc. and individual contributors
Apache v2 licensed
Additional documentation can be found at opengamma.github.io/StrataDocs.


Paragraphs are separated by a blank line.
2nd paragraph. Italic, bold, monospace
. Itemized lists
look like:
Note that --- not considering the asterisk --- the actual text content starts at 4-columns in.
Block quotes are written like so.
They can span multiple paragraphs, if you like.
Use 3 dashes for an em-dash. Use 2 dashes for ranges (ex. "it's all in chapters 12--14"). Three dots ... will be converted to an ellipsis.
Here's a numbered list:
Note again how the actual text starts at 4 columns in (4 characters from the left side). Here's a code sample:
# Let me re-iterate ...
for i in 1 .. 10 { do-something(i) }
As you probably guessed, indented 4 spaces. By the way, instead of indenting the block, you can use delimited blocks, if you like:
define foobar() {
print "Welcome to flavor country!";
}
(which makes copying & pasting easier). You can optionally mark the delimited block for Pandoc to syntax highlight it:
import time
# Quick, count to ten!
for i in range(10):
# (but not *too* quick)
time.sleep(0.5)
print i
Now a nested list:
First, get these ingredients:
Boil some water.

Notice again how text always lines up on 4-space indents (including that last line which continues item 3 above). Here's a link to a website. Here's a link to a local doc. Here's a footnote [^1].
[^1]: Footnote text goes here.
Tables can look like this:
size material color
9 leather brown 10 hemp canvas natural 11 glass transparent
Table: Shoes, their sizes, and what they're made of
(The above is the caption for the table.) Here's a definition list:
apples : Good for making applesauce. oranges : Citrus! tomatoes : There's no "e" in tomatoe.
Again, text is indented 4 spaces. (Alternately, put blank lines in between each of the above definition list lines to spread things out more.)
Inline math equations go in like so: $\omega = d\phi / dt$. Display math should get its own line and be put in in double-dollarsigns:
$$I = \int \rho R^{2} dV$$
Done.
print "Hello world"


2-Look OLL Practice
Reset
Algorithm
Scramble
Whole Cube:
y
y'
First Look:
Opposite
Adjacent
None
Second Look:
Sune
Anti-Sune
Car
Blinker
Headlights
Chameleon
Bowtie


---
layout: post
title: A Time & Place For Homework
date: 2010-08-28 13:27:58.000000000 -07:00
type: post
parent_id: '0'
published: true
pd: ''
status: publish
categories:
- Classroom Talk
- Organizational Tips
tags:
- back to school
- homework
- organizing your child
author:
login: k
email: k@k
display_name: mcary
first_name: ''
last_name: ''
---
All too often teachers hear excuses from children for all the reasons that their homework isn’t done. Ideally homework is assigned to practice new skills that have been learned during the school day. Homework should be given for an age appropriate amount of time and shouldn’t be considered as “busy work.”
Here are a few tips that parents might want to adopt in order to improve their child’s homework experience:
- Have a designated time each school day when homework is done. Some children need a break right after school and some do better getting it over with and having the rest of the evening free.
 Include a ruler, calculator, markers, pencils, scissors, glue, etc..
- Make sure your child has a planner at school to copy assignments in. Encourage neatness in handwriting so that you are able to read and understand what is being assigned.
- Use a calendar to record and track assignments that are long term. Practice budgeting time to get large assignments done on time.
- Teach your child from an early age that they are accountable for homework not you. Support your child’s teacher in expecting homework to be done.


Host information used by OTA to identify devices.
Settings for the WiFi Access Point this device broadcasts.
Web Authentication credentials. (Only applies to the Pose Editor and File Editor and is obviously not very secure. Demo only.)
Settings for the servo/lighting special effects.
Hardware setup for the first servo motor.
Hardware setup for the second servo motor.
Please confirm you wish to delete all the log files.
An "Over The Air" update is in progress. Once complete, please wait for the device to restart, and then reload this page.


kindredsec created Certified Professional Penetration Tester Field Manual:
Located on disk in Cheat Sheets > Field Manuals


{% load static %}
{% include "header.html" %}
{% include "navigation.html" %}
| App ID | {{data.app.aid}} |
| Name: | {% if data.edit == 'app_name' %} {% else %} {{data.app.name}} | Change {% endif %} |
| Last edit: | {{data.app_latest_commit_ts}} |
| Views: | {% if data.view == 'things' %} Code editor | App Things {% else %} Code editor | App Things {% endif %} |
| WARNING: you are deleting the App named "{{data.app.name}}", this operation will also delete all of its thing data and cannot be undone. | |
| Actions: | Cancel | Confirm delete App |
| Actions: | Delete App |
*experimental feature
{% endif %}


SecurityProtocol
public struct SecurityProtocol: CustomStringConvertible
The possible security protocols that can be used to communicate with brokers.
-
The textual representation of the SecurityProtocol.
Declaration
Swift
public let description: String
-
Don’t use a protocol and send messages in plaintext.
Declaration
Swift
public static let plaintext = SecurityProtocol(description: "plaintext")
-
Use the Secure Sockets Layer (SSL) protocol.
Declaration
Swift
public static let ssl = SecurityProtocol(description: "ssl")
-
Use the Simple Authentication and Security Layer (SASL) without SSL.
Declaration
Swift
public static let sasl_plaintext = SecurityProtocol(description: "sasl_plaintext")
-
Use the Simple Authentication and Security Layer (SASL) with SSL.
Declaration
Swift
public static let sasl_ssl = SecurityProtocol(description: "sasl_ssl")


{%extends 'base.html'%} {% import "bootstrap/wtf.html" as wtf %} {% block content %}
{{ pitch.content }}


|
Class Summary |
| AncestorGeneratorService |
This CMSService performs the following service functions
Available service functions:
AGS_GENPROPERTIES - generate catalog, catalogs, and AncestorCategories (for catalogs, products, skus)
AGS_GENCATALOGS - generate catalog and catalogs (for catalogs, products and skus)
AGS_GENPARENTCATS - generate parent categories
AGS_GENANCESTORS - generate ancestors (for products and skus)
AGS_GENPROPERTIES_FOR_CATEGORY - only generate category and above
AGS_GENPROPERTIES_FOR_PRODUCT - only generate product and above |
| CatalogAlias |
A user-defined property descriptor that will allow one property to
act as an alias for another. |
| CatalogCompletionService |
This service performs incremental maintenance on the catalog system
after changes have been made to the catalog structure in the UI. |
| CatalogItemLookupDroplet |
This servlet looks for a RepositoryItem by its id from within a
Repository. |
| CatalogMaintenanceService |
This service extends the standard catalog maintenance to provide
processing specific to custom catalogs. |
| CatalogMigration |
This class is used to migrate the old product catalog data to the custom Catalog. |
| CatalogMigrationService |
This class migrates a standard system to a custom catalog system. |
| CatalogPossibleValues |
This subclass of atg.repository.servlet.PossibleValues
will only include items that are contained in the current users
catalog, in the list of possible values. |
| CatalogProfilePropertySetter |
Commerce specific implementation of the ProfilePropertySetter
that sets set the catalog property of a profile from the current site. |
| CatalogProperties |
CatalogProperties.java
Created: Wed Feb 28 11:19:49 2001 |
| CatalogSearchFormHandler |
Does the same thing as atg.commerce.catalog.SearchFormHandler but it limits all searches
to within the current catalog. |
| CatalogUpdateService |
This service batch-computes the properties that are usually maintained
by CatalogCompletionService . |
| CatalogVerificationService |
This CMSService performs the following service functions |
| CustomCatalogTools |
This class is an extension of atg.commerce.catalog.CatalogTools
that modifies the behavior so it works with custom catalogs. |
| CustomCatalogTypeInfo |
This class represents type metadata relating to the product
catalog, and is serializable. |
| FilteringCatalogPossibleValues |
This subclass of atg.repository.servlet.PossibleValues
will only include items that are contained in the current users
catalog, in the list of possible values. |
| FilteringSearchFormHandler |
Overrides the custom catalog search form handler when in development mode
to filter items by catalogs in post query processing |
| ForEachItemInCatalog |
This is exactly the same as the ForEach droplet except only items
that are in the current users catalog. |
| InfoGeneratorService |
This service examines the product catalog and ensures that every
category has a category-info object for each catalog it is
contained in, that every product has a product-info for each
catalog it is contained in, and that every sku has a sku-info for
each catalog it is contained in. |
| SubCatalogsGeneratorService |
This class will update each catalogs "subCatalogs" property with a
list of all the sub catalogs (and their sub catalogs, etc.)
The following properties will be updated by this service:
catalog.allRootCategories
catalog.allRootCategoryIds
catalog.subCatalogs
catalog.subCatalogsIds
category.subCatalogsChildCategories
|


Defines an abstract syntax tree for constructing lanaguages over first order logic. Also defines the types of transformations on such a language, such as parsing, compiling, unifying and so on.


Hover the mouse over the buttons and other elements of the configuration dialog in the picture below to see a short description. Click the respective element to read more.
To see the real configuration dialog either install AgreementGINA2 or start the config.exe. But where to find the configuration dialog if AgreementGINA2 was installed? Easy, when logged on at the machine as admin and pressing Ctrl+Alt+Del you will see the button "Configure GINA", press it to configure the settings.
This group of settings allows to configure the technical aspects of the
agreement dialog, such as timeout, content to be shown and whether there should
be a timeout period at all!
If this title is displayed in gray the agreement
dialog will not be shown by default (which is the case in "guest only" mode and
for the special setting, see below)!
Pressing this test button will allow you to see the currently active settings. Note: currently active means that changes need to be saved before you test them!
The contents of the agreement dialog, as well as the other dialog with HTML
content can have different forms how you declare the content.
Basically there are two modes:
1. URI/URL mode
2. HTML mode
The 1st mode allows you to enter a URI/URL (e.g. http://localhost/somefile)
in which case the text field will appear with blue background. The 2nd mode allows
you to enter HTML content directly. The content length is limited to 64kB, which
you should not use to its full extent if possible because the content is being saved
to the registry
(it shouldn't cause problems, according to MS, but experiences from Windows 95 and 98
are still in my mind, so use this carefully with only a few kB).
Well, how does the GINA recognize whether the content is a URL or HTML content?
Easy: if you start your content with < or if the
content contains explicit line breaks, if will be recognized as HTML content and the
text field background turns white!
To learn more about what content is allowed, see the
agreement dialog description.
Deactivates or activates showing of the timer. There is one special setting if the box is checked, but the timeout period is set to zero: in this case the agreement dialog will not show at all and hence the title of the surrounding groupbox will be shown in gray as described above.
This sets the timeout period. There is one special setting if the box is checked, but the timeout period is set to zero: in this case the agreement dialog will not show at all and hence the title of the surrounding groupbox will be shown in gray as described above.
This defines the text which will be used for the "Yes" button. Default text is "Yes" which you may change for your local language. Other appropriate settings would be "Proceed" or "Agree".
This defines the text which will be used for the "No" button. Default text is "No" which you may change for your local language. Another appropriate setting would be "Cancel".
This defines the text right to the checkbox in the agreement dialog. This checkbox needs to be checked for the "Yes" button to become active.
All settings for news and maintenance mode can be configured in this groupbox.
This includes turning these modes on or off and setting their content.
If this title is displayed in gray the agreement
dialog will not be shown by default (which is the case in "guest only" mode and
for the special setting, see below)!
Pressing this test button will allow you to see the currently active settings. Note: currently active means that changes need to be saved before you test them!
The contents of the news dialog, as well as the other dialog with HTML
content can have different forms how you declare the content.
Basically there are two modes:
1. URI/URL mode
2. HTML mode
The 1st mode allows you to enter a URI/URL (e.g. http://localhost/somefile)
in which case the text field will appear with blue background. The 2nd mode allows
you to enter HTML content directly. The content length is limited to 64kB, which
you should not use to its full extent if possible because the content is being saved
to the registry
(it shouldn't cause problems, according to MS, but experiences from Windows 95 and 98
are still in my mind, so use this carefully with only a few kB).
Well, how does the GINA recognize whether the content is a URL or HTML content?
Easy: if you start your content with < or if the
content contains explicit line breaks, if will be recognized as HTML content and the
text field background turns white!
To learn more about what content is allowed, see the
news dialog description.
This simply turns the news mode on or off according to whether the checkbox is checked or unchecked. News mode is not active for "guest only" mode.
Pressing this test button will allow you to see the currently active settings. Note: currently active means that changes need to be saved before you test them!
The contents of the maintenance dialog, as well as the other dialog with HTML
content can have different forms how you declare the content.
Basically there are two modes:
1. URI/URL mode
2. HTML mode
The 1st mode allows you to enter a URI/URL (e.g. http://localhost/somefile)
in which case the text field will appear with blue background. The 2nd mode allows
you to enter HTML content directly. The content length is limited to 64kB, which
you should not use to its full extent if possible because the content is being saved
to the registry
(it shouldn't cause problems, according to MS, but experiences from Windows 95 and 98
are still in my mind, so use this carefully with only a few kB).
Well, how does the GINA recognize whether the content is a URL or HTML content?
Easy: if you start your content with < or if the
content contains explicit line breaks, if will be recognized as HTML content and the
text field background turns white!
To learn more about what content is allowed, see the
maintenance dialog description.
This simply turns the maintenance mode on or off according to whether the checkbox is checked or unchecked. Maintenance mode is not active for "guest only" mode.
This disallows locking of a workstation for the logged-on user.
This setting is only valid for non-admin users, may it be in "guest only" mode or
in any other mode. Administrative users will have the standard settings always. But be aware
that these standard settings may be some policy which disables locking the workstation
for admins as well.
This implies that if activated (i.e. locking disabled), the policy is being overridden
for non-admin users, whatever it was.
This disallows changing the password for the logged-on user.
This setting is only valid for non-admin users, may it be in "guest only" mode or
in any other mode. Administrative users will have the standard settings always. But be aware
that these standard settings may be some policy which disables changing the password
for admins as well.
This implies that if activated (i.e. changing disallowed), the policy is being overridden
for non-admin users, whatever it was.
This setting allows you to either disable or replace the task manager.
And yes, replacing really means replacing the task manager completely,
even when started through the explorer or something else.
Disabling the task manager will deactivate the button in the security dialog only,
but replacing it will replace it, however you start it. Note however, that the application
you use as replacement must not take command line parameters (i.e. it must ignore them).
See the registry settings to learn more!
The setting is only valid for non-admin users, may it be in "guest only" mode or
in any other mode. Administrative users will have the standard settings always. But be aware
that these standard settings may be some policy which disables changing the password
for admins as well.
This implies that if activated (i.e. changing disallowed), the policy is being overridden
for non-admin users, whatever it was.
In these four fields you have to enter the information needed to logon the designated guest user (guest does not actually mean that the user has to have only guest privileges, any account can be used here!). If the fields appear with green background the information contained is at least syntactically correct (non-empty username, twice the same password), however if it appears red this information will not be saved! This means that the old information will still exist and be used.
This activates or deactivates the "guest only" mode, according to the checkbox setting.
Override this by holding down F1 or Shift before the automatic logon appears. This will
allow an admin to log on.
The specified account
is being logged on immediately. Logging off results in logging on with this account once
more (except if overridden). Ideal for a kiosk mode ;)
IMPORTANT: combining this mode with
a restriction for the "guest" account (such as "deny local logon") will result in
an infinite loop of reboots which can be interrupted by the override sequence F1.

This setting tells the GINA that the admin should never be shown the agreement and news dialogs! This is the default.
User information is an optional extra feature. In our PC-pool we use it to have a central
PHP script on the domain server which keeps a list of logged-on users. Furthermore it
allows to create a ranking, to see who was the first logged-on user. This feature, if
enabled will create a listening server thread in the GINA which returns information
about the logged on user and the current status. This option allows you to configure
the port on which the GINA will listen and return information. If set to zero (0) the
feature is disabled.
Note: The returned information is first of all encoded as a URI (special characters
appear as %xx, xx being a 2-digit hexadecimal character code). So
you should first decode the string according to this scheme. Secondly the decoded
string is in UTF-8 format. This means if you use any special characters (say cyrillic)
these will be UTF-8 encoded and can be easily decoded into its native form (independent
of any local settings).
The format of the returned and decoded string is as follows (also see the telnet screenshot
below):
User#Domain#YYYY-MM-DD@hh:mm:ss#AMG#xxx.yyy.zzz.bbbUser being the username, Domain being the domain name to which the user logged on, YYYY-MM-DD@hh:mm:ss being the time in an ISO-similar manner and AMG being the three flags which may appear in any combination.
To test this feature connect to the machine with the installed GINA (and activated user information) using Telnet and the following command line.
telnet <target> <port>To use this feature effectively you have to have some programming knowledge to connect to this port and read out the string. Perhaps some srcipts will be included in the distribution package soon (PHP and Perl in this case).


| get_dim {panelPomp} | R Documentation |
Subset matrix dropping dimension but without dropping dimname
(as done by `[`
by default).
get_col(matrix, rows, col)
get_row(matrix, row, cols)
matrix |
matrix. |
rows |
numeric; rows to subset; like with |
col |
integer; single column to subset. |
row |
integer; single row to subset. |
cols |
numeric; columns to subset; like with |
A named vector
object.
Carles Bretó
m <- matrix(NA,dimnames=list('r1','c1'))
m[1,1] # = NA; R removes both names
get_col(m,rows=1,col=1) # = c(r1=NA) keeps colname
get_row(m,row=1,cols=1) # = c(c1=NA) keeps rowname


suitable distribution species tenuifolia climate highly RCP. habitat variables potential change scenarios current Fig environmental models range Maxent future {border-style China regions px;} used #ffffff;} ./j.-...x distributions model data Global area mean region total .%, Central Ecology West plant presence Change medium Chinese different global modeling climatic using AUC Predicting Species conservation low occurrence predicted Biology. Current Distribution Polygala Potential RCP., altitude indicate land medicinal precipitation probability wild China. Climate Habitat Hebei, North RCP annual areas higher impact px; spatial temperature tenuifolia. warmest {font-family .%. East Ecological Environmental Inner Mongolia, Press; Sciences South Zhang accuracy contribution font-size geographic habitats high important increase results (RCP., Academy Ecography. Ecology. Gansu, Hebei Henan, International Liaoning, Ningxia, Science Shaanxi, Table Using Willd. changes decline double; effects modelling performance plants resource result shifts showed significant values variable warming -.% ./journal.pone. Anderson BIO Elith Evolution. However, JZ. Jiancheng Jilin, Modeling National Periods RCP.) RCPs Radix Science. Shanxi, Suitable Zhao affect affected based better bold border-color border-width changing conditions decrease elevation obtained patterns predict predicting quarter records red relative role selected solid; study threshold vegetation {font-style {font-weight (.–.), (RCPs ./ddi. ./nature Applied Biogeography. Distributions. Diversity Fund Geographical Heilongjiang, Hunan, Information Jiangxi, Nature. Northwest ONE. Project Qinghai, SDM Sciences, Shandong, Special Training Wang Yang Yunnan, analyzed approximately assessment bioclimatic change: courier; cover, cultivation distribution, dominant effect em; evaluate evaluation gain herb implications included increased located management maps methods original pathways period prediction predictions pt;} selection shown soil, species. studies test variables.


| Developer Spotlight |
Christine Karman is the Founder of Tryllian in Amsterdam, Holland. Tryllian, which has been a member of the Project JXTA community since May 2001, provides distributed agent products, services and solutions. Christine is an astrophysicist by training, is a longtime software engineer who has been working in artificial intelligence since 1987 and mobile-agent technology since 1993. A pioneer in artificial intelligence, she left her position at the Dutch software company, Origin, and founded Tryllian in March 1998. She recently relinquished her CEO title in spring 2001, however she remains actively involved with the company, focusing on strategic business development and public relations. Christine thinks that the world has been thinking in terms of centralized systems for decades, then everyone turned to client-server, which provided as little flexibility as centralized systems. She says that what we need is flexibility and adaptivity. Users don't want to know about architectures. Users need data, information, knowledge, and communications wherever they are. Christine sees JXTA as a step towards extremely flexible and adaptive architectures. Christine says that JXTA enables Tryllian to use auto-discovery, pass firewalls, and solve their NAT problem. They have been using JXTA since the summer of 2001, and now are actively using the security features. JXTA allowed them to solve infrastructural problems their very dynamic environment poses, enabling Tryllian to focus on the core features of their platform. You can reach Christine at<EMAIL_ADDRESS>or on the discuss mailing list. |


Day 1: Marrakech
Arrival at the Menara airport. Transfer to the hotel or Riad.
Day 2: Marrakech – Aguelmame Ouiouane (1650m) (366km)
Departure after breakfast by 4WD or minibus via Beni Mellal, Khénifra to the Ouiouane Lake in the Middle Atlas. Overnight stay in a local gîte.
Day 3: Aguelmame Ouiouane – Zaouit Ifran Falls (4hours walk)
We will cross the forests to descend to the waterfall Zaouit Ifran for a picnic. Zaouia d'Ifrane is a Berber village, known for its cedar and oak forests, waterfalls, beautiful plateaus and cliffs. Return late afternoon by car, overnight stay in the gîte.
Day 4: Aguelmame Ouiouane – Sources Oum er Rbia (4hours walk)
We will continue our trek through the cedar forest on a mule track. This forest sheltered the lions of the Atlas, as well as tigers, which disappeared around the 70’s. We will follow a valley that leads us to the gorges from which spring the 40 sources of Oum er Rbia, a magical place where caves have been set up along the sources. Picnic and return late afternoon by car. Overnight stay in the gîte.
Day 5: Aguelmame Ouiouane - Aguelmame Tiguelmamine (1650m) – Aguelmame Azigza (1487m) (4hours walk)
We are still in the Zayan Country, a famous tribe in the history of Morocco, very proud and very welcoming population. We'll follow a path that crosses centennial cedar forests. These forests are home to a few dozen pairs of monkeys, which we'll approach easily. Notice the many sheepfolds near the pastures, enjoy the superb view on the mountain and the cedar forest near the Ighoud-sources. Picnic and return late afternoon by car.
Day 6: Aguelmame Ouiouane – Fez (127km)
Departure after breakfast via Azrou and Ifrane to Fez. Day off to explore the city: medina, tanneries, souks, medersa, …. Overnight stay in a hotel or riad.
Day 7: Fez – Marrakech (515km)
When return flight from Fez, the journey ends in Fez. If you return from Marrakech, we will leave after breakfast for a long drive to Marrakech. Overnight stay in a hotel or riad.
Day 8: Marrakech – return flight
Got to catch that airplane!


| TIMES(2) | Linux Programmer's Manual | TIMES(2) |
clock_t times(struct tms *buf);
struct tms { clock_t tms_utime; /* user time */ clock_t tms_stime; /* system time */ clock_t tms_cutime; /* user time of children */ clock_t tms_cstime; /* system time of children */ };
The tms_utime field contains the CPU time spent executing instructions of the calling process. The tms_stime field contains the CPU time spent executing inside the kernel while performing tasks on behalf of the calling process.
The tms_cutime field contains the sum of the tms_utime and tms_cutime values for all waited-for terminated children. The tms_cstime field contains the sum of the tms_stime and tms_cstime values for all waited-for terminated children.
Times for terminated children (and their descendants) are added in at the moment wait(2) or waitpid(2) returns their process ID. In particular, times of grandchildren that the children did not wait for are never seen.
All times reported are in clock ticks.
sysconf(_SC_CLK_TCK);
In POSIX.1-1996 the symbol CLK_TCK (defined in <time.h>) is mentioned as obsolescent. It is obsolete now.
In Linux kernel versions before 2.6.9, if the disposition of SIGCHLD is set to SIG_IGN, then the times of terminated children are automatically included in the tms_cstime and tms_cutime fields, although POSIX.1-2001 says that this should happen only if the calling process wait(2)s on its children. This nonconformance is rectified in Linux 2.6.9 and later.
On Linux, the buf argument can be specified as NULL, with the result that times() just returns a function result. However, POSIX does not specify this behavior, and most other UNIX implementations require a non-NULL value for buf.
Note that clock(3) also returns a value of type clock_t, but this value is measured in units of CLOCKS_PER_SEC, not the clock ticks used by times().
On Linux, the "arbitrary point in the past" from which the return value of times() is measured has varied across kernel versions. On Linux 2.4 and earlier, this point is the moment the system was booted. Since Linux 2.6, this point is (2^32/HZ) - 300 seconds before system boot time. This variability across kernel versions (and across UNIX implementations), combined with the fact that the returned value may overflow the range of clock_t, means that a portable application would be wise to avoid using this value. To measure changes in elapsed time, use clock_gettime(2) instead.
| 2017-09-15 | Linux |


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Organisation Centre for Excellence in Child and Family Welfare (2003 - )
- From
- 2003
- Categories
- Peak body
- Website
- http://www.cfecfw.asn.au/
Summary
The Centre for Excellence in Child and Family Welfare, established in 2003, is a peak body for community service organisations in the child, youth and family services sector of Victoria, established in 2003. The organisation began as the Children's Welfare Association of Victoria, a peak body set up in 1912.
Details
The Centre for Excellence in Child and Family Welfare was established in 2003. The Centre is a peak body, providing representation, professional development, research, policy and program advice, publications and resources for 96 community service organisations in the child, youth and family services sector of Victoria.
The Centre for Excellence began as the Children's Welfare Association of Victoria, a peak body set up in 1912.
The Centre represents small, medium and large community service organisations spread across the State in metropolitan and country areas. Its members provide services including residential care, family support, counselling, parenting support, day programs, alternative education, financial counselling, foster care, respite care, support for families with children with a disability, unemployment services, drug and alcohol counselling, sexual abuse counselling, women's refuges, domestic violence services, supported accommodation, youth support services, school support and assistance for families in crisis.
Skip to
Related Entries
Timeline
1910 - 1912 Child Saving Council
1912 - 2003 Children's Welfare Association of Victoria
2003 - Centre for Excellence in Child and Family Welfare
Publications
Reports
- Raman, Sunitha; Forbes, Catherine, It's Not Too Late To Care: report on the research into life outcomes for people brought up in institutional care in Victoria, Centre for Excellence in Child and Family Welfare Inc., Melbourne, 2008. Details
Gallery
Prepared by: Cate O'Neill
Created: 21 January 2009, Last modified: 14 December 2011


Site Name
There are so many good 3x3s, and this list isn't extensive. It is only a list of three good cubes as well as links.
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JsonHelper
public struct JsonHelper
Helps to convert dictionaries/arrays with custom objects to a valid JSON string. (and back)
-
Encodes the contents of a dictionary recursively.
Declaration
Swift
public static func encode(object: [String: Any]) -> EncodedDictionary
-
Encodes the contents of an array recursively.
Seealso
seealso
encode(object: [String: Any])
Declaration
Swift
public static func encode(object: [Any]) -> EncodedArray
-
Encodes dictionary convertibles like
User
.Declaration
Swift
public static func encode(object: DictionaryConvertible) -> EncodedDictionary
-
Encodes objects that conform to
StringRepresentable
.Declaration
Swift
public static func encode(object: StringRepresentable) -> String
-
Returns the UNIX timestamp from the
Date
Declaration
Swift
public static func encode(object: Date) -> Int
-
Returns the absolute string of the
URL
.Declaration
Swift
public static func encode(object: URL) -> String
-
Encodes a
[String: Any]
to a valid JSON-string.Throws
An error if the decoding failed
Declaration
Swift
public static func jsonString(from dictionary: [String: Any]) throws -> String?
Parameters
dictionary
The dictionary to encode
Return Value
The JSON-string
-
Encodes a
[Any]
to a valid JSON-string.Throws
An error if the decoding failed
Declaration
Swift
public static func jsonString(from array: [Any]) throws -> String?
Parameters
array
The array to encode
Return Value
The JSON-string
-
Encodes a
DictionaryConvertible
to a valid JSON-string.Throws
An error if the decoding failed
Declaration
Swift
public static func jsonString(from object: DictionaryConvertible) throws -> String?
Parameters
object
The object to encode
Return Value
The JSON-string
-
Decodes a given JSON-string
Note
Unlike the
jsonString(from:)
method, this will not convert the String to custom objects. You will have to use their initializers.Note
Try to avoid this method. It’s easier to use the JSON-initializer of
JsonConvertible
objects.Throws
An error if the decoding failed
Declaration
Swift
public static func decode(jsonString json: String) throws -> Any
Parameters
json
The JSON-string
Return Value
The decoded object


PXRColorPicker Class Reference
| Inherits from | UIViewController |
| Conforms to | PXRColorWheelDelegate |
| Declared in | PXRColorPicker.h |
Overview
A view controller for picking colors in an ios application.
Example Usage:
- (IBAction)openColorPicker:(UIButton*)sender{
PXRColorPicker *colorPicker = [[PXRColorPicker alloc] init];
colorPicker.delegate = self;
[self presentViewController:colorPicker animated:YES completion:^{}];
}
- (void)colorPicker:(PXRColorPicker *)colorPicker pickedColor:(UIColor *)color{
NSLog(@"picked color %@", color);
[self dismissViewControllerAnimated:YES completion:^{}];
}
- (void)colorPickerCancelled:(PXRColorPicker *)colorPicker{
[self dismissViewControllerAnimated:YES completion:^{}];
}
Tasks
-
delegate
The delegate for the color picker. See PXRColorPickerDelegate for more info.
property -
currentColor
The current UIColor in the picker has selected.
property -
defaultsPrefix
A prefix to use for NSUserDefaults that will define what the naming convention of the saving of swatches and the main color.
property
Setting this to a unique string per document can let the user have a picker with swatches and a main color that are unique to that document. -
brightnessIncrement
The amount of steps the lighter and darker buttons will go by for setting brightness.
property -
swatches
An array of UIButtons to use as swatches. For use in a custom nib.
property -
alphaSlider
A UISlider to be used to set the opacity of the color. For use in a custom nib.
property -
tintSlider
A UISlider to be used to set the hue of the color. For use in a custom nib.
property -
colorWheel
A PXRColorWheel that will update the color when the user moves a finger over it. For use in a custom nib.
property -
wheelLed
A UIImageView the LED that appears over the tintSlider that will show the user where they have selected. For use in a custom nib.
property -
colorLed
A UIView that shows the main color. For use in a custom nib.
property -
dragLed
A UIView that shows when the user has tapped on the main LED. Dragging over a swatch will let the user set that swatch. For use in a custom nib.
property -
darkerButton
A UIButton that a user can tap to make the color darker. For use in a custom nib.
property -
lighterButton
A UIButton that a user can tap to make the color lighter. For use in a custom nib.
property -
– changeHue:
Changes the hue of the main color. Can be hooked up to the tintSlider UIControlEventValueChanged event.
-
– changeAlpha:
Changes the opacity of the main color. Can be hooked up to the alphaSlider UIControlEventValueChanged event.
-
– changeColorFromSwatch:
Changes the color to the background color of a swatch. Can be hooked up to each of the UIControlEventTouchUpInside events in for swatches.
-
– onOk:
Notifies the delegate that the picker has picked a color. By default hooked up to a “done” button.
-
– onCancel:
Notifies the delegate that the picker has cancelled picking. By default hooked up to a “cancel” button.
-
– darker:
Darkens the color by the amount of steps set in brightnessIncrement. Can be hooked up to the darkerButton UIControlEventTouchUpInside event.
-
– lighter:
Lightens the color by the amount of steps set in brightnessIncrement. Can be hooked up to the lighterButton UIControlEventTouchUpInside event.
-
– saveColors
Saves the colors and swatches to NSUserDefaults using defaultsPrefix.
Properties
alphaSlider
A UISlider to be used to set the opacity of the color. For use in a custom nib.
@property (weak) IBOutlet UISlider *alphaSlider
Discussion
A UISlider to be used to set the opacity of the color. For use in a custom nib.
Declared In
PXRColorPicker.h
brightnessIncrement
The amount of steps the lighter and darker buttons will go by for setting brightness.
@property NSUInteger brightnessIncrement
Discussion
The amount of steps the lighter and darker buttons will go by for setting brightness.
Declared In
PXRColorPicker.h
colorLed
A UIView that shows the main color. For use in a custom nib.
@property (weak) IBOutlet UIView *colorLed
Discussion
A UIView that shows the main color. For use in a custom nib.
Declared In
PXRColorPicker.h
colorWheel
A PXRColorWheel that will update the color when the user moves a finger over it. For use in a custom nib.
@property (weak) IBOutlet PXRColorWheel *colorWheel
Discussion
A PXRColorWheel that will update the color when the user moves a finger over it. For use in a custom nib.
Declared In
PXRColorPicker.h
currentColor
The current UIColor in the picker has selected.
@property (strong, readonly) UIColor *currentColor
Discussion
The current UIColor in the picker has selected.
Declared In
PXRColorPicker.h
darkerButton
A UIButton that a user can tap to make the color darker. For use in a custom nib.
@property (weak) IBOutlet UIButton *darkerButton
Discussion
A UIButton that a user can tap to make the color darker. For use in a custom nib.
Declared In
PXRColorPicker.h
defaultsPrefix
A prefix to use for NSUserDefaults that will define what the naming convention of the saving of swatches and the main color.
Setting this to a unique string per document can let the user have a picker with swatches and a main color that are unique to that document.
@property (strong) NSString *defaultsPrefix
Discussion
A prefix to use for NSUserDefaults that will define what the naming convention of the saving of swatches and the main color.
Setting this to a unique string per document can let the user have a picker with swatches and a main color that are unique to that document.
Declared In
PXRColorPicker.h
delegate
The delegate for the color picker. See PXRColorPickerDelegate for more info.
@property (weak) NSObject<PXRColorPickerDelegate> *delegate
Discussion
The delegate for the color picker. See PXRColorPickerDelegate for more info.
Declared In
PXRColorPicker.h
dragLed
A UIView that shows when the user has tapped on the main LED. Dragging over a swatch will let the user set that swatch. For use in a custom nib.
@property (strong) IBOutlet UIView *dragLed
Discussion
A UIView that shows when the user has tapped on the main LED. Dragging over a swatch will let the user set that swatch. For use in a custom nib.
Declared In
PXRColorPicker.h
lighterButton
A UIButton that a user can tap to make the color lighter. For use in a custom nib.
@property (weak) IBOutlet UIButton *lighterButton
Discussion
A UIButton that a user can tap to make the color lighter. For use in a custom nib.
Declared In
PXRColorPicker.h
swatches
An array of UIButtons to use as swatches. For use in a custom nib.
@property (strong) IBOutletCollection ( UIButton ) NSArray *swatches
Discussion
An array of UIButtons to use as swatches. For use in a custom nib.
Declared In
PXRColorPicker.h
tintSlider
A UISlider to be used to set the hue of the color. For use in a custom nib.
@property (weak) IBOutlet UISlider *tintSlider
Discussion
A UISlider to be used to set the hue of the color. For use in a custom nib.
Declared In
PXRColorPicker.h
wheelLed
A UIImageView the LED that appears over the tintSlider that will show the user where they have selected. For use in a custom nib.
@property (weak) IBOutlet UIImageView *wheelLed
Discussion
A UIImageView the LED that appears over the tintSlider that will show the user where they have selected. For use in a custom nib.
Declared In
PXRColorPicker.h
Instance Methods
changeAlpha:
Changes the opacity of the main color. Can be hooked up to the alphaSlider UIControlEventValueChanged event.
- (IBAction)changeAlpha:(UISlider *)sender
Parameters
- sender
The UISlider sending the update.
Discussion
Changes the opacity of the main color. Can be hooked up to the alphaSlider UIControlEventValueChanged event.
Declared In
PXRColorPicker.h
changeColorFromSwatch:
Changes the color to the background color of a swatch. Can be hooked up to each of the UIControlEventTouchUpInside events in for swatches.
- (IBAction)changeColorFromSwatch:(UIButton *)sender
Parameters
- sender
The UIButton sending the update.
Discussion
Changes the color to the background color of a swatch. Can be hooked up to each of the UIControlEventTouchUpInside events in for swatches.
Declared In
PXRColorPicker.h
changeHue:
Changes the hue of the main color. Can be hooked up to the tintSlider UIControlEventValueChanged event.
- (IBAction)changeHue:(UISlider *)sender
Parameters
- sender
The UISlider sending the update.
Discussion
Changes the hue of the main color. Can be hooked up to the tintSlider UIControlEventValueChanged event.
Declared In
PXRColorPicker.h
darker:
Darkens the color by the amount of steps set in brightnessIncrement. Can be hooked up to the darkerButton UIControlEventTouchUpInside event.
- (IBAction)darker:(UIButton *)sender
Parameters
- sender
The UIButton sending the update.
Discussion
Darkens the color by the amount of steps set in brightnessIncrement. Can be hooked up to the darkerButton UIControlEventTouchUpInside event.
Declared In
PXRColorPicker.h
lighter:
Lightens the color by the amount of steps set in brightnessIncrement. Can be hooked up to the lighterButton UIControlEventTouchUpInside event.
- (IBAction)lighter:(UIButton *)sender
Parameters
- sender
The UIButton sending the update.
Discussion
Lightens the color by the amount of steps set in brightnessIncrement. Can be hooked up to the lighterButton UIControlEventTouchUpInside event.
Declared In
PXRColorPicker.h
onCancel:
Notifies the delegate that the picker has cancelled picking. By default hooked up to a “cancel” button.
- (IBAction)onCancel:(UIButton *)sender
Parameters
- sender
The UIButton sending the update.
Discussion
Notifies the delegate that the picker has cancelled picking. By default hooked up to a “cancel” button.
Declared In
PXRColorPicker.h
onOk:
Notifies the delegate that the picker has picked a color. By default hooked up to a “done” button.
- (IBAction)onOk:(UIButton *)sender
Parameters
- sender
The UIButton sending the update.
Discussion
Notifies the delegate that the picker has picked a color. By default hooked up to a “done” button.
Declared In
PXRColorPicker.h
saveColors
Saves the colors and swatches to NSUserDefaults using defaultsPrefix.
- (void)saveColors
Discussion
Saves the colors and swatches to NSUserDefaults using defaultsPrefix.
Declared In
PXRColorPicker.h


Senior Leader Course
S305: Active and Reserve Component Capabilities
* * *
Table of Contents
- Five Capabilities 3
- Publish & Process 4
- Scope 5
- Learning Objective 6
- Assigned Readings 7
- Our Service 8
- How the Army Operates 9
- Army Responsibility 10
- The Roles of the Army 11
- The Core Competencies 14
- The Role of the Army Reserve 17
- The Role of the Army National Guard 21
- Army Guard Snapshot 25
- State Partnership Program (SPP) 26
- Summary 28
Use five minutes to answer the information below on a 3x5 card or sheet of paper. Once complete, place your 3x5 card or sheet of paper off to the side.
In your own words, list five capabilities for each component.
-
Active Army:
-
Army National Guard:
-
Army Reserve:
Answer the question(s) in your journal. Good note taking during the lesson can aid in effective reflection and retention of material while journaling.
-
What is the importance of knowing the three components capabilities?
-
How different are the capabilities of each component?
Scope
At the end of this two-hour lesson, learners will have investigated active and reserve component capabilities. As a result, learners will have a better understanding of the capabilities of the total Army force.
Answer the question in your journal before selecting further analysis button.
List the Roles of the Army
The Roles of the Army
-
Shape Operational Environments
-
Preventing Conflict
-
Prevail In Large–Scale Ground Combat Operations
-
Consolidated Gains
Roles of the Army Explained
Shape Operational Environments
The Army provides unique forces with capabilities to shape operational environments. Shaping operational environments
allows combatant commanders to reassure partners and deter aggression while establishing conditions that support the
potential employment of joint forces. Army regionally aligned forces—including special operations units, Army Reserve
units, and Army National Guard units—assist partners with internal defense and develop the capabilities needed to deter
adversaries and defeat enemies. Army forces further develop relationships with multinational partner land forces, share
intelligence, strengthen their security forces, increase cultural awareness, and conduct bilateral and multilateral
military exercises. Through efforts such as the State Partnership Program, Army National Guard and Reserve units supply
unique and dual–trained Soldiers with special skills obtained as civilians to assist in medical and engineering activities,
disaster preparedness, critical infrastructure management, and resource protection. Together, these efforts allow the Army
to maintain a global landpower network that is critical in shaping operational environments and winning wars. Army forces
conduct shaping operations through the day–to–day actions of its Service component commanders, trainers, advisors, and
logistic activities as specified under Title 10, USC and support to Title 22 and Title 50, USC.
Ref: ADP–1, para 2–19
Preventing Conflict
Preventing conflict includes all activities that deter adversary military actions which threaten allies or partners and
deny them the ability to achieve objectives counter to U.S. interests. A well–trained, credible, and capable Army reduces
the risk of aggression by adversaries because it raises both the risk and potential cost of military action to their
forces. Moving ready and trained Army forces into a region tells adversaries that the United States is prepared and willing
to protect its interests. Partner nations under external threats understand that introducing U.S. forces alters the regional
military balance of power in their favor and bolsters their resolve to resist aggression. Multinational partners and
adversaries recognize that Army forces—combined with the nation’s joint air, maritime, and space–based forces—are dominant
and therefore are a deterrence to armed conflict. This role meets the objectives described in the National Military Strategy.
Ref: ADP–1, para 2–20
Prevail In Large-Scale Ground Combat
The Army’s capability and capacity to conduct large–scale ground combat is unique and foundational to its other roles.
Only the Army has the capabilities necessary for sustained ground combat anywhere in the world. The credibility inherent
in its ability to conduct large–scale ground combat as part of the joint force is a critical part of U.S. conventional
deterrence. It is a primary source of assurance to friendly nations and an important factor in worldwide stability. The
U.S. Army conducts large–scale ground combat as part of the joint force. When it deploys and fights, the Army both enables
and is enabled by the other Services when they perform their roles. An Army that can defeat any enemy worldwide requires
professionally committed leadership, well–equipped and trained units, and proficiency in the conduct of joint and
multinational operations. Maintaining the readiness necessary for large–scale ground combat is a difficult and continual
process that consumes significant time and resources. Readiness for large–scale ground combat operations saves lives.
Ref: ADP–1, para 2–21
Consolidated Gains
Operations to consolidate gains make temporary operational successes enduring and set the conditions to facilitate the
transition of control over territory to legitimate authorities. Army forces enable the joint force commander to capitalize
on operational success by following through to ensure sustainable conditions on the ground. Consolidation of gains is an
integral part of winning armed conflict and is essential to retaining the long–term initiative over determined adversaries.
Army forces reinforce and integrate the efforts of all unified action partners when they consolidate gains. Operations serve
a higher national purpose in support of U.S. interests and are planned and executed to support that purpose at each echelon.
A clear understanding of the higher purpose of the mission and operational environment determines what must happen to
consolidate gains during the course of operations. How well ground forces consolidate gains determines in large part how
enduring the results of operations will be. Effectively consolidating gains increases options for national leaders and
contributes to decisive outcomes.
Ref: ADP–1, para 2–22
Answer the question in your journal before selecting further analysis button.
What are The Core Competencies?
The Core Competencies
-
Prompt and Sustained Land Combat
-
Combined Arms Operations
-
Special Operations
-
Set and Sustain the Theater for the Joint Force
-
Integrate National, Multinational, and Joint Power on Land
The Core Competencies Explained
Prompt and Sustained Land Combat
Prompt and sustained land combat is the assigned function of the Army, directed both by Congress in Title 10, USC, and by
DODD 5100.01. This function is the foundation from which the Army builds its ability to win in combat. It is the primary
function for which the Army organizes, trains, and equips forces. Prompt land combat is what requires the Army’s
expeditionary capability: the ability to deploy on short notice task—organized forces capable of immediately conducting
operations upon arrival to austere locations. Sustained land combat requires the Army to campaign with the power to
conduct extended operations and continuous consolidation of gains necessary to achieve the objectives set for the Army
by the joint force. Sustained land combat spans the range of military operations. It requires a force that can sustain
its efforts for as long as necessary and can adapt to unpredictable changes in an operational environment.
Ref: ADP–1, para 2–25
Combined Arms Operations
All operations are combined arms operations. Combined arms is the synchronized and simultaneous application of arms to
achieve an effect greater than if each element was used separately or sequentially (ADP 3–0). Combined arms includes Army
capabilities and joint, multinational, and other unified action partner capabilities. Combined arms operations integrate
leadership, information, and each of the warfighting functions. Used destructively, combined arms integrate different
capabilities so that responding to one capability makes the enemy vulnerable to another. Combined arms multiply the
effects of Army and joint capabilities in operations. They require highly trained Soldiers, skilled leaders, and
integrated information systems. Commanders synchronize combined arms capabilities using command and control to employ
combat power to their best advantage. Combined Arms Operations will be further discussed in S307.
Ref: ADP–1, para 2–26
Special Operations
Special operations require unique modes of employment, tactics, equipment, and training. Army special operations forces
provide combatant commanders with precise lethal and nonlethal capabilities. These capabilities include special warfare and
surgical strike operations in hostile, denied, or politically sensitive areas. These operations may be time sensitive,
clandestine, low visibility, and high risk. Special operations forces possess uniquely assessed, organized, trained, and
equipped Soldiers. The interdependence of special operations and conventional forces, gained by the right mix of complementary
and reinforcing capabilities, enhances success throughout the range of military operations across the competition continuum.
Ref: ADP–1, para 2–31
Set and Sustain the Theater for the Joint Force
The Army’s ability to set and sustain the theater is essential to allowing the joint force to seize the initiative while
restricting an enemy force’s options. Setting the theater for the joint force includes the establishment of access and
infrastructure to support joint force operations. The Army possesses unique capabilities to establish and maintain vital
infrastructure and support the joint force commander. These capabilities include intelligence support; communications; port and
airfield opening; logistics; ground-based air defense; chemical defense; and reception, staging, onward movement, and integration.
Sustaining the theater for the joint force includes theater sustainment and meeting executive agent responsibilities. Maintaining
critical infrastructure—as well as sustaining joint forces, unified action partners, and multinational forces—is accomplished
through the Army’s support to other Services, executive agent, and Title 10, USC, requirements. The Army uses Army Service
component commands, forward deployed forces, and rotational forces to develop, sustain, and operate this theater structure.
Ref: ADP–1, para 2–32
Integrate National, Multinational, and Joint Power on Land
The Army has the largest number of headquarters that are joint task force headquarters capable and can combine all elements of
national, multinational, and joint power. Army headquarters are designed to be the core components that integrate unified action
partner capabilities into a Service headquarters or rapidly transition from a Service headquarters into a joint or multinational
joint task force or land component command. These headquarters provide the capability to plan, prepare, execute, and assess joint and
multinational operations. Army forces support partners with situational understanding, security, and logistics. Army forces ensure
combatant commanders possess the ability to reinforce and sustain land forces rapidly through forward positioning, theater
infrastructure capabilities, and the use of prepositioned equipment and supplies. Army headquarters and forces help impose order to
chaotic situations and synchronize plans, programs, and efforts necessary to accomplish the mission.
Ref: ADP–1, para 2–33
Answer the question in your journal before selecting further analysis button.
How much of the Army Reserve makes up the Army’s organized units?
Further Analysis
Possible Answer:
Ref: ADP 1, para 1–11
The Army Reserve makes up only about one–fifth of the Army’s organized units, but it provides one–half of the Army’s sustainment units and one–fourth of the Army’s mobilization base–expansion capability.
Army Reserve
The Army Reserve is under the command of the President and serves as a federal military force. Elements of it mobilize
when required. Most Army Reserve Soldiers serve for a period in the Regular Army and then elect to continue their service
in the Reserve. The Army Reserve makes up about a fifth of the Army’s organized units, but it provides a half of the Army’s
sustainment units, a fourth of the Army’s mobilization base–expansion capability, and most of its civil affairs capacity. The
Army Reserve is also the Army’s major source of trained individual Soldiers for strengthening headquarters and filling
vacancies in the Regular Army during a crisis. Many Army Reserve Soldiers are also civilian professionals, such as nurses,
dentists, and computer technicians, who augment critical Army specialties. Similar to Army National Guard members, a small
number of Army Reservists are full–time active duty.
Ref: ADP–1, para 1–11
Answer the question in your journal before selecting further analysis button.
What is the role of the Army National Guard Component?
Further Analysis
Possible Answer:
Ref: ADP–1, para 1–9
The Army National Guard has a dual role based on the Constitution. Its first role is that of a state military force. Its second role is as an operational reserve for the Regular Army. Each state, the U.S. territories (Guam, Puerto Rico, and the Virgin Islands), and the District of Columbia have Army National Guard units totaling 54 state and territorial National Guards. Army National Guard forces remain under the command of their respective governors until mobilized for federal service. Each state or territory Army National Guard has an adjutant general—a general officer appointed by the governor—who serves as its uniformed leader. The governor can order the Army National Guard to state service since it is a state military force. The Army National Guard responds to natural disasters and other domestic emergencies many times each year. While serving their states, these Soldiers are subject to civil laws and their states‘ Codes of Military Justice. A governor can use the Army National Guard of the state for law enforcement, which is something that federal military forces cannot perform except under special circumstances. A small number of Army National Guard Soldiers are on full–time active duty, a duty status called ”Active Guard and Reserve.”
Army National Guard
When ordered to active duty, Army National Guard Soldiers become subject to the Uniform Code of Military Justice and fall
under the command of combatant commanders. Army National Guard forces are similarly organized and equipped as units in the
Regular Army and Army Reserve. The Department of the Army provides their equipment, provides much of their funding, and is
responsible for assessing their combat readiness. However, states retain latitude in recruiting, manning, and training.
Ref: ADP–1, para 1–10
Answer the question in your journal.
How will the understanding of the component capability of the Army, Army Reserve, and National Guard assist you in future operations?
Your facilitator will provide instructions for The Army Learning Activity.


or Abseiling from the shoulders of giants - © Gregory Popovitch - March 10, 2019
[tl;dr] We present a novel hashmap design, the Parallel Hashmap. Built on a modified version of Abseil's flat_hash_map, the Parallel Hashmap has lower space requirements, is nearly as fast as the underlying flat_hash_map, and can be used from multiple threads with high levels of concurrency. The parallel hashmap repository provides header-only version of the flat and node hashmaps, and their parallel versions as well.
If you haven't been living under a rock, you know that Google open sourced late last year their Abseil library, which includes a very efficient flat hash table implementation. The absl::flat_hash_map stores the values directly in a memory array, which avoids memory indirections (this is referred to as closed hashing).
Using parallel SSE2 instructions, the flat hash table is able to look up items by checking 16 slots in parallel, which allows the implementation to remain fast even when the table is filled to 87.5% capacity.
The graphs below show a comparison of time and memory usage necessary to insert up to 100 million values (each value is composed of two 8-byte integers), between the default hashmap of Visual Studio 2017 (std::unordered_map), and Abseil's flat_hash_map:
On the bottom graph, we can see that, as expected, the Abseil flat_hash_map is significantly faster that the default stl implementation, typically about three times faster.
The top graph shown the memory usage for both tables.
I used a separate thread to monitor the memory usage, which allows to track the increased memory usage when the table resizes. Indeed, both tables have a peak memory usage that is significantly higher than the memory usage seen between insertions.
In the case of Abseil's flat_hash_map, the values are stored directly in a memory array. The memory usage is constant until the table needs to resize, which is why we see these horizontal sections of memory usage.
When the flat_hash_map reaches 87.5% occupancy, a new array of twice the size is allocated, the values are moved (rehashed) from the smaller to the larger array, and then the smaller array, now empty, is freed. So we see that during the resize, the occupancy is only one third of 87.5%, or 29.1%, and when the smaller array is released, occupancy is half of 87.5% or 43.75%.
The default STL implementation is also subject to this higher peak memory usage, since it typically is implemented with an array of buckets, each bucket having a pointer to a linked list of nodes containing the values. In order to maintain O(1) lookups, the array of buckets also needs to be resized as the table size grows, requiring a 3x temporary memory requirement for moving the old bucket array (1x) to the newly allocated, larger (2x) array. In between the bucket array resizes, the default STL implementation memory usage grows at a constant rate as new values are added to the linked lists.
Instead of having a separate linked list for each bucket, std::unordered_map implementations often use a single linked list (making iteration faster), with buckets pointing to locations within the single linked list. absl::node_hash_map, on the other hand, has each bucket pointing to a single value, and collisions are handled with open addressing like for the absl::flat_hash_map.
This peak memory usage can be the limiting factor for large tables. Suppose you are on a machine with 32 GB of ram, and the flat_hash_map needs to resize when you inserted 10 GB of values in it. 10 GB of values means the array size is 11.42 GB (resizing at 87.5% occupancy), and we need to allocate a new array of double size (22.85 GB), which obviously will not be possible on our 32 GB machine.
For my work developing mechanical engineering software, this has kept me from using flat hash maps, as the high peak memory usage was the limiting factor for the size of FE models which could be loaded on a given machine. So I used other types of maps, such as sparsepp or Google's cpp-btree.
When the Abseil library was open sourced, I started pondering the issue again. Compared to Google's old dense_hash_map which resized at 50% capacity, the new absl::flat_hash_map resizing at 87.5% capacity was more memory friendly, but it still had these significant peaks of memory usage when resizing.
If only there was a way to eliminate those peaks, the flat_hash_map would be close to perfect. But how?
Suddenly, it hit me. I had a solution. I would create a hash table that internally is made of an array of 16 hash tables (the submaps). When inserting or looking up an item, the index of the target submap would be decided by the hash of the value to insert. For example, if for a given size_t hashval
, the index for the internal submap would be computed with:
submap_index = (hashval ^ (hashval >> 4)) & 0xF;
providing an index between 0 and 15.
In the actual implementation, the size of the array of hash tables is configurable to a power of two, so it can be 2, 4, 8, 16, 32, ... The following illustration shows a parallel_hash_map with 8 submaps.
The benefit of this approach would be that the internal tables would each resize on its own when they reach 87.5% capacity, and since each table contains approximately one sixteenth of the values, the memory usage peak would be only one sixteenth of the size we saw for the single flat_hash_map.
The rest of this article describes my implementation of this concept that I have done in my parallel hashmap repository. This is a header only library, which provides the following eight hashmaps:
This implementation requires a C++11 compatible compiler, and provides full compatibility with the std::unordered_map (with the exception of pointer stability for the flat
versions. C++14 and C++17 methods, like try-emplace
, are provided as well. The names for it are parallel_flat_hash_map or parallel_flat_hash_set, and the node equivalents. These hashmaps provide the same external API as the flat_hash_map, and internally use a std::array of 2**N flat_hash_maps.
I was delighted to find out that not only the parallel_flat_hash_map has significant memory usage benefits compared to the flat_hash_map, but it also has significant advantages for concurrent programming as I will show later. In the rest of this article, we will focus on the parallel_flat_hash_map, but similar results are seen for the parallel_node_hash_map, and the set versions of course.
So, without further ado, let's see the same graphs graphs as above, with the addition of the parallel_flat_hash_map. Let us first look at memory usage (the second graph provides a "zoomed-in" view of the location where resizing occurs):
We see that the parallel_flat_hash_map behaves as expected. The memory usage matches exactly the memory usage of its base flat_hash_map, except that the peaks of memory usage which occur when the table resizes are drastically reduced, to the point that they are not objectionable anymore. In the "zoomed-in" view, we can see the sixteen dots corresponding to each of the individual submaps resizing. The fact that those resizes are occuring at roughly the same x location in the graph shows that we have a good hash function distribution, distributing the values evenly between the sixteen individual submaps.
But what about the speed? After all, for each value inserted into the parallel hashmap, we have to do some extra work (steps 1 and 2 below):
The first step (compute the hash) is the most problematic one, as it can potentially be costly. As we mentioned above, the second step (computing the index from the hash) is very simple and its cost in minimal (3 processor instruction as shown below in Matt Godbolt's compiler explorer):
As for the hash value computation, fortunately we can eliminate this cost by providing the computed hash to the submap functions, so that it is computed only once. This is exactly what I have done in my implementation of the parallel_flat_hash_map, adding a few extra APIs to the internal raw_hash_map.h header, which allow the parallel_flat_hash_map to pass the precomputed hash value to the underlying submaps.
So we have all but eliminated the cost of the first step, and seen that the cost of the second step is very minimal. At this point we expect that the parallel_flat_hash_map performance will be close to the one of its underlying flat_hash_map, and this is confirmed by the chart below:
Indeed, because of the scale is somewhat compressed due to the longer times of the std::unordered_map, we can barely distinguish between the blue curve of the flat_hash_map and the red curve of the parallel_flat_hash_map. So let's look at a graph without the std::unordered_map:
This last graph shows that the parallel_flat_hash_map is slightly slower especially for smaller table sizes. For a reason not obvious to me (maybe better memory locality), the speeds of the parallel_flat_hash_map and flat_hash_map are essentially undistinguishable for larger map sizes (> 80 million values).
This is already looking pretty good. For large hash_maps, the parallel_flat_hash_map is a very appealing solution, as it provides essentially the excellent performance of the flat_hash_map, while virtually eliminating the peaks of memory usage which occur when the hash table resizes.
But there is another aspect of the inherent parallelism of the parallel_flat_hash_map which is interesting to explore. As we know, typical hashmaps cannot be modified from multiple threads without explicit synchronization. And bracketing write accesses to a shared hash_map with synchronization primitives, such as mutexes, can reduce the concurrency of our program, and even cause deadlocks.
Because the parallel_flat_hash_map is made of sixteen separate submaps, it posesses some intrinsic parallelism. Indeed, suppose you can make sure that different threads will use different submaps, you would be able to insert into the same parallel_flat_hash_map at the same time from the different threads without any locking.
So, if you can iterate over the values you want to insert into the hash table, the idea is that each thread will iterate over all values, and then for each value:
Here is the code for the single-threaded insert:
template <class HT>
void _fill_random_inner(int64_t cnt, HT &hash, RSU &rsu)
{
for (int64_t i=0; i<cnt; ++i)
{
hash.insert(typename HT::value_type(rsu.next(), 0));
++num_keys[0];
}
}
and here is the code for the multi-threaded insert:
template <class HT>
void _fill_random_inner_mt(int64_t cnt, HT &hash, RSU &rsu)
{
constexpr int64_t num_threads = 8; // has to be a power of two
std::unique_ptr<std::thread> threads[num_threads];
auto thread_fn = [&hash, cnt, num_threads](int64_t thread_idx, RSU rsu) {
size_t modulo = hash.subcnt() / num_threads; // subcnt() returns the number of submaps
for (int64_t i=0; i<cnt; ++i) // iterate over all values
{
unsigned int key = rsu.next(); // get next key to insert
size_t hashval = hash.hash(key); // compute its hash
size_t idx = hash.subidx(hashval); // compute the submap index for this hash
if (idx / modulo == thread_idx) // if the submap is suitable for this thread
{
hash.insert(typename HT::value_type(key, 0)); // insert the value
++(num_keys[thread_idx]); // increment count of inserted values
}
}
};
// create and start 8 threads - each will insert in their own submaps
// thread 0 will insert the keys whose hash direct them to submap0 or submap1
// thread 1 will insert the keys whose hash direct them to submap2 or submap3
// --------------------------------------------------------------------------
for (int64_t i=0; i<num_threads; ++i)
threads[i].reset(new std::thread(thread_fn, i, rsu));
// rsu passed by value to threads... we need to increment the reference object
for (int64_t i=0; i<cnt; ++i)
rsu.next();
// wait for the threads to finish their work and exit
for (int64_t i=0; i<num_threads; ++i)
threads[i]->join();
}
Using multiple threads, we are able to populate the parallel_flat_hash_map (inserting 100 million values) three times faster than the standard flat_hash_map (which we could not have populated from multiple threads without explicit locks, which would have prevented performance improvements).
And the graphical visualization of the results:
We notice in this last graph that the memory usage peaks, while still smaller than those of the flat_hash_map, are larger that those we saw when populating the parallel_flat_hash_map using a single thread. The obvious reason is that, when using a single thread, only one of the submaps would resize at a time, ensuring that the peak would only be 1/16th of the one for the flat_hash_map (provided of course that the hash function distributes the values somewhat evenly between the submaps).
When running in multi-threaded mode (in this case eight threads), potentially as many as eight submaps can resize simultaneaously, so for a parallel_flat_hash_map with sixteen submaps the memory peak size can be half as large as the one for the flat_hash_map.
Still, this is a pretty good result, we are now inserting values into our parallel_flat_hash_map three times faster than we were able to do using the flat_hash_map, while using a lower memory ceiling.
This is significant, as the speed of insertion into a hash map is important in many algorithms, for example removing duplicates in a collection of values.
It may not be practical to add logic into your program to ensure you use different internal submaps from each thread. Still, locking the whole parallel_flat_hash_map for each access would forego taking advantage of its intrinsic parallelism.
For that reason, the parallel_flat_hash_map can provide internal locking using the std::mutex
(the default template parameter is phmap::NullMutex
, which does no locking and has no size cost). When selecting std::mutex
, one mutex is created for each internal submap at a cost of 8 bytes per submap, and the parallel_flat_hash_map internally protects each submap access with its associated mutex.
| map | Number of submaps | sizeof(map) |
|---|---|---|
| std::unordered_map (vs2017) | - | 64 |
| phmap::flat_hash_map | - | 48 |
| phmap::parallel_flat_hash_map, N=4, phmap::NullMutex | 16 | 768 |
| phmap::parallel_flat_hash_map, N=4, phmap::Mutex | 16 | 896 |
It is about time we provide the complete parallel_flat_hash_map class declaration (the declaration for parallel_flat_hash_set is similar):
template <class K, class V,
class Hash = phmap::priv::hash_default_hash<K>,
class Eq = phmap::priv::hash_default_eq<K>,
class Allocator = phmap::priv::Allocator<std::pair<const K, V>>, // alias for std::allocator
size_t N = 4, // 2**N submaps
class Mutex = phmap::NullMutex> // use std::mutex to enable internal locks
class parallel_flat_hash_map;
Let's see what result we get for the insertion of random values from multiple threads, however this time we create a parallel_flat_hash_map with internal locking (by providing std::mutex as the last template argument), and modify the code so that each thread inserts values in any submap (no pre-selection).
If we were to do a intensive insertion test into a hash map from multiple threads, where we lock the whole hash table for each insertion, we would be likely to get even worse results than for a single threaded insert, because of heavy lock contention.
In this case, our expectation is that the finer grained locking of the parallel_flat_hash_map (separate locks for each internal submap) will provide a speed benefit when compared to the single threaded insertion, and this is indeed what the benchmarks show:
Interestingly, we notice that the memory peaks (when resizing occur) are again very small, in the order of 1/16th of those for the flat_hash_map. This is likely because, as soon as one of the submaps resizes (which takes much longer than a regular insertion), the other threads very soon have to wait on the resizing submap's mutex for an insertion, before they reach their own resizing threashold.
Since threads statistically will insert on a different submap for each value, it would be a surprising coincidence indeed if two submaps reached their resizing threshold without the resizing of the first submap blocking all the other threads first.
If we increase the number of submaps, we should see more parallelism (less lock contention across threads, as the odds of two separate threads inserting in the same subhash is lower), but with diminishing returns as every submap resize will quickly block the other threads until the resize is completed.
This is indeed what we see:
| map | Number of submaps | sizeof(map) | time 100M insertions |
|---|---|---|---|
| phmap::flat_hash_map | - | 48 | 14.77s |
| phmap::parallel_flat_hash_map, N=4, std::mutex | 16 | 896 | 8.36s |
| phmap::parallel_flat_hash_map, N=5, std::mutex | 32 | 1792 | 7.14s |
| phmap::parallel_flat_hash_map, N=6, std::mutex | 64 | 3584 | 6.61s |
There is still some overhead from the mutex lock/unlock, and the occasional lock contention, which prevents us from reaching the performance of the previous multithreaded lock-free insertion (5.12s for inserting 100M elements).
We have seen that the novel parallel hashmap approach, used within a single thread, provides significant space advantages, with a very minimal time penalty. When used in a multi-thread context, the parallel hashmap still provides a significant space benefit, in addition to a consequential time benefit by reducing (or even eliminating) lock contention when accessing the parallel hashmap.
I would like to thank Google's Matt Kulukundis for his eye-opening presentation of the flat_hash_map design at CPPCON 2017 - my frustration with not being able to use it helped trigger my insight into the parallel_flat_hash_map. Also many thanks to the Abseil container developers - I believe the main contributors are Alkis Evlogimenos and Roman Perepelitsa - who created an excellent codebase into which the graft of this new hashmap took easily, and finally to Google for open-sourcing Abseil. Thanks also to my son Andre for reviewing this paper, and for his patience when I was rambling about the parallel_flat_hash_map and its benefits.
Repository for the Parallel Hashmap, including the benchmark code used in this paper
Matt Kulukindis: Designing a Fast, Efficient, Cache-friendly Hash Table, Step by Step


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Note that many of our activites have moved online since March 2020. For up-to-date information on these programs, visit their respective pages!
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Three Peaks Challenge
Horton-in-Ribblesdale ENG
Website: www.threepeaksrace.org.uk
Race Winners
(63 runnings)
30 Apr
2011 24 Apr
2010 25 Apr
2009 26 Apr
2008
30 Apr 2006
2:54:15 3:43:40 24 Apr 2005
2:57:50 3:59:56 25 Apr 2004
2:55:46 3:39:49 27 Apr 2003
3:56:40 28 Apr 2002
3:46:12 2001
30 Apr 2000
3:38:11 25 Apr 1999
3:20:17 26 Apr 1998
3:34:16 27 Apr 1997
3:34:39 28 Apr 1996
3:16:17 30 Apr 1995
3:48:40 24 Apr 1994
3:21:50 25 Apr 1993
3:39:50 26 Apr 1992
3:19:11 28 Apr 1991
3:16:29 29 Apr 1990
3:44:18 30 Apr 1989
3:32:43 24 Apr 1988
3:37:16 26 Apr 1987
3:44:05 27 Apr 1986
3:49:12 28 Apr 1985
3:38:10 29 Apr 1984
3:41:00 24 Apr 1983
4:08:01 25 Apr 1982
3:40:54 11
Oct 1981
3:59:16 27 Apr 1980
3:35:34 3:43:12 25 Apr 1976
27 Apr 1975
28 Apr 1974
29 Apr 1973
30
Apr 1972
25 Apr 1971
26 Apr 1970
27 Apr 1969
28 Apr 1968
30 Apr 1967
24 Apr 1966
25 Apr 1965
26 Apr 1964
28 Apr 1963
29 Apr 1962
30 Apr 1961
24 Apr 1960
26 Apr 1959
27 Apr 1958
28 Apr 1957
29 Apr 1956
24 Apr 1955
24 Apr 1954
3:48:00
Notes: 1954 was the inaugural year. The 2001 race was cancelled due to an
outbreak of foot-and-mouth disease. The course traverses three peaks on
trails with sections that are open (no trail). In 1975, the start/finish
were moved from Chapel le Dale (Hill Inn) to Horton
in Ribblesdale, adding about two kilometers.
The route has been altered for various reasons, but
primarily to avoid parts of the route that were becoming badly eroded and to
keep clear of farming land. The present distance is about 37 km but times
are estimated as 15-20 minutes slower than in the earliest years, suggesting
that the distance originally was on the order of 32 km. Changes since 1996
have been relatively minor and event records are considered from 1996. In
1981, a severe blizzard struck the area on the day before the race was due to
take place and all access roads became impassable. On the hillsides the snow
drifts were up to 20 feet deep and so the race was rescheduled for October 11th.
29 Apr
2017
2:49:38
Murray Strain (SCO)
3:09:19
Victoria Wilkinson-3
30 Apr
2016
2:48:58
Marc Lauenstein (SUI)
3:26:47
Victoria Wilkinson-2
25 Apr
2015
2:51:42
Ricky Lightfoot-2
3:27:24
Helen Bonsor (SCO)
26 Apr
2014
2:53:16
Ricky Lightfoot (ENG)
3:21:32
Victoria Wilkinson (ENG)
27 Apr
2013
2:54:39
Joe Symonds-2
3:33:04
Jasmin Paris
28 Apr
2012
2:55:58
Joe Symonds (SCO)
3:28:46
Sarah O'Neill (SCO)
2:53:34
Thomas Owens (GBR)
3:30:00
Anna Frost (NZL)
3:02:34
Morgan Donnelly (ENG)
3:30:45
Anna Lupton-2
2:54:53
Robert Jebb-4
3:36:31
Anna Lupton (ENG)
2:53:39
Jethro Lennox (SCO)
3:14:43
Anna Pichrtova (CZE)
29 Apr
2007
2:51:49
Robert Jebb-3
3:30:22
Mary Wilkinson (ENG)
Robert Jebb-2
Helen Sedgwick (ENG)
Robert Jebb (ENG)
Sally Malir (ENG)
Andy Pearce-4
Louise Sharp (ENG)
3:06:27
David Walker (ENG)
Beverley Whitfield (ENG)
3:10:43
Simon Booth-2
Tracey Brindley (SCO)
---
cancelled
---
cancelled
2:52:43
Simon Booth (WAL)
Sally Newman
3:04:48
Mark Croasdale (ENG)
Angela Mudge (SCO)
3:03:31
Mark Roberts (WAL)
Carol Greenwood-3
2:52:28
Ian Holmes (ENG)
Carol Greenwood-2
2:46:03
Andy Peace-3
Sarah Rowell-4
2:52:52
Andy Peace-2
Jean Rawlinson (ENG)
2:56:52
Andy Peace (ENG)
Sarah Rowell-3
3:05:17
Gavin Bland
Carol Greenwood (ENG)
3:01:11
Ian Ferguson-3
Sarah Rowell-2
2:51:41
Ian Ferguson-2
Sarah Rowell (ENG)
3:00:51
Gary Devine (ENG)
Ruth Pickvance (ENG)
2:51:45
Shaun Livesey-2
Vanessa Brindle-4
2:57:29
Ian Ferguson (ENG)
Vanessa Brindle-3
3:00:01
Hugh Symonds-3
Vanessa Brindle-2
2:56:40
Shaun Livesey
Carol
Walkington-2
2:49:13
Hugh Symonds-2
Vanessa Brindle (ENG)
2:50:34
Hugh Symonds (ENG)
Bridget Hogge
2:53:34
Kenneth Stuart (ENG)
Carol Walkington (ENG) + Wendy Dodds
(ENG)
2:37:30
Jonathan Wild (ENG)
Jane Robson (ENG)
2:56:34
Harry Walker-3
Fiona Hinde (SCO)
2:43:32
Mike Short (ENG)
Sheila Parkin
29 Apr
1979
2:53:11
Harry Walker-2
Jean Lochhead (WAL)
30 Apr
1978
2:43:34
Harry Walker (ENG)
24 Apr
1977
2:51:04
John Calvert-2
2:43:59
John Calvert (ENG)
2:41:37
Jeffrey Norman-6
2:29:53
Jeffrey Norman-5
2:31:58
Jeffrey Norman-4
2:36:27
Jeffrey Norman-3
2:36:26
Jeffrey Norman-2
2:48:11
Jeffrey Norman (ENG)
2:44:44
Colin Robinson (ENG)
2:40:34
Mike Davies-4
2:47:19
Mike Davies-
2:53:22
Mike Davies-2
2:47:00
Mike Davies (ENG)
2:53:00
Peter Hall (ENG)
3:18:37
Dennis Hopkinson (ENG)
3:00:07
Geoff Hodgson-2
3:05:10
Geoff Hodgson (ENG)
2:58:53
Frank Dawson-2
3:13:25
Frank Dawson (ENG)
3:08:25
George Brass-2
3:33:50
Paul Dugdale (ENG)
3:33:15
Jack Bloor (ENG)
3:28:45
George Brass (ENG)
Fred
Bagley (ENG)
Most Wins
(1954-date)
Men
6
Jeffrey Norman
(ENG)
1970-75
Women
4
Vanessa Brindle
(ENG)
1985,1987-89
Sarah Rowell
(ENG)
1991-92,1994,1996
Prize Money
(ARRS qualified runners)
Prize money has not been awarded in this race according to available information.
Race Time Bias
(sec/km)
Insufficient data to calculate the race time bias.
Competitive Level
(1990-date)
Insufficient data to calculate the competitive level.
Finishers
Year Men Women M+F
2012
559 82
641
2011
582 95
677
2010
526 76 602
2009
541 74 615
2008
576 109 685
2007
416 43 459
2006 323
40 363
2005 309
31 340
2004 364
43 407
2003 183 22
205
2002 192 15
207
.... cancelled
2000 369 41
410
1999 308 25
333
1998 349 23
372
1997 404 22
426
1996 381 34
415
1995 395 21
416
1994 407 24
431
1993 404 27
431
1992 387 29
416
1991 377 29
406
1990 379 18
397
1989 410 15
425
1988 404 18
422
1987 408 16
424
1986 399 17
416
1985 356 13
369
1984 369 8
377
1983 341 6
347
1982 314 3
317
1981 265 2
267
1980 302 9
311
1979 320 8
328
1978 336
336
1977 352
352
1976 319
319
1975 246
246
1974 251
251
1973 202
202
1972 197
197
1971 193
193
1970 142
142
1969 116
116
1968 118
118
1967 12
12
1966 93
93
1965 97
97
1964 75
75
1963 45
45
1962 54
54
1961 49
49
1960 47
47
1959 29
29
1958 26
26
1957 17
17
1956 13
13
1955 13
13
1954 3
3
Sums 15549 1033
16582
M/F
15.05
Last Updated on
07 May 2017
Contributors: Bill Wade, Juraj Gasparovic (50), Thierry Lefeuvre (11), Neil Shuttleworth (5), Mick McGeoch (5)


Spatial Sequencing Analysis Pipeline.
SSAM-lite is a complete spatial sequencing analysis pipeline that runs entirely in your browser.
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Parameters
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Step 1: Kernel Density Estimation
As a fist step, we run a KDE that creates a density of mRNA expression.
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Step 2: Cell Assignments
We can now infer cell types.
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About
The SSAM framework was conceived by Dr. Jeongbin Park
as part of his PhD project at the Berlin Institute of Health.
Read the original SSAM publication
to learn more about the methods.
SSAM-lite-Server has been designed and implemented by Seastian Tiesmeyer and Shashwat Sahay at the Berlin Institute of Health.
Learn more about SSAM-lite here.
For a comprehensive documentation of the SSAM-lite tool check out our
Read the Docs page.
If you are using SSAM-lite for your research please cite:
Tiesmeyer S, et al. 2021. SSAM-lite: a light-weight web app for rapid analysis of spatially resolved transcriptomics data.
bioRxiv. doi: 10.1101/2<IP_ADDRESS>2194
Designed and implemented by Sebastian Tiesmeyer, BIH.