When I started planning out Beerpad, I wanted to focus on fun beer ideas.  Once I had my designs, I wanted to prototype the juicy real features right away. Enter Heroku. Heroku is a service for hosting Ruby webapps. I've been interested in the service since I saw Adam Wiggins demo it at a SVC Ruby Meetup. Heroku is a one-stop service for starting a database-backed, Rack compatible, Ruby webapp. They use git to version control your code, Thin to serve your traffic, and Postgresql to store your data. They also have add-ons that webapps may find useful. I've been looking for an excuse to play with the service, and Beerpad fit the bill perfectly. Follow the jump for my experiences.
Before I got started, I read through their well-written documentation. It's good to get a high-level architectural overview of Heroku's infrastructure to appreciate how much plumbing the service abstracts. If you're familiar with deploying a Rails app on a Linux system and use git as your VCS, the learning curve isn't steep. That said, because Heroku manages your entire software stack, there'll more than one layer that you'll need to reference when you're first starting out.
The first step was to generate my blank Rails project. I chose to use postgresql locally to mirror the production environment closer, and also because I had it setup for previous projects. Once I verified my application ran locally, I added Heroku as a git remote source and pushed. The really cool part here is that Heroku uses git's post receive hook to package your dependencies with Gem bundler and deploy it on their infrastructure.
As someone who has deployed several different Rails apps with capistrano and different requirements, my jaw dropped when I saw in my terminal:
-----> Heroku receiving push
-----> Gemfile detected, running Bundler
All dependecies are satisfied
Locking environment
-----> Rails app detected
-----> Installing Exceptional plugin from
-----> git://github.com/contrast/exceptional.git...done.
-----> Installing quick_sendgrid plugin from
-----> git://github.com/pedro/quick_sendgrid.git...done.
-----> Installing New Relic plugin...done.
Compiled slug size is 7.6MB
-----> Launching.......... done
http://beerpad.heroku.com deployed to Heroku
With a simple "git push heroku", Heroku resolved my gem dependencies, installed add-ons to handle exception reporting, emails, and performance monitoring, and restarted the app servers.
Sure, I've accomplished all of these things before with my other apps, but each of those tasks had to be thought out separately, written, and maintained. I love the git workflow abstraction.  Your app's online. Rinse and repeat, and you have an amazing prototyping tool. I don't miss configuring capistrano, databases, and postfix. I don't miss having separate credentials for github, amazon web services, monitoring, and servers.
As much as I love the service up to this point, not everything was smooth sailing. At one point, when I pushed the code, Beerpad would barf up a completely cryptic backtrace. Trying to access the app via the online dashboard would cause the dashboard to barf with a 500 server error. Emailing back and forth with support indicated that it was a known bug they're working on, and the fix was to delete and re-add my project.
Now I didn't mind the outage because Beerpad is a toy application with zero traffic, but if my bread and butter app mysteriously died and the fix after 24 hours was to delete and re-add, heads would've rolled.
Another annoyance is only 100 lines of logs are kept. Down the line, I can imagine an add-on to address this, but in the meantime, people sent their log data to external services. This works, but definitely isn't in the spirit of removing plumbing responsibilities from the user.
Definitely. Without a doubt, I see Heroku's value. It consolidates several services into one, adds a functional dashboard, and has room for extensibility. It saves you a ton of time on plumbing unrelated to your webapp. If you're starting a new Ruby webapp, whether personal or commercial, you'd be nuts to duplicate the work the Heroku guys have done. On top of that, because you won't have a dedicated systems team (read: $$$), you'll end up doing a much worse job.
If you have an existing app and a well defined deployment process, the story changes. Replacing one good process with another is a lot of work and might not be worth it. But that decision needs to be weighed on a case by case basis. For new projects, Heroku is freaking awesome.


{{ with .Site.Author.image }} {{ end }} {{ .Site.Author.name | default .Site.Title }} {{ partialCached "author-links.html" . }} {{ .Site.Author.bio }} I am bit talkative and if you want to know more, read here. {{ .Content | emojify }}


{{ define "content" }}
Information about this process.
| Name | Value |
|---|---|
| # Threads | {{.Threads}} |
| # Goroutines | {{.Goroutines}} |
| Effective Group Id | {{.Egid}} |
| Effective User Id | {{.Euid}} |
| Group Id | {{.GID}} |
| Groups | {{.Groups}} |
| Hostname | {{.Hostname}} |
| Parent Process Id | {{.Ppid}} |
| Process Id | {{.Pid}} |
| Temporary Directory | {{.TempDir}} |
| User Id | {{.UID}} |
| Working Directory | {{.Wd}} |


{% extends "layout.html" %} {% from "components/card/template.html" import Card -%} {% block article_body %}
France will elect a new president with voting in April and May, in what is set to be an unpredictable and closely fought battle between traditional and ‘outsider’ candidates.
This is the FT’s guide to the contenders.
{# repeating card section starts #} {% for item in cards.selected %} {{ Card(item) }} {% endfor %} {# repeating card section ends #} {% if cards.unfilled.length > 0 %}


Hello fellow inhabitants of Earth, I'm currently a sophomore at Western Reserve Academy and currenly live in Hammond Indiana.


|
Home >
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Participants >
FireEye > Carbanak+FIN7 Configuration
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FireEye Configuration
Product Versions
- FireEye Endpoint Security 5.0.1 with agent 32.30.12
- Helix Security Platform 2020.6.1
| Name | Version | Purpose |
|---|---|---|
| AMSI | 1.0.0 | Detection of script-based attacks |
| Enricher | 1.3.5 | Automated analysis of files via FireEye Intelligence and FireEye Detection on Demand |
| Event Streamer | 1.1.7 | Streaming of Windows event log data to Helix Security Platform |
| Logon Tracker | 0.4.4 | Detection of lateral movement |
| Process Guard | 1.4.1 | Detection of LSASS credential dumping |
| Process Tracker | 1.2.4 | Detection of unique file execution for submission to Enricher |
| UAC Protect | 1.0.9 | Detection of UAC bypass attacks |
Product Description
FireEye Endpoint Security:
FireEye knows that not all breaches can be prevented; attackers are constantly changing to find new vectors and exploits. Breaches can be mitigated by detecting early and responding to the breaches that matter. These breaches are seen every day through the incidents to which Mandiant responds. FireEye Endpoint Security brings the knowledge and experience of these responders to all of our customers. Using a best practices defense in depth, Endpoint Security combines both Endpoint Protection and Endpoint Detection and Response into a single agent.
Endpoint detection and response (EDR) capabilities are enabled through a real-time Indicators of Compromise (IOC) engine that uses current, frontline intelligence to identify advanced threats and enable response. This defense in depth strategy helps protect organizations by both preventing and reducing detection time of attacks. Native forensic capabilities and the ability to rapidly search EDR data and operating system artifacts at enterprise scale empower analysts and investigators to efficiently search for compromise, determine the scope of attacks and resolve incidents.
Protection is provided by three built-in protection engines; filtering out the known malware using a signature-based engine, blocking unknown and advanced malware with our machine learning engine, MalwareGuard, and stopping business application and browser exploits with our behavior-based analytics engine, ExploitGuard.
To create new protection engines and add new features, FireEye introduced Modules for Endpoint Security. These modules are created to respond to a new threat vector or create new features outside of a normal release cycle. By using modules and the Host Sets, protection and alerting can be customized to the endpoint based on likelihood and impact of an attack. Additionally, modules can be deployed based on events, such as when an incident response is in process, certain modules can provide key data for investigators. Modules are provided for protection, detection and response and for additional management features. All modules are available from the FireEye Market.
Although MITRE did not evaluate MSSP coverage in this year’s evaluation, Endpoint Security can be enhanced through a managed detection and response (MDR), Mandiant Managed Defense. Managed Defense combines industry-recognized cyber security expertise, FireEye technology and unparalleled knowledge of attackers to help minimize the impact of a breach. Our battle-savvy security analysts provide a comprehensive assessment of attacker activity along with customized response recommendations, delivering the context needed to understand threats, assess risk and take definitive action.
Even with the best protection, breaches are inevitable. To ensure a substantive response that minimizes business disruption, FireEye Endpoint Security provides tools to:
- Search for and investigate known and unknown threats on tens of thousands of endpoints in minutes
- Identify and detail vectors an attack used to infiltrate an endpoint
- Determine whether an attack occurred (and persists) on a specific endpoint and where it spread
- Establish timeline and duration of endpoint compromises and follow the incident
- Clearly identify which endpoints and systems need containment to prevent further compromise
Primary Features:
- Single agent with four engines for protection, detection and enabling response.
- Single integrated workflow to analyze and respond to threats
- Triage Summary and Audit Viewer for exhaustive inspection and analysis of threats
- Enterprise Search to rapidly find and illuminate suspicious activity and threats
- Customer downloadable modules for enhanced protection, detection and additional features
Product Configuration
Malware protection, MalwareGuard, Exploit Guard and Real-time Indicator Detection were enabled for the test. AMSI, Event Streamer, Process Tracker, Enricher, Logon Tracker, UAC Protect and Process Guard modules were also enabled. All engines were enabled in detection-only mode, per test requirements.
FireEye Endpoint Security allows customers to create and upload their own security content (in addition to what we provide them). To showcase this capability, we used our production security content, as well as all ATT&CK specific security content. FireEye has released the ATT&CK security content to our customer Marketplace as Endpoint Security Supplementary IOCs.


Welcome
Getting Started
Bonjour
world
Click to view this page's source
src/posts/bonjour.html.md
--- title: 'Bonjour' layout: 'post' tags: ['greeting','french'] --- Bonjour **world**


Fun in the Sky
For the best views of Mount Maunganui, you can't get better than a scenic flight. These offer sights of Mauao, Tauranga city and the surrounding beaches and islands
If you're feeling a bit more adventurous you can opt to parasail from the top of Mauao (tandem flights with a qualified instructor are available!)


Euromillions lottery winning ticket bought in Batterstown
by John DonohoeA EuroMillions player in Meath is €41,248 better off after matching five numbers on last night’s EuroMillions draw (Friday 22nd November). There was no winner of the €17,000,000 jackpot.
The winning Quick Pick ticket was sold in The Village Pump, Batterstown.
The winning numbers from the main EuroMillions draw were: 03, 21, 32, 34 and 48 and the lucky star numbers were: 03 and 11. More than 51,000 Irish players won prizes on last night’s draw.
A National Lottery spokesperson said: “We are urging all our EuroMillions players across the country to check their tickets to see if they have won prizes but particularly those who played in Batterstown as somebody has won this cool €41,248 prize, which will surely come in handy as we come into the festive season! If you find you are the winner of the €41,248 prize, be sure to sign the back of the ticket, keep the ticket safe and contact our prize claims team on 01 836 4444 and we will make arrangements for you to come to the National Lottery to get your prize.”


{{product.ProductDescription}}
Define style this season with Armani's new range of trendy tops, crafted with intricate details. Create a chic statement look by teaming this lace number with skinny jeans and pumps.


Package com.lukflug.panelstudio
Interface Interface
public interface Interface
Interface to abstract rendering and input methods.
-
Field Summary
-
Method Summary
Modifier and Type Method Description void
drawImage(java.awt.Rectangle r, int rotation, boolean parity, int image)
Draw an image.void
drawLine(java.awt.Point a, java.awt.Point b, java.awt.Color c1, java.awt.Color c2)
Draw a line on the screen.void
drawRect(java.awt.Rectangle r, java.awt.Color c1, java.awt.Color c2, java.awt.Color c3, java.awt.Color c4)
Draw the outline of an axis-aligned rectangle on the screen.void
drawString(java.awt.Point pos, java.lang.String s, java.awt.Color c)
Draw a string on the screen.void
fillRect(java.awt.Rectangle r, java.awt.Color c1, java.awt.Color c2, java.awt.Color c3, java.awt.Color c4)
Draw an axis-aligned rectangle on the screen.void
fillTriangle(java.awt.Point pos1, java.awt.Point pos2, java.awt.Point pos3, java.awt.Color c1, java.awt.Color c2, java.awt.Color c3)
Draw a triangle on the screen.boolean
getButton(int button)
Method to query the current mouse button state.int
getFontHeight()
Get height of font rendered bydrawString(Point, String, Color)
int
getFontWidth(java.lang.String s)
Get the font width of a string being rendered bydrawString(Point, String, Color)
java.awt.Point
getMouse()
Method to query the current mouse position.int
loadImage(java.lang.String name)
Load an image into memory and return a number that may be used to draw that image.void
restore()
Restore the clipping to the previous state.void
window(java.awt.Rectangle r)
Clip all rendering on screen outside the intersection of the specified rectangle and the current clipping rectangle.
-
Field Details
-
LBUTTON
static final int LBUTTONID for the left mouse button.- See Also:
getButton(int)
, Constant Field Values
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RBUTTON
static final int RBUTTONID for the right mouse button.- See Also:
getButton(int)
, Constant Field Values
-
-
Method Details
-
getMouse
java.awt.Point getMouse()Method to query the current mouse position. May be called by any GUI-related method.- Returns:
- current mouse position
-
getButton
boolean getButton(int button)Method to query the current mouse button state. May be called by any GUI-related method. -
drawString
void drawString(java.awt.Point pos, java.lang.String s, java.awt.Color c)Draw a string on the screen. May only be called in a GUI rendering method.- Parameters:
pos
- the position of the string on the screens
- the string to be displayedc
- the color of the string to be displayed
-
getFontWidth
int getFontWidth(java.lang.String s)Get the font width of a string being rendered bydrawString(Point, String, Color)
- Parameters:
s
- the string to be considered- Returns:
- the font width
-
getFontHeight
int getFontHeight()Get height of font rendered bydrawString(Point, String, Color)
- Returns:
- the font height
-
fillTriangle
void fillTriangle(java.awt.Point pos1, java.awt.Point pos2, java.awt.Point pos3, java.awt.Color c1, java.awt.Color c2, java.awt.Color c3)Draw a triangle on the screen. The color of the triangle should ideally be smoothly interpolated. May only be called in a GUI rendering method.- Parameters:
pos1
- the first corner of the trianglepos2
- the second corner of the trianglepos3
- the third corner of the trianglec1
- the color at the first cornerc2
- the color at the second cornerc3
- the color at the third corner
-
drawLine
void drawLine(java.awt.Point a, java.awt.Point b, java.awt.Color c1, java.awt.Color c2)Draw a line on the screen. The color of the line should ideally be smoothly interpolated. May only be called in a GUI rendering method.- Parameters:
a
- the start of the lineb
- the end of the linec1
- the color at the start of the linec2
- the color at the end of the line
-
fillRect
void fillRect(java.awt.Rectangle r, java.awt.Color c1, java.awt.Color c2, java.awt.Color c3, java.awt.Color c4)Draw an axis-aligned rectangle on the screen. The color of the rectangle should ideally be smoothly interpolated. May only be called in a GUI rendering method.- Parameters:
r
- the rectangle to be renderedc1
- the color at the top-left corner of the rectanglec2
- the color at the top-right corner of the rectanglec3
- the color at the bottom-right corner of the rectanglec4
- the color at the bottom-left corner of the rectangle
-
drawRect
void drawRect(java.awt.Rectangle r, java.awt.Color c1, java.awt.Color c2, java.awt.Color c3, java.awt.Color c4)Draw the outline of an axis-aligned rectangle on the screen. The color of the rectangle should ideally be smoothly interpolated. May only be called in a GUI rendering method.- Parameters:
r
- the rectangle to be renderedc1
- the color at the top-left corner of the rectanglec2
- the color at the top-right corner of the rectanglec3
- the color at the bottom-right corner of the rectanglec4
- the color at the bottom-left corner of the rectangle
-
loadImage
int loadImage(java.lang.String name)Load an image into memory and return a number that may be used to draw that image. Should only be called during initialization. The name string should ideally be the filename of the image, not including the path, since the implementation of this interface must ideally provide the directory in which the images are located.- Parameters:
name
- a string indicating the location of the image to be loaded- Returns:
- a number identifying the image
- See Also:
drawImage(Rectangle, int, boolean, int)
-
drawImage
void drawImage(java.awt.Rectangle r, int rotation, boolean parity, int image)Draw an image.- Parameters:
r
- the rectangle specifying the position of the imagerotation
- the rotation of the image in units of 90 degrees counter-clockwiseparity
- if true, will switch the top-left and bottom-right, the bottom-left and top-right cornersimage
- the number identifying the image- See Also:
loadImage(String)
-
window
void window(java.awt.Rectangle r)Clip all rendering on screen outside the intersection of the specified rectangle and the current clipping rectangle. May only be called in a GUI rendering method. The calling method should restore clipping by callingrestore()
after rendering.- Parameters:
r
- the clipping rectangle- See Also:
restore()
-
restore
void restore()Restore the clipping to the previous state.- See Also:
window(Rectangle)
-


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Access Control -- Passwords Use the fields below to enter 8 to 32 characters and click "Apply/Save" to change or create passwords. Note: Don't use spaces at the beginning or end of the password. Nor enter multiple consecutive spaces. Old Password: New Password: Confirm Password:


When called, it checks current value of $location.hash()
and scroll to related element,
according to rules specified in
Html5 spec.
It also watches the $location.hash()
and scroll whenever it changes to match any anchor.
This can be disabled by calling $anchorScrollProvider.disableAutoScrolling()
.
$anchorScroll();


The waddle of the geese across the lake was like the exchange of wampum between the Native Americans, as they built their homes with wallboard and clay-ware. [G|D]
AI:The gentle waft of a warm breeze was so wan and wee that it couldn't even weld the two branches together, but it was enough to bring some peace. [G|D]
The little fish wiggled its way through the wildfowl just outside the bay, but those same waters held a wickedly mysterious wickedness that scared all the creatures away. [G|D]
The wobblyyachtsman, trying to live out his dream, yammered on about his plans and his zeal as he set sail towards the horizon. [G|D]


Book Maintenance
If you wish to delete a Book, enter the ISBN of the book below and click on delete.


Base Peak Chromatogram
* upgrading to a modern browser enables better graphics, zoom and scan click-through capabilities...


--- layout: default --- {% include nav.html %}
I like doors, and I hope you like these doors too! :smile:
This website is made using Jekyll and is hosted by GitHub, the code is available at robbrenn.github.io
Rarebit refers to Welsh rarebit, but I also like the idea of having a few bytes of rare bits.
Special thanks to Long Qian for their Jekyll Tags guide that helped me realise Github only allows some plugins, and not the useful jekyll-tagging plugin, and provided example code for adding tags to posts.


We have completed over 30 projects today both locally and at international locations. Enclose below is our seleted list of references.
In 2007 and through open competitive bidding, we were awarded our single largest contract worth some USD 30 million by Petronas Methanol Labuan for the engineering, procurement, construction and commissioning assistance of three hot oil heaters for the Labuan Gas Terminal.
This contract entails the engineering design of three new hot oil heaters together with the hot oil expansion and recirculation system. We had the privilege to collaborate with Linde Impianti (for the heater design) and Kencana Bestwide (for the local engineering support and E&I works). Project was completed ahead of schedule and while achieving an overall local content of more than 70%!
This milestone achievement propelled us further as a true integrated service provider.
| Enduser/Client | Location | Contract Value (RM) | Scope of Supply | Date of award / completion |
|---|---|---|---|---|
| Alwich Enviro-Management Sdn Bhd/Best Wide Matrix | Kemaman,Terengganu | 150,000 | 13 Nos. Process Filters / Strainers | Aug/Nov 04 |
| Amsteel Mills Sdn Bhd | Labuan, Sabah | 500,000 | Engineering, procurement & delivery of Oxygen Injection skid | Sept 04/May 05 |
| Linde AG | Skopje, Greece | 120,000 | Refurbishment of ASU Coldbox | Oct/Dec 04 |
| CIC Environmental Services Sdn Bhd | Kuala Belait,Brunei | 60,000 | Design & Fabrication of Furnace Helical Coil | Dec 04/Feb 05 |
| Sabah Forest Industries Sdn Bhd | Sipitang, Sabah | 30,000 | Insulation material for Coldbox | Jan/Mar 05 |
| Optimal Olefins Sdn Bhd | Kerteh,Terengganu | 50,000 | Supply of knock-out vessel filtration pads | Nov 05/Dec 05 |
| Petronas Methanol Labuan Sdn Bhd | Labuan, Sabah | 26,000,000 | EPC + Commissioning assistance of Hot Oil Heater system package | July 08/Sept 10 |


Edit Plot
Erase Plots
Edit Title
Edit X Axis Title
Edit Y Axis Title
Export Data
Export Plots
Toggle Slider
Get Sample Data
Visualization Toolkit
X
Select Plot Options
Step 1: Select Device
Spectra
Vega
Vicra
Optotrak
Certus
AAK
Astra
Step 2: Select Test
Step 3 : Pick Plots
Selected Plots
Step 4 : Select Plotting Options
Include failed and repeated characterizations
Limit data to current year's results
Plot by date
Custom date range
Custom Plot
Date Selection options
Select range
Select all before date
Select all after date
Add Plot
Filter Points


--- layout: base title: Home page ---
Version: {{ site.current_version }}
This site contains developer documentation for the following resources:
NOTE: This project is in development, so stay tuned for more additions and improvements in the coming months. The design for this site is a basic placeholder using core styles from Apollo. A new design will be implemented when these docs are incorporated into the Design Resource Base later this year.


Accountant, Ledger Associates
First Name
Maria
Last Name
Rodriguez
Occupation
Accountant
Company
Ledger Associates
Birthday
04 Feb 1988
Address
345 Maple St.
City
Madison
Contact Number
6085557683
Email
<EMAIL_ADDRESS>08 August 2012
Hamster
2693 Commerce St., McFarland
+6085558763


Background
An Aggregate is an object or collection of objects (Entities and Value Objects) that must be treated as a single unit for the purposes of a business transaction. The Aggregate will maintain all invariants for all objects that comprise the Aggregate, enforcing all business rules internal to the Aggregate.
Aggregate Root
All Aggregates have a single point of entry that is know as the root. The Aggregate Root is the interface to the external world. All interaction with an Aggregate is via the Aggregate Root. As such, an Aggregate Root MUST have a globally unique identifier within the system. Other Entites that are present in the Aggregate but are not Aggregate Roots require only a locally unique identifier, that is, an Id that is unique within the Aggregate. For example, an Order will contain Order Lines. The Order is the Aggregate Root and must have a unique Order Id. The Order Lines cannot be accessed directly. Any updates to Order Lines must be via the Order. That is, you ask the Order to make the change to IT'S Order Line. An Order Line is only required to be identifiable with the Order therefore it is permissible to have Order Line Id's such as 1,2,3 etc. on each order. It is, of course, valid to use a globally unique identifier onthe Order Line for persistence purposes, while having a locally unique candidate key for presentation.
It is not permissible to have references to entities or value objects from an Aggregate Root other than the Aggregate Root itself. In a CQRS system, it is permissible, indeed required, to have read models that have data from one or more Aggregate Roots.
Modelling
The modelling of an Aggregate Root is based on the invariants that must be maintained when updating. In our example above, an Order will perform aggregate functions on the order lines (e.g. summing the totals, assigning ids, maintaining ordering, etc.) and therefore will potentially update all order lines at the same time. An Aggregate is essentially a business transaction and should include everything that has to be kept consistent.
System Invariants
The Aggregate maintains only internal invariants. It is not responsible for maintaining invariants between Aggregates. For example, it is not the responsiblity of the individual Aggregate to ensure that a Username is unique. It is the responsibility of the System as a whole to maintain these system invariants. The exact mechanism it uses will depend on the invariant and the consequences of breaking them.
Note
What you must learn is that these rules are no different that the rules of a computer system. Some of them can be bent. Others can be broken. Morpheus, The Matrix
All rules are not created equal. Business Rules are essentially business problems, not primarily technical problems. It may be simpler and cheaper to break a rule and then clean it up later in a compensating transaction, than to expend a lot of time, energy and money ensuring the rule is not broken.
Aggregate Roots in doLittle
doLittle provides a base class AggregateRoot that implements functionality that makes it easier to rehydrate Aggregate Roots, generate events and persist these to the Event Store. The AggregateRoot is an implementation of an Event Source. It is recommended that all your Aggregate Root classes inherit from this class.
State
In doLittle, an Aggregate is a purely WRITE concern. It plays no roll in reading or presentation. As such, an Aggregate must not expose any public state, via variables or properties. Neither should the Aggregate return any of its internal entities or values objects, even in a transient state. The Aggregate is only required to keep such internal state that it requires to maintain its invariants. Since no public state is exposed by the Aggregate it does not need to keep in state values that are not
Identity
All AggregateRoot classes must have a Guid key. It is permissible to include other candidate keys, though these should have a map to the Guid.
Rehydration
AggregateRoots are an Event Source and their internal state is rehydrated from the persistance store by replaying the events associated with this instance. doLittle distinguishes between CommittedEventStreams, which are persisted to the Event Store and UncommittedEventStreams which are not persisted. A CommittedEventStream can be replayed against an AggregateRoot and each Event re-applied. Since the Event is responsible for setting an internal state, the AggregateRoot will be returned to its actual state when all Events are re-applied. The CommittedEventStream is a perfect audit record of all changes of the AggregateRoot.


Appalachia is a cultural region in the Eastern United States that stretches from the Southern Tier of New York to northern Alabama and Georgia.
While endowed with abundant natural resources, especially coal, Appalachia has long struggled and been associated with poverty. Native American
hunter-gatherers first arrived in what is now Appalachia over 16,000 years ago. Since then there has been many influences in the Appalachian culture,
influences such as Scottish, English, African American, German, and Irish. Each of these regions have made an influence in the music, traditions, and
styles of living in the Appalachian region.
One of the most iconic symbols of Appalachian culture— the banjo— was brought to the region by African-American slaves in the 18th century. Black banjo players were performing in Appalachia as early as 1798, when their presence was documented in Knoxville, Tennessee.


Module: exposure
¶
|
Performs Gamma Correction on the input image. |
|
Performs Logarithmic correction on the input image. |
|
Performs Sigmoid Correction on the input image. |
Return cumulative distribution function (cdf) for the given image. |
|
|
Contrast Limited Adaptive Histogram Equalization (CLAHE). |
|
Return image after histogram equalization. |
|
Return histogram of image. |
|
Determine if an image is low contrast. |
|
Adjust an image so that its cumulative histogram matches that of another. |
|
Return image after stretching or shrinking its intensity levels. |
adjust_gamma¶
-
skimage.exposure.
adjust_gamma
(image, gamma=1, gain=1)[source]¶ Performs Gamma Correction on the input image.
Also known as Power Law Transform. This function transforms the input image pixelwise according to the equation
O = I**gamma
after scaling each pixel to the range 0 to 1.- Parameters
- imagendarray
Input image.
- gammafloat, optional
Non negative real number. Default value is 1.
- gainfloat, optional
The constant multiplier. Default value is 1.
- Returns
- outndarray
Gamma corrected output image.
See also
Notes
For gamma greater than 1, the histogram will shift towards left and the output image will be darker than the input image.
For gamma less than 1, the histogram will shift towards right and the output image will be brighter than the input image.
References
Examples
>>> from skimage import data, exposure, img_as_float >>> image = img_as_float(data.moon()) >>> gamma_corrected = exposure.adjust_gamma(image, 2) >>> # Output is darker for gamma > 1 >>> image.mean() > gamma_corrected.mean() True
Examples using skimage.exposure.adjust_gamma
¶
adjust_log¶
-
skimage.exposure.
adjust_log
(image, gain=1, inv=False)[source]¶ Performs Logarithmic correction on the input image.
This function transforms the input image pixelwise according to the equation
O = gain*log(1 + I)
after scaling each pixel to the range 0 to 1. For inverse logarithmic correction, the equation isO = gain*(2**I - 1)
.- Parameters
- imagendarray
Input image.
- gainfloat, optional
The constant multiplier. Default value is 1.
- invfloat, optional
If True, it performs inverse logarithmic correction, else correction will be logarithmic. Defaults to False.
- Returns
- outndarray
Logarithm corrected output image.
See also
References
Examples using skimage.exposure.adjust_log
¶
adjust_sigmoid¶
-
skimage.exposure.
adjust_sigmoid
(image, cutoff=0.5, gain=10, inv=False)[source]¶ Performs Sigmoid Correction on the input image.
Also known as Contrast Adjustment. This function transforms the input image pixelwise according to the equation
O = 1/(1 + exp*(gain*(cutoff - I)))
after scaling each pixel to the range 0 to 1.- Parameters
- imagendarray
Input image.
- cutofffloat, optional
Cutoff of the sigmoid function that shifts the characteristic curve in horizontal direction. Default value is 0.5.
- gainfloat, optional
The constant multiplier in exponential’s power of sigmoid function. Default value is 10.
- invbool, optional
If True, returns the negative sigmoid correction. Defaults to False.
- Returns
- outndarray
Sigmoid corrected output image.
See also
References
- 1
Gustav J. Braun, “Image Lightness Rescaling Using Sigmoidal Contrast Enhancement Functions”, http://www.cis.rit.edu/fairchild/PDFs/PAP07.pdf
cumulative_distribution¶
-
skimage.exposure.
cumulative_distribution
(image, nbins=256)[source]¶ Return cumulative distribution function (cdf) for the given image.
- Parameters
- imagearray
Image array.
- nbinsint, optional
Number of bins for image histogram.
- Returns
- img_cdfarray
Values of cumulative distribution function.
- bin_centersarray
Centers of bins.
See also
References
Examples
>>> from skimage import data, exposure, img_as_float >>> image = img_as_float(data.camera()) >>> hi = exposure.histogram(image) >>> cdf = exposure.cumulative_distribution(image) >>> np.alltrue(cdf[0] == np.cumsum(hi[0])/float(image.size)) True
equalize_adapthist¶
-
skimage.exposure.
equalize_adapthist
(image, kernel_size=None, clip_limit=0.01, nbins=256)[source]¶ Contrast Limited Adaptive Histogram Equalization (CLAHE).
An algorithm for local contrast enhancement, that uses histograms computed over different tile regions of the image. Local details can therefore be enhanced even in regions that are darker or lighter than most of the image.
- Parameters
- image(M, N[, C]) ndarray
Input image.
- kernel_size: integer or list-like, optional
Defines the shape of contextual regions used in the algorithm. If iterable is passed, it must have the same number of elements as
image.ndim
(without color channel). If integer, it is broadcasted to each image dimension. By default,kernel_size
is 1/8 ofimage
height by 1/8 of its width.- clip_limitfloat, optional
Clipping limit, normalized between 0 and 1 (higher values give more contrast).
- nbinsint, optional
Number of gray bins for histogram (“data range”).
- Returns
- out(M, N[, C]) ndarray
Equalized image.
See also
Notes
- For color images, the following steps are performed:
The image is converted to HSV color space
The CLAHE algorithm is run on the V (Value) channel
The image is converted back to RGB space and returned
For RGBA images, the original alpha channel is removed.
References
Examples using skimage.exposure.equalize_adapthist
¶
equalize_hist¶
-
skimage.exposure.
equalize_hist
(image, nbins=256, mask=None)[source]¶ Return image after histogram equalization.
- Parameters
- imagearray
Image array.
- nbinsint, optional
Number of bins for image histogram. Note: this argument is ignored for integer images, for which each integer is its own bin.
- mask: ndarray of bools or 0s and 1s, optional
Array of same shape as image. Only points at which mask == True are used for the equalization, which is applied to the whole image.
- Returns
- outfloat array
Image array after histogram equalization.
Notes
This function is adapted from [1] with the author’s permission.
References
histogram¶
-
skimage.exposure.
histogram
(image, nbins=256, source_range='image', normalize=False)[source]¶ Return histogram of image.
Unlike
numpy.histogram
, this function returns the centers of bins and does not rebin integer arrays. For integer arrays, each integer value has its own bin, which improves speed and intensity-resolution.The histogram is computed on the flattened image: for color images, the function should be used separately on each channel to obtain a histogram for each color channel.
- Parameters
- imagearray
Input image.
- nbinsint, optional
Number of bins used to calculate histogram. This value is ignored for integer arrays.
- source_rangestring, optional
‘image’ (default) determines the range from the input image. ‘dtype’ determines the range from the expected range of the images of that data type.
- normalizebool, optional
If True, normalize the histogram by the sum of its values.
- Returns
- histarray
The values of the histogram.
- bin_centersarray
The values at the center of the bins.
See also
Examples
>>> from skimage import data, exposure, img_as_float >>> image = img_as_float(data.camera()) >>> np.histogram(image, bins=2) (array([107432, 154712]), array([0. , 0.5, 1. ])) >>> exposure.histogram(image, nbins=2) (array([107432, 154712]), array([0.25, 0.75]))
is_low_contrast¶
-
skimage.exposure.
is_low_contrast
(image, fraction_threshold=0.05, lower_percentile=1, upper_percentile=99, method='linear')[source]¶ Determine if an image is low contrast.
- Parameters
- imagearray-like
The image under test.
- fraction_thresholdfloat, optional
The low contrast fraction threshold. An image is considered low- contrast when its range of brightness spans less than this fraction of its data type’s full range. [1]
- lower_percentilefloat, optional
Disregard values below this percentile when computing image contrast.
- upper_percentilefloat, optional
Disregard values above this percentile when computing image contrast.
- methodstr, optional
The contrast determination method. Right now the only available option is “linear”.
- Returns
- outbool
True when the image is determined to be low contrast.
References
Examples
>>> image = np.linspace(0, 0.04, 100) >>> is_low_contrast(image) True >>> image[-1] = 1 >>> is_low_contrast(image) True >>> is_low_contrast(image, upper_percentile=100) False
match_histograms¶
-
skimage.exposure.
match_histograms
(image, reference, *, multichannel=False)[source]¶ Adjust an image so that its cumulative histogram matches that of another.
The adjustment is applied separately for each channel.
- Parameters
- imagendarray
Input image. Can be gray-scale or in color.
- referencendarray
Image to match histogram of. Must have the same number of channels as image.
- multichannelbool, optional
Apply the matching separately for each channel.
- Returns
- matchedndarray
Transformed input image.
- Raises
- ValueError
Thrown when the number of channels in the input image and the reference differ.
References
Examples using skimage.exposure.match_histograms
¶
rescale_intensity¶
-
skimage.exposure.
rescale_intensity
(image, in_range='image', out_range='dtype')[source]¶ Return image after stretching or shrinking its intensity levels.
The desired intensity range of the input and output, in_range and out_range respectively, are used to stretch or shrink the intensity range of the input image. See examples below.
- Parameters
- imagearray
Image array.
- in_range, out_rangestr or 2-tuple, optional
Min and max intensity values of input and output image. The possible values for this parameter are enumerated below.
- ‘image’
Use image min/max as the intensity range.
- ‘dtype’
Use min/max of the image’s dtype as the intensity range.
- dtype-name
Use intensity range based on desired dtype. Must be valid key in DTYPE_RANGE.
- 2-tuple
Use range_values as explicit min/max intensities.
- Returns
- outarray
Image array after rescaling its intensity. This image is the same dtype as the input image.
See also
Examples
By default, the min/max intensities of the input image are stretched to the limits allowed by the image’s dtype, since in_range defaults to ‘image’ and out_range defaults to ‘dtype’:
>>> image = np.array([51, 102, 153], dtype=np.uint8) >>> rescale_intensity(image) array([ 0, 127, 255], dtype=uint8)
It’s easy to accidentally convert an image dtype from uint8 to float:
>>> 1.0 * image array([ 51., 102., 153.])
Use
rescale_intensity
to rescale to the proper range for float dtypes:>>> image_float = 1.0 * image >>> rescale_intensity(image_float) array([0. , 0.5, 1. ])
To maintain the low contrast of the original, use the in_range parameter:
>>> rescale_intensity(image_float, in_range=(0, 255)) array([0.2, 0.4, 0.6])
If the min/max value of in_range is more/less than the min/max image intensity, then the intensity levels are clipped:
>>> rescale_intensity(image_float, in_range=(0, 102)) array([0.5, 1. , 1. ])
If you have an image with signed integers but want to rescale the image to just the positive range, use the out_range parameter:
>>> image = np.array([-10, 0, 10], dtype=np.int8) >>> rescale_intensity(image, out_range=(0, 127)) array([ 0, 63, 127], dtype=int8)


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R/add_n_nodes_ws.R
add_n_nodes_ws.Rd
Add n
new nodes to or from one or more nodes available as a selection
in a graph object of class dgr_graph
. New graph edges will all move
either from the nodes in the selection toward the newly created nodes (with
the option direction = "from"
), or to the selected nodes already in
the graph (using direction = "to"
). Optionally, set node type
and edge rel
values for all the new nodes and edges created,
respectively.
add_n_nodes_ws(graph, n, direction = NULL, type = NULL, label = NULL, rel = NULL, node_aes = NULL, edge_aes = NULL, node_data = NULL, edge_data = NULL)
| graph | a graph object of class |
|---|---|
| n | the number of new nodes to attach as successor nodes to the nodes in the selection. |
| direction | using |
| type | an optional character vector that provides group identifiers for the nodes to be added. |
| label | an optional character object that describes the nodes to be added. |
| rel | an optional string to apply a |
| node_aes | an optional list of named vectors comprising node aesthetic
attributes. The helper function |
| edge_aes | an optional list of named vectors comprising edge aesthetic
attributes. The helper function |
| node_data | an optional list of named vectors comprising node data
attributes. The helper function |
| edge_data | an optional list of named vectors comprising edge data
attributes. The helper function |
a graph object of class dgr_graph
.
This function makes use of an active selection of nodes (and the
function ending with _ws
hints at this).
Selections of nodes can be performed using the following node selection
(select_*()
) functions:
select_nodes()
,
select_last_nodes_created()
,
select_nodes_by_degree()
,
select_nodes_by_id()
, or
select_nodes_in_neighborhood()
.
Selections of nodes can also be performed using the following traversal
(trav_*()
) functions:
trav_out()
,
trav_in()
,
trav_both()
,
trav_out_node()
,
trav_in_node()
,
trav_out_until()
, or
trav_in_until()
.
# Create an empty graph, add a node to it, select # that node, and then add 5 more nodes to the graph # with edges from the original node to all of the # new nodes graph <- create_graph() %>% add_n_nodes(n = 1) %>% select_last_nodes_created() %>% add_n_nodes_ws( n = 5, direction = "from") # Get the graph's nodes graph %>% get_node_ids()#> [1] 1 2 3 4 5 6#> [1] "1->2" "1->3" "1->4" "1->5" "1->6"# Create an empty graph, add a node to it, select # that node, and then add 5 more nodes to the graph # with edges toward the original node from all of # the new nodes graph <- create_graph() %>% add_n_nodes(n = 1) %>% select_last_nodes_created() %>% add_n_nodes_ws( n = 5, direction = "to") # Get the graph's nodes graph %>% get_node_ids()#> [1] 1 2 3 4 5 6#> [1] "2->1" "3->1" "4->1" "5->1" "6->1"


What I do
Back-End
NodeJS, APIs, Microservices, Devops, NoSQL
Front-End
CSS3, Javascript, ES6, React, Angular, Vue
Hardware
MSP430, Arm Cortex M3 & M4, Raspberry Pi
Cloud
AWS, Firebase
Apps
Flutter, Android
I'm Patrick, a true Fullstack engineer. From the devices to the
cloud.
I thrive when I got the chance to combine my recently gained knowledge
in state of the art software engineering and hardware applications.
Some call it IoT, I want to show the benefits in a fully connected
environment.
Links
build
Recent work
As part of the Accenture Liquid Studios we help companies become built
for change through new technologies, skills and ways of working. We
rapidly prototype and deliver software to help you reach customers and
enter new markets.
My responsabilities
Leading technical teams and contributing to the delivery of
prototypes, minimal viable products and production pilots of
disruptive technologies like Artificial Intelligence, Blockchain or
Internet of Things for international companies
Fullfilling tasks as technical Expert for Blockchain, Internet of
Things and hardware design
Coaching new hires and team members in Agile software engineering
methodologies
Side projects
Automotive
I'm a proud co-owner of a VW Bus T3 from 1988. I travel Europe with
my partner and for that I have to use my gained knowledge from my
apprenticeship.
Self driving car
Besides loving to drive by myself I see the real value for the
society within self driving cars. I look forward to see Elon Masks
promise fullfilled, when he announced full self driving capability
end of 2019. Therefore I myself try to protoype some systems. Such
as the
SLAM
or enabling a toy car with simple following the street.
Hardware
In general every Hardware Bit has his place and I love to get to the
Bits. Sometimes this includes applying network sniffing techniques
to Serial Bus systems (ex.
SPI)


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@*
* Copyright 2021 HM Revenue & Customs
*
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
*@
@import uk.gov.hmrc.hmrcemailrenderer.templates.onlinepaymentservice.AmountFormatter.formatAmountInPence
@import uk.gov.hmrc.hmrcemailrenderer.templates.onlinepaymentservice.partials.html.surcharge_recon_row
@(params: Map[String, Any])
@uk.gov.hmrc.hmrcemailrenderer.templates.helpers.html.template_main(params, params("subject").toString) {
Telephone payments via RCS
|
Corporate Debit Card Volume |
Corporate Debit Card Commission Value |
Credit Card Volume |
Credit Card Commission Value |
Grand Total Volume |
Grand Total Commission Value |
| SDLT |
@surcharge_recon_row(params("tpsRcsSurchargeReport_sdlt").toString.split(",").toArray)
| VAT |
@surcharge_recon_row(params("tpsRcsSurchargeReport_vat").toString.split(",").toArray)
| SA |
@surcharge_recon_row(params("tpsRcsSurchargeReport_sa").toString.split(",").toArray)
| SAFE |
@surcharge_recon_row(params("tpsRcsSurchargeReport_safe").toString.split(",").toArray)
| CT |
@surcharge_recon_row(params("tpsRcsSurchargeReport_ct").toString.split(",").toArray)
| PAYE |
@surcharge_recon_row(params("tpsRcsSurchargeReport_epaye").toString.split(",").toArray)
| NTC |
@surcharge_recon_row(params("tpsRcsSurchargeReport_ntc").toString.split(",").toArray)
| NPS/NIRS |
@surcharge_recon_row(params("tpsRcsSurchargeReport_nps").toString.split(",").toArray)
| Total |
@surcharge_recon_row(params("tpsRcsSurchargeReport_total").toString.split(",").toArray)
|
|
|
|
|
To agree Shipley RCS TPS Credit Card Commission |
Online payments via RCS
|
Corporate Debit Card Volume |
Corporate Debit Card Commission Value |
Credit Card Volume |
Credit Card Commission Value |
Grand Total Volume |
Grand Total Commission Value |
| SA |
@surcharge_recon_row(params("opsRcsSurchargeReport_sa").toString.split(",").toArray)
| COTAX |
@surcharge_recon_row(params("opsRcsSurchargeReport_cotax").toString.split(",").toArray)
| PAYE |
@surcharge_recon_row(params("opsRcsSurchargeReport_paye").toString.split(",").toArray)
| MISC |
@surcharge_recon_row(params("opsRcsSurchargeReport_misc").toString.split(",").toArray)
| SDLT |
@surcharge_recon_row(params("opsRcsSurchargeReport_sdlt").toString.split(",").toArray)
| Total Shipley |
@surcharge_recon_row(params("opsRcsSurchargeReport_totalShipley").toString.split(",").toArray)
|
|
|
|
|
To agree Shipley RCS OPS Credit Card Commission |
| VAT |
@surcharge_recon_row(params("opsRcsSurchargeReport_vat").toString.split(",").toArray)
| Total Cumbernauld |
@surcharge_recon_row(params("opsRcsSurchargeReport_totalCumbernauld").toString.split(",").toArray)
|
|
|
|
|
To agree Cumbernauld RCS OPS Credit Card Commission |
Telephone payments via DES plus MODS
|
Corporate Debit Card Volume |
Corporate Debit Card Commission Value |
Credit Card Volume |
Credit Card Commission Value |
Grand Total Volume |
Grand Total Commission Value |
| P800 |
@surcharge_recon_row(params("topsNoModsSurchargeReport_p800").toString.split(",").toArray)
| PNGR |
@surcharge_recon_row(params("topsNoModsSurchargeReport_pngr").toString.split(",").toArray)
| FChB |
@surcharge_recon_row(params("topsNoModsSurchargeReport_childBenefitRepayments").toString.split(","))
| Total |
@surcharge_recon_row(params("topsNoModsSurchargeReport_total").toString.split(",").toArray)
|
|
|
|
|
|
*To agree ETMP BW report - GL Balance 210102014 |
|
Corporate Debit Card Volume |
Corporate Debit Card Commission Value |
Credit Card Volume |
Credit Card Commission Value |
Grand Total Volume |
Grand Total Commission Value |
| MODS |
@surcharge_recon_row(params("topsJustModsSurchargeReport_mods").toString.split(",").toArray)
Online payments via DES plus MODS
|
Corporate Debit Card Volume |
Corporate Debit Card Commission Value |
Credit Card Volume |
Credit Card Commission Value |
Grand Total Volume |
Grand Total Commission Value |
| P800 |
@surcharge_recon_row(params("opsDesNoModsSurchargeReport_p800").toString.split(",").toArray)
| SIMPLE ASSESSMENT |
@surcharge_recon_row(params("opsDesNoModsSurchargeReport_simpleAssessment").toString.split(",").toArray)
| CGT |
@surcharge_recon_row(params("opsDesNoModsSurchargeReport_cgt").toString.split(",").toArray)
| PNGR |
@surcharge_recon_row(params("opsDesNoModsSurchargeReport_pngr").toString.split(",").toArray)
| CDS |
@surcharge_recon_row(params("opsDesNoModsSurchargeReport_cds").toString.split(",").toArray)
| FChB |
@surcharge_recon_row(params("opsDesNoModsSurchargeReport_childBenefitRepayments").toString.split(","))
| Total |
@surcharge_recon_row(params("opsDesNoModsSurchargeReport_total").toString.split(",").toArray)
|
|
|
|
|
|
*To agree ETMP BW report - GL Balance 210102014 |
|
Corporate Debit Card Volume |
Corporate Debit Card Commission Value |
Credit Card Volume |
Credit Card Commission Value |
Grand Total Volume |
Grand Total Commission Value |
| MODS |
@surcharge_recon_row(params("opsDesJustModsSurchargeReport_mods").toString.split(",").toArray)
From HMRC Online Payments team
}


|
Gday,
my name is Steve.
NEWS
UPDATE: Just arrived back from Australia
(July 19). Photos to be published in some rough
form tomorrow under the photo gallery. Had a great
time parasailing and snorkelling in the Great Barrier
Reef.
|
|
|
Steven Atkinson -- This is Me
|
|
Erin -- This is my Girlfriend
|
This is Namo Web Editor
4.0....just playing with it right now. Of course,
I really want to get into Cocoon,
but time in the day.....
See my SSR 2001 Panel talk at: http://steven.atkinson.net/index.htm.
|


--- layout: page title: Sermons ---
{{post.date | date: "%-m/%-d/%y"}}
{{post.speaker}}
{{post.verse}}


Extra storage space now available in Pokémon Go
"Attention, Trainers!"
by Vikki BlakeNiantic, the team behind augmented reality mobile game Pokémon Go, has revealed its upped the game's storage limits.
In a tweet on the official Twitter account, it was confirmed Pokémon Go has expanded the capacity limits so the game now offers Pokémon storage and item storage limits of 3,000 and 2,500 respectively.
"Attention, Trainers!" the tweet exclaims. "The limit on Pokémon storage has now been expanded to 3000. Need more room? Item capacity upgrades now allow you to store up to 2,500 items!"
The extra space doesn't come free, of course; to unlock the extra room, you'll need to cough up 200 PokéCoins for every additional 50 spaces in either allocation.
ICYMI, Tom reported earlier this week that Pokémon Go is bringing back all of its 2019 Community Day creatures for a recap weekend on 14th and 15th December.
All Community Day exclusive moves previously offered when evolving will once again be available, including all 2018 Community Day moves. So, if you have a Larvitar, Beldum or Bagon sitting ready to evolve - now is the time. Each will get meta-defining attacks when you evolve them up over the weekend.
The Community Day weekend will run from 9am to 9pm on both Saturday 14th and Sunday 15th December. During that time, all 2019 Community Day Pokémon will appear more frequently in the wild: Totodile, Swinub, Treecko, Torchic, Mudkip, Ralts, Slakoth, Trapinch, Bagon, Turtwig, and Chimchar.


On the left, put the tag you want the rule to trigger on. On the right, put the tags you want to be automatically inserted, separated by commas. Putting a # in the tag name is unnecessary but harmless.


Public History: My Experience With Numen
28 Sep 2014 tagged in british museum, museums, personal, public history, vacation, vacationsSo in my public history a few weeks back, we were discussing how we as students have interacted with public history. The professor encouraged us to share our own experiences with museums – something fun, something different, something that made history come alive.
I have a lot of memories that I could share about museums – I mean, I’ve been on plenty of family vacations and adventures of my own where I’ve been surprised or excited or learned something new at a museum. But there is one moment in particular that I remembered as different than the others – and though I didn’t share it in class, I’d like to share it here.
When I was fifteen, I joined a local school’s trip to London, which at the time was my absolute dream vacation. I had always loved Harry Potter and so I saw England and the United Kingdom as this fantastically posh place where all excitement seemed to happen. I read the itinerary nightly in the months leading up to the trip, finding all of the exciting places I would go.
At the time, i wasn’t totally sure that I wanted to go into history – I just knew it was something I liked, something I was interested in. And so, a place like the British Museum seemed really cool on paper – and I was excited to go. But walking into the museum was something else – for lack of better words, it took my breath away. Someone pointed out to me that I didn’t smile the entire time I was in the museum – something I too noticed. I was so overwhelmed by sheer size of the collections, the information, and the building itself – there was so much to take in. I saw all the notable items – the Rosetta Stone, the Elgin Marbles, the Assyrian Bulls – but I felt out of place. I had been to many museums before, but this was different – this was a world in which I had little context and little background that I was unsure what to make of it.
Flash forward two years later, when my family spent our Christmas vacation in London. I was a different person than the girl who had made her way to London as a sophomore – it was my senior year of high school, I’d just been accepted to UMass Amherst (literally just the day before), and I had expanded my knowledge of history to the point where I had actually decided to be a history major. I had been looking forward to returning to the place that had once mystified me.
I don’t think I ever stopped smiling once I entered the museum. It was truly amazing how different the building looked to me – no longer intimidating and filled with a hodgepodge of items, but fascinating and filled with knowledge I could actually comprehend. Time didn’t seem to pass felt like an _aha! _moment – realizing how comfortable and at ease the museum made me.
This is a common desire of people visiting museums, historic houses and sites – numen. It’s a bit difficult to explain exactly what _numen _is, but it’s not far from what I described. A “deep engagement or transcendence” a form of empathy, or an “awe of reverence” allows visitors to experience something very personal when experiencing history. And I’m searching to find that feeling in every museum I visit – greeting this realm of public history like an old friend.


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RUCS, the Review of Undergraduate Computer Science, is the first publication from a top 20 university dedicated solely to undergraduate computer science. We are a non-archival open-access journal that features the best of undergraduate computer science research at the University of Toronto and other top universities. Founded in 2015 by Kawin Ethayarajh, RUCS alumni include graduate students at top schools and prominent tech companies.
We strive to make research more accessible and participatory. Our hope is that RUCS contributes to a positive and supportive environment for future computer science researchers.


Colour Evolution
Each child inherits the colour of the 3 parents above
Evolve
Colour:
Primary
Full Spectrum
Black & White
Evolve
Generations:
60
80
100


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Welcome to Open OnDemand!
You have successfully installed Open OnDemand.
However, you now have to configurure authentication for this apache instance. See
the authentication documentation
for all the options available.
Go to Documentation.


Very well done little curious!! We are so proud of you for reaching this level. Don't stop, keep going!


The entrance to the Brisbane River is along the west coast of Moreton Bay, towards the southern end. The commercial port is obvious near the river mouth; the city of Brisbane lies about 17 miles upstream. The river bar is deep and may be crossed in any weather conditions or tidal state.
Location: 27°28'25"S 153°1'56"E
Nearby coverage includes: Scarborough , Manly and Gold Coast
A useful guide for cruisers to Brisbane can be found on s/v Ceilydh's blog - dated October 2013.
The yacht clearance boarding station is at the Rivergate Marina. This is located just before the first bridge in the Brisbane River. Their website (http://rivergate.com.au/customs-clearance/) has detailed information about clearing customs.
It is 30nm from the NE channel to Rivergate Marina, 6 miles further if you come through the NW channel. Current in the river is strong at Rivergate Marina; you may want to arrive at slack water particularly if short handed.
Yachts must notify Customs a minimum of 96 hours in advance of arrival. This can be done by: sending an email to<EMAIL_ADDRESS>; sending a fax to +61 2 6275 6331; phoning Australian Customs National Communications Centre on telephone number +61 3 9244 8973. Clearance is done by Customs, Immigration and Quarantine. See Australia/Clearance for full details.
Clearance formalities are performed at Rivergate Marina; yachts must proceed directly to the Customs & Quarantine Berth (indicated by yellow signs) and the marina will organise for all the officials to come to your boat.
Note that this marina is located 10 miles from the city centre, just east of the M1 River Bridge (see view of Rivergate marina below). It is remote with very few facilities close-by.
If you arrive on a weekend, you may have to get cleared in by quarantine which charges a weekend or after hours fee (approx. double the normal fee). Alternatively, Customs may just lock the gate and leave you there until Monday morning when Quarantine will clear you in (saving you the after hours fee). This is not guaranteed, however.
The Customs office does not permit anchoring at Mud Island.
Last updated March 2015.
The city of Brisbane provides a unique opportunity for visiting yachts to anchor or moor in the heart of a major urban centre. The Brisbane River is navigable by deep-draft vessels the 12 miles up river to the city. Low bridge clearances there restrict further upstream excursions by masted yachts. Note that the river can run at 3kn at times.
There are anchorages along the eastern shore of the river opposite Eagle Street Pier, just upstream of the Gateway Bridge on the right hand side of the river, or along the western shore south of the pile moorings at the Botanic Gardens. All anchorages and marinas are affected by ferry wakes throughout the day; however commercial traffic ceases overnight.
This is a very popular port and finding a berth can be quite a challenge. It is advisable to plan ahead if possible. Finding available facilties (water, toilets, showers etc.) is also difficult when anchored in the river.
An alternative is to use a marina further from the city, such as those at Manly (to the south) or Scarborough or Bribie Island to the north.
Whilst Rivergate Marina is the official clearance station, many cruising boats move on after clearing in to a marina closer to the city and facilities.
Security Note - In the past there have been dinghy thefts reported by boats at the Garden Point Moorings adjacent to downtown Brisbane. Be sure to secure your dinghy and engine at all times.
Last updated March 2015.


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LIFE EVENTS:
ADULT FICTION
SHORT STORIES: ALFRED HITCHCOCK'S MYSTERY MAGAZINE
SHORT STORIES: MIKE SHAYNE MYSTERY MAGAZINE
JUVENILE AND HISTORICAL FICTION
Something waited for Bent on the other side of the horizon: something with a soundless voice called to him. I thought of that every time I saw him alone on the deck of our schooner, as he watched the sea with brooding, unsatisfied eyes, his face a dark pool of intensity, every splinter of thought reflected there like a dart of light. I don’t know where it might have ended, but it doesn’t matter now; Harvey Wolfe saw to that, Harvey and his wife Lorry.
Learn about his film legacy on his IMDb page.


First, to tell you guys the truth, I had no intention to write this post. You know, because I actually don’t have much experience with Caffe. And I am not some kind of experienced tech-guy who can deal with almost developing environment, either.
Remember I told you about how to prepare your AWS g2.x2large instance for Machine Learning? You can have a look at this post here. I recommended you to use AWS’s instance because of the fact that most of us can’t afford a proper desktop to run Machine Learning stuff. But of course it is always a good idea to set things up similarly on your local machine. Why? Because we can do all the coding on your machine (like configure your network architecture, or test if your codes can be compiled without errors, etc), and just leave the heavy tasks for the GPU instance. It would help you save some money.
With that thought, I decided to install Caffe on my laptop. And guess what? It took me almost a whole working day to finish!  But soon I realize how experienced I became after struggling with it.  But I didn’t regret a little bit, not even a little bit. Because at least I got it done. And I’m here to share my experience with all you guys.
My laptop is running on Ubuntu 16.04, with OpenCV 3.0.0 installed. The other versions of Ubuntu should work as well, because it is the Caffe and the necessary dependencies matter, not the Ubuntu version.
As you may already knew, Caffe is a powerful framework written in C++ for implementing Deep Neural Network and it is being used almost everywhere out there. For that reason, you can just type Caffe installation in Google search bar, and you can find a lot of websites telling you how to do it. But sometimes it may not work to someone, just like my case. So what is the reason then?
First, Caffe does require a lot of necessary dependencies to make it work. And errors occur mostly because of dependencies incompatibility.
As you may be recommended by other sites that you should use Anaconda, one distribution of Python which can self-manage packages installation. I am not saying that Anaconda is bad. In fact I used it a lot in the past, when I had very little experience in Python package installation. It did help me do most of the installing things.
So what is the problem? In my case, having both Python and Anaconda installed caused some kind of a mess, and Caffe struggled with finding the appropriate libraries it needed. Note that Anaconda itself is a completely seperate Python distribution, which means I had two version of Python installed in my machine!
So I decided to remove Anaconda from my disk to try some luck. And guess what? The problem was SOLVED! So the first thing I want you to try is: if you have both Python and Anaconda installed, try to remove Anaconda first.
Note that you will have to change the path according to your Anaconda path. Next, we will install Boost:
In the next step, we will install all the necessary packages for Caffe:
Next, clone Caffe repository, and make a copy of file Makefile.config.example:
Next, we will have to install all the necessary Python packages, using pip. Navigate to python folder, and type the line below:
Note that I got to add sudo to make it work on my laptop. Because what it was supposed to install directly to the real environment.
Next, we have to modify the Makefile.config. Uncomment the line CPU_ONLY := 1, and the line OPENCV_VERSION := 3. I also commented out the lines which indicate using Anaconda just to make sure that Anaconda doesn’t mess up with the installation:
Now you got everything ready. Let’s make it:
It will take a while to finish. But you would probably get some error message like below:
Seems like a mess, huh? It is because hdf5 library and hdf5_hl library actually have a postfix serial in their names, the compiler cannot find them. To fix this, we just have to make a link to the actual files. Remember, we are not changing their names!
But first, let’s check out the actual name of the libraries. It may vary on your machines, though.
You may find the two files like above. Note again that the version may be different. Just take note the ones you saw. Then we will make a link to them:
And note that the postfixes of hdf5 and hdf5_hl are not always the same. In my case, I assumed that they are the same (10.1.0) and it made me pay the price with another error (of course it took me another while to figure out what I did wrong).
After doing that, try make all again, this time there should be no more errors!
Next, we will run two other commands:
And these two should be working as well. And you will likely see the result like below:
If you saw something similar, then Congratulations! You have successfully installed Caffe!
Next step is optional but I highly recommend because we are using Python for our works. We will compile the Python layer so that we can use caffe directly in our Python source code.
Here, most of your machines will compile without error. But someone may see some error like below (I did too).
The error indicates that it can not find a header file named arrayobject.h. It was caused because numpy was installed in a different path, and we must manually point to it. Actually, this problem was solved at the time of writing, but the installation path varies, so not everyone will get through it. For ones who encountered the error above, all you have to do is to make a small change to your Makefile.config from this:
to this:
After that, let’s do make pycaffe again, and it should work now. Next, we will have to add the module directory to our $PYTHONPATH by adding this line to the end of ~/.bashrc file.
Note that you have to change your caffe directory accordingly. We are nearly there, next execute the command below to make things take effect:
At this time, you can import caffe in Python code without any error. Not so hard, right?
But we are not done yet. Caffe provides us some examples of the most well-known models. We will use the LeNet model to train the MNIST dataset. Everything was already set up. All we have to do is just make it work:
Note that you have to change the path to where you put caffe accordingly. Next, we will train the model:
At this point, there should be an error telling you that it was trying to use GPU in CPU-only configuration:
Well, that’s OK. We just have to apply a tiny fix to the file examples/mnist/lenet_solver.prototxt, replace GPU with CPU, and save it. Try to run the command above again, then everything should work just fine!
It will take a while to finish the training (maybe long since we are using CPU). When it completes, you may see something like this:
Your result may vary but we will likely achieve an accurary value of approximately 99%. Congratulations again! Caffe is now working perfectly on your machine!
After today’s post, I hope that you all had Caffe installed successfully on you machines. But if you still had troubles installing Caffe, like some frustrating errors keep coming or something, then feel free to leave me a comment below, and I will try to help you figure out why. See you!