PowerShell: Export Non-Standard and Multi-Value AD Attributes to CSV
I’ve recently been spending a lot of my time at work doing PowerShell scripting for a project that’s currently underway. While working on a bit of code late last week I ran into two interesting problems that I had yet to really stumble across despite doing heavy PowerShell scripting against Active Directory for nearly a decade now.
Exporting Non-standard Attributes To CSV⌗
My first issue was that I needed to export some non-standard attributes from contact objects in AD to a .csv file. When I say “non-standard” I don’t mean that we’ve done a custom schema extension or anything like that. Instead, I simply mean that the AD PowerShell module only wants to include certain attributes when exporting AD objects to a .csv file. For example, if I run Get-ADObject -Properties * against a particular contact object and simply let the output dump to my shell, I see all of the attributes I expect including stuff like givenName and sn. However, if I run the exact same cmdlet but pipe the result to Export-Csv rather than sending it to the shell I will not have all the same attributes; ones like givenName and sn will now be missing. That’s a problem.
Storing Mutli-Value Attributes In a CSV⌗
The other problem was that one of the attributes I needed is proxyAddresses. This is a multi-value attribute as contacts could very likely have multiple proxy addresses associated with a particular mailbox. They may have an alias, x500 addresses, etc. If you use PowerShell to pull this information from AD and dump it to the screen you’ll see the expected proxy address information. If you call GetType() on the proxyAddresses attribute you’ll see it listed as an array. That’s why if you export a contact to a .csv file and include proxyAddresses, the value for each contact in that particular column will simply read:
Microsoft.ActiveDirectory.Management.ADPropertyValueCollection
PowerShell isn’t sure what to do with a multi-value attribute as far as the .csv file goes so it stores the data type. This is also a problem!
The Solution⌗
My solution to this was the following. Note that it’ll be easier to view the Gist for it.
# Get the objects with the required attributes and storing proxyAddresses properly in the .csv file.
Get-ADObject -Filter { objectClass -eq "contact" } -Server myserver.mydomain.net -SearchBase "OU=Contacts,DC=mydomain,DC=net" -SearchScope OneLevel -Properties name,givenName,sn,displayName,telephoneNumber,proxyAddresses,targetAddress,mail,mailNickname,company,department,l,physicalDeliveryOfficeName,postalCode,st,streetAddress,title | Select-Object name,givenName,sn,displayName,telephoneNumber,targetAddress,mail,mailNickname,company,department,l,physicalDeliveryOfficeName,postalCode,st,streetAddress,title,@{name="proxyAddresses"; expression={$_.proxyAddresses -join ";"}} | Export-Csv -Path .\sample.csv -Encoding ASCII -Append -NoClobber -NoTypeInformation
# Shows how to then use the proxyAddresses attribute in the future.
$allContacts = Import-Csv -Path .\sample.csv
foreach($singleContact in $allContacts) {
$proxyAddresses = $singleContact.proxyAddresses.Split(";")
}
The first thing I needed was to get the properties I actually needed as opposed to just the ones PowerShell felt like including due to the object type. The solution was to:
-
Specify all of the attributes I wanted in -Properties to ensure they would be available.
-
Pipe the AD object to Select-Object and then re-specify each of the properties I wanted.
This works because PowerShell is selecting the attributes to include in the .csv file based on the type of object. Select-Object takes whatever comes through the pipeline, though, and makes a brand new, generic object from it. That object will include any properties from that original object that you specify, hence why I tell it the exact listing of properties that I need again.
This leads to the solution to the second problem which is what to do for proxyAddresses. PowerShell allows for the use of an expression to parse together a new property. In this instance the expression is to take the existing proxyAddresses array and -join it into a string. Each of the items in the array are separated by a semicolon. If a contact has the following proxy addresses, for example:
<EMAIL_ADDRESS><EMAIL_ADDRESS>Then the property in the .csv file will be stored as:
SMTP:pretty<EMAIL_ADDRESS>You could pick any character for the delimiter that you want as long as it isn’t used in other data that you’re storing.
In this instance my goal was to take the exported data, re-import it, and then create contacts in a different AD forest. When creating a new object AD is expecting an array for the proxyAddresses attribute. A string with a random delimiter won’t do it. That’s where the second part of the example comes into play. If I’m looping through all of the data stored in the .csv file I can recreate the array of proxy addresses by splitting the string on my delimiter (in this case a semicolon) and assigning the result to a variable. That variable will be an array which can then be used to popular proxyAddresses when running New-ADObject


This article will discuss app state and show one approach to it in Rust, continuing the TicTacToe application example and using the valerie framework. This is the third in a series which starts here and continues from where we left off last time.
The code for this example is here: my fork of valerie/examples/tictactoe. (Actually this commit is a little ahead of this article)
Why you might want to lift state out of components§
Fulcro made this clear to me.
When one object appears at multiple locations in a page, the information needs to be stored at a
top-level component and passed down (as props in React and clones of the State
structs in valerie). This
couples components and their nesting, to thread the state object from where it is stored, to where it is displayed.
When a deep sub-component references a piece of state, this must be known to each wrapping component.
For example, a nested view of order lines needs to make a decision about how to present information about the product it relates to. The order line state may know just the foreign key identifier of the product the line relates to, but the user may be expecting its short code, display name and packaging dimensions. It would be better if the decision about what to display could be delegated to the order line view, without asking order to pass down too much (any?) product information (and then, what if we want to join to stock on hand?).
Returning to our implementation of Tic Tac Toe, if our game was constructed like this:
fn game() -> Node {
div!(
div!(
board(), // NOTE: three boards!
board(),
board(),
).class("game-board"),
div!(
div!(),
ol!()
).class("game-info")
).class("game").into()
}
we would have had three independent games proceeding in parallel.
A different intention would be for each of those boards to reference the same playing state - various views of the same data, remaining synchronised. Various view functions could show different perspectives on the running game. We could answer questions and put that information anywhere on the page, for example: how many turns done? Win possible next turn? How many doubles?
(Later we will explore how to select which intention is rendered.)
If we have our state completely separate from views, how would it look?
Static-scope state we might call "Store"§
In Rust, static-scoped items are accessible from any part of the application without being passed as parameters. What if the rest of state was accessible through a lookup to static stores, using an identifier?
The Store will be a generic dictionary (HashMap) which maps the identifier to a tuple of the target struct, and both sides of the channel we need to link up views to the object, and take action upon events. It will be implemented through a trait:
pub trait Relation<K: Copy + Eq + Hash, V: Clone + Default + Send> {
fn get(id: K) -> V;
fn insert(id: K, value: V);
fn mutate(id: K, m: &impl Mutator<V>);
fn subscribe(id: K) -> StateReceiver<V>;
fn notify(id: K);
}
Implementing Relation<K, V>
for V
means that associated functions of V
can be used to interact
with uniquely identified instances of V - from anywhere in the DOM.
Mutations are a helper type that represent updates/changes to the struct as their own distinct struct. Even though it seems like unnecessary complexity, let this ride for a moment because it will become very useful when we want to pass those mutations to a remote back-end API, over the network.
Mutations just need to know how to apply themselves to their target type, producing a modified instance:
trait Mutator<V> {
fn mutate(&self, v: &V) -> V;
}
An illustrative example of implementing Relation
:
struct PostID(u32);
struct Post {
id: PostID,
body: String,
author: String,
}
impl Relation<PostID, Post> for Post {
// we need this impl to be easy...
}
// usage example:
let post = Post {
id: PostID(34),
body,
author,
};
Post::insert(post.id, post);
let post = Post::get(PostID(34));
The branch in valerie (linked above), provides a macro implementation for such a dictionary (implemented using a HashMap). Let's have a look what that means for the TicTacToe code.
Abstracting the Model§
Firstly, we can abstract the Model. We can use some very simple and explicit structs.
A square is marked either empty, X or O, and starts out empty.
enum SquareMark {
Empty,
X,
O,
}
impl Default for SquareMark {
fn default() -> Self {
Self::Empty
}
}
We also use the mark to track which player is next (okok), so it needs a mutation which sets the starting player and changes between players.
enum NextPlayerChange {
Start,
Next,
}
impl Mutator<SquareMark> for NextPlayerChange {
fn mutate(&self, v: &SquareMark) -> SquareMark {
use SquareMark::*;
match self {
Self::Start => X,
Self::Next => match v {
X => O,
O => X,
Empty => unreachable!(),
},
}
}
}
A square is state, indexable within the board. We set up some defaults so they start Empty, but I've omitted this code.
struct SquareID(u8);
struct Square {
id: SquareID,
pub mark: SquareMark,
}
Squares change when they are clicked, but the change depends on the player, so that is a parameter of the mutator.
enum SquareChange {
Mark(SquareMark),
}
impl Mutator<Arc<Square>> for SquareChange {
fn mutate(&self, v: &Arc<Square>) -> Arc<Square> {
let mut v: Square = Square::clone(v);
match self {
Self::Mark(mark) => v.mark = *mark,
}
Arc::new(v)
}
}
You will notice that we are mutating Arc<Square>
, not Square
. We pass data around a lot through channels,
so our types need to be Clone
.
The board is interesting. Instead of an array of marks, we have an array of identifiers. The Squares themselves are managed by their own relation, so we reference into that. Board no longer knows what constitutes a Square.
The default board sets up references to nine new squares, which in turn, default to Empty. We also factor out our game logic for determining if the board contains any lines of three identical non-Empty marks.
struct Board {
pub squares: [SquareID; 9],
}
impl Default for Board {
fn default() -> Self {
let mut squares = [SquareID(0); 9];
for i in 0usize..9 {
let square = Square::new(SquareID(i as u8));
Square::new(square.id);
squares[i] = square.id;
}
Self { squares }
}
}
impl Board {
pub fn calculate_winner(&self) -> bool {
// ...
}
}
Game status has a very similar implementation to Square, and the mutator is the simplest setter, so not shown here.
Hopefully at this point you agree we have a model for playing a game of tictactoe, which is very much decoupled from the view.
I have not shown the implementations of the trait Relation
yet. The code branch has two macros which implement
the associated functions using a HashMap. All that is required to set up the Stores is:
// Square::get(SquareID) -> Arc<Square>
relation!(Square, SquareID, Arc<Square>);
// GameBoard::get() -> Arc<Board>
singleton!(GameBoard, Arc<Board>);
singleton!(GameStatus, Status);
singleton!(NextPlayer, SquareMark);
singleton!
is very similar to relation!
and sets up reactive state which is not indexed by an identifier.
We can represent our game state! What does it do for our view?
A clean view without model implementation noise§
It's time to get paid. But first, there is one part of the trait Relation
I hid from you. formatted
will take the instance and pass the changed object from the receiver channel to a closure which generates the
Node
text, which is inserted as the update.
fn game() -> Node {
NextPlayer::mutate(NextPlayerChange::Start);
execute(GameBoard::turn_checker());
div!(div!(
div!(
GameStatus::formatted(move |s| {
let s = match s {
Status::Playing => "Next player: ",
Status::Won => "Winner: ",
};
format!("{}", s)
}),
NextPlayer::formatted(move |p| {
format!("{}", p)
})
)
.class("status"),
GameBoard::node()
)
.class("game-board"))
.class("game")
.into()
}
NextPlayer
needed to be mutated because it is a singleton SquareMark
and they default to
Empty, remember?
game()
executes an event-triggered function turn-checker, which we'll return to in a moment.
The game status is used to generate the label text, and the next player is used to display the mark of the next
player. Finally, we insert the board as a node, which is a function we need to write, and we do it by re-opening
the struct. It just loops through the squares in rows of three, and inserts three of the nodes created by
square()
.
Notice that we are only passing the identifier of the square.
impl GameBoard {
pub fn node() -> Node {
let board = Self::get();
let board = &board.squares;
let mut parent = div!();
for row in board.chunks(3) {
let mut row_div: Tag<html::elements::Div> = div!().class("board-row");
for id in row {
row_div = row_div.push(square(*id));
}
parent = parent.push(row_div);
}
parent.into()
}
pub async fn turn_checker() {
let rx = Self::subscribe();
let mut old = StateId::new();
while let Some((new, _)) = rx.receive(old).await {
if GameBoard::get().calculate_winner() {
GameStatus::mutate(StatusChange::Won);
} else {
NextPlayer::mutate(NextPlayerChange::Next);
}
old = new;
}
}
}
The turn-checker grabs a receiver for the GameBoard and waits for events. When an event arrives, it uses the model to check if we have a winner, and either ends the game, or flips the player, using the relevant mutators. The mutators for those stores push those changes down the channels so that the DOM is updated everywhere that is listening on related receivers.
fn square(id: SquareID) -> Node {
button!(Square::formatted(id, |s| {
format!("{}", s.mark)
}))
.class("square")
.on_event("click", (), move |_, _| {
use SquareMark::Empty;
use Status::Playing;
let status = GameStatus::get();
let current = Square::get(id).mark;
if status == Playing && current == Empty {
Square::mutate(id, &SquareChange::Mark(NextPlayer::get()));
GameBoard::notify();
}
})
.into()
}
The square()
function generates the buttons and sets up the event. It has a bit of logic around whether to
accept the click, but if so, then it mutates the square to the current player's mark, and notifies the
GameBoard
. This triggers the turn-checker, which was looping, listening on the GameBoard's receiver.
Satisfy yourself now that if we put:
GameBoard::node(),
GameBoard::node(),
GameBoard::node()
into game()
, we will see three boards that are playing the same game. All three would run turn-checkers
(which would be weird) but they will render the same square state from the static GameBoard singleton and Square
relation.
Do you believe this is neater?§
We have done a lot of work to really separate the model and the view, and the views from each other. This is not quite enough return for what we have invested yet, but we have laid critical groundwork for very powerful back-end integration.
Next article, I'll explore some simple extensions to trait Relation
that will let us fetch objects
from a remote back-end, render them as loading... until they arrive, make local changes speculatively, and
confirm them (or error) when the fetch returns to us with the server's outcome.


|
Path Planning
Andreas Udacity Path Planning
|
Files | |
| file | common.h [code] |
| file | config.cpp [code] |
| file | config.h [code] |
| file | config.hpp [code] |
| file | coordinates.cpp [code] |
| file | coordinates.h [code] |
| file | datalogger.cpp [code] |
| file | datalogger.h [code] |
| file | main.cpp [code] |
| file | mapserivce.cpp [code] |
| file | mapserivce.h [code] |
| file | mapservice.cpp [code] |
| file | mapservice.h [code] |
| file | pathplanner.cpp [code] |
| file | pathplanner.h [code] |
| file | sensor.cpp [code] |
| file | sensor.h [code] |
| file | spline.h [code] |
| file | statemachine.cpp [code] |
| file | statemachine.h [code] |
| file | trajectory.cpp [code] |
| file | trajectory.h [code] |
| file | vehicle.cpp [code] |
| file | vehicle.h [code] |
| file | viz.cpp [code] |
| file | viz.h [code] |


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Marlene Aviles
Data scientist proficient in data extraction, interpretation, reporting, and visualizations. Presently enrolled in a Master of Data Science program to heighten my skills and a highly motivated team player with exceptional interpersonal, verbal, and written skills committed to contributing to the success of this industry..


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CHILDREN OF HEAVEN A film review by Steve Rhodes Copyright 1999 Steve Rhodes RATING (0 TO ****): **
Ali (Mohammad Amir Naji), an Iranian third-grader, is working hard to come in third place in the big race. Battling hundreds of other competitors about his age, he races four kilometers around the lake. As he approaches the finish line, he is in danger of overachieving -- only a third place finish will win the shoes he needs. Ever since he lost his sister's shoes, they have been time-sharing his pair of shoes, so he desperately needs exactly two runners in front of him.
CHILDREN OF HEAVEN (BACHEHA-YE ASEMAN), written and directed by Majid Majidi, is less a movie than a visual pantomime of a short story. The thin narrative and sparse dialog almost dares critics not to like it by imbuing just about every character with near sainthood. When we finally meet the one family we expect to hate, it turns out to be led by a blind beggar with a heart of gold. Add in the amateurish acting, and you would seem to have a recipe for a film that will cause people to smile politely and try think of kind things to say.
The director does fashion a few nice visuals. The movie opens with an intimate close-up of a little girl's shoes being mended. Another lovely little image has kids blowing soap bubbles at each other. Too often, however, he runs out of ideas and just films the same ugly alleyway, again and again.
The story's dirt-poor family hasn't paid their rent in 5 months, and they're overdrawn on their credit with the grocer. The son, Ali, loses his first-grade sister Zahra's (Mir Farrokh Hashemian) shoes on the way back from the shoe repair shop. The plot revolves around the logistics of sharing shoes and of obtaining a replacement pair. Using little dialog, the film sticks to the visuals to tell the bulk of its story. The kids spend large amount of their screen time either racing to swap shoes or waiting for the one with the shoes to return home.
As a change of pace, one day Ali and his father take a beat-up bike and go looking for work as gardeners in Tehran's wealthy enclaves, where the rich live in alabaster mansions behind large gated walls. The movie's best sequence occurs when the father gets inside the gates and views the exterior of one of the elaborate homes. His saucer-sized eyes speak volumes, as he is dumbstruck by the opulence.
Many obvious questions are never answered. Why don't their parents ever realize the shoes are missing? And, why don't the kids wear their sandals, which they both have, rather than continue getting in trouble for being late to school?
The movie does contain one amazing scene. We actually see the kids doing homework! Kids all over America do this everyday -- except in American movies.
CHILDREN OF HEAVEN runs just 1:28. The film is in Persian with English subtitles. It is not rated but would be a G since nothing even remotely offensive occurs. The picture would be fine for all ages, but kids would probably need to be at least 9 to be interested.
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Norwalk IO
Micah Abbott - @rageear
Principal Quality Engineer - Red Hat
+ +
Scaling up == more hardware == more money == wasted resources
+ + +
Scaling up == more VMs == less money == less wasted resources
+ + +
Scalling up == more containers == even less money == even less wasted resources
The battle against OS + configuration skew!
Stone Age == Golden images
Industrial age == VM images + configuration management tooling
Future == containers served from registry, referenced by SHA256
See also: immutable infrastructure
"An immutable host is where the OS is delivered in such a way where OS modification is not expected*"
- me, probably definitely
Typically delivered as image (or image-like artifact)
Allows for hosts to become disposable (i.e. ants vs. elephants)
Provides a foundation for repeatable deployments (i.e. phoenix servers)
RancherOS
Ubuntu Core
OpenSUSE MicroOS
NixOS
VMWare Photon
And probably your favorite that is mising from this list...
Docker containers for EVERYTHING
Upgrades handled via A/B boot entries
Uses cloud-config for initial host configuration
Atomic updates via btrfs snapshots
Read-only root filesystem
Docker + Podman + CRIO container runtimes available
cloud-init for system customization
Fully declarative system configuration
Transactional upgrade model via Nix store
Non-privileged users can install packages
Reproducible from source
Gentoo-based
No package manager (containerize everything)
OS auto-updates
A/B partitioning for updates
Declaratively configure system via Ignition
Built from RPMs
Immutable root filesystem
Updates delivered via ostree/rpm-ostree
Atomic, transactional updates/rollbacks
Fully supports SELinux
Philosophy of Container Linux
Technology of Atomic Host
"An automatically updating, minimal, monolithic, container-focused operating system, designed for clusters but also operable standalone, optimized for Kubernetes but also great without it."
ostree/rpm-ostree - managing OS contents
Ignition - declaratively configure system
podman - build, run, manage containers
zincati - update agent
coreos-assembler - build Fedora CoreOS-style systems
(lib)ostree can be simplified as "git for operating systems"
Files are checksummed + tracked via content-addressed object store
Files are de-duplicated via hardlinks
Can handle bootloader configuration, management of /etc
rpm-ostree is a hybrid image/package system
Uses libostree as the base image format
Accepts RPMs on the server side for composes and on the client side for package layering using libdnf
Primary entrypoint for managing your Fedora CoreOS-style system
Ignition configs: declarative JSON documents provided via user data
Can write files and systemd units, create users and groups, partition disks, create RAID arrays, format filesystems
Runs from the initramfs
Runs exactly once
Fails the boot if provisioning fails
Intended as a drop-in replacement for (most of) docker CLI
Supports OCI image format and Docker image format
Doesn't require a daemon running (#nobigfatdaemons)
Full management of container life cycle
Can run containers as unprivileged user
Can create/manage pods which can be exported to Kubernetes
rpm-ostree is driven by a service, Zincati, that requests permission to update
Updates are rolled out gradually, and can be stopped if regressions are reported
Nodes can request update permission from a cluster service
Useful for ensuring an entire cluster doesn't update simultaneously
Both the developer and production tool
Can run fully unprivileged
Uses rpm-ostree and supermin
Doesn’t use Anaconda to build images
Both share the following:
RPMs from the Fedora ecosystem
Support package installation (although differently)
Can run containers and Flatpaks
Only /var and /etc are writeable on Silverblue
Silverblue uses atomic, transactional updates
Running system is not touched during updates (thank you bubblewrap)
You can pull the plug on a Silverblue (and Fedora CoreOS) host during an upgrade
Tradeoff: reboot to get into upgraded OS
Workstation delivered as traditional RPMs
Silverblue has OS delivered as OSTree commit
Although both can install packages as RPMs
Support for installing (some) packages to /opt; namely Google Chrome
Support for Nvidia drivers (akmods)
Shoutout to Alex Larsson for both of those features!
Enabling automatic OS upgrades by default
Installed Flatpaks out of the box (built + delivered from Fedora infra)
Derive Silverblue config from Fedora CoreOS
Building Silverblue via coreos-assembler
Improving documentation, growing the community
Preview release available now - https://getfedora.org/coreos
Don't run it in production!
First stable release in ~3 months
next and stable streams
Full set of cloud and virtualization platforms
Live PXE and Live CD
Improved network configuration
OKD/Kubernetes integration
Community Discourse - https://discussion.fedoraproject.org/
Fedora CoreOS Issue Tracker - https://github.com/coreos/fedora-coreos-tracker
Fedora Silverblue Issue Tracker - https://github.com/fedora-silverblue/issue-tracker
Fedora Silverblue Twitter - https://twitter.com/teamsilverblue
Twitter - https://twitter.com/rageear
Email - miabbott@redhat.com


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Basic Equations¶
We consider a constant-property slab of atoms, located at a height \(h\) above the visible solar “surface”, in the presence of a deterministic magnetic field of arbitrary strength \(B\), inclination \(\theta_B\) and azimuth \(\chi_B\) (see Fig. 1). The slab’s optical thickness at the wavelength and line of sight under consideration is \(\tau\). We assume that all the atoms inside this slab are illuminated from below by the photospheric solar continuum radiation field, whose center-to-limb variation has been tabulated by Pierce (2000). The ensuing anisotropic radiation pumping produces population imbalances and quantum coherences between pairs of magnetic sublevels, even among those pertaining to the different \(J\)-levels of the adopted atomic model. This atomic level polarization and the Zeeman-induced wavelength shifts between the \(\pi\) (\(\Delta{M}=M_u-M_l=0\)), \(\sigma_{\rm blue}\) (\(\Delta{M}=+1\)) and \(\sigma_{\rm red}\) (\(\Delta{M}=-1\)) transitions produce polarization in the emergent spectral line radiation.
In order to facilitate the understanding of the code, in the following we summarize the basic equations which allow us to calculate the spectral line polarization taking rigorously into account the joint action of atomic level polarization and the Hanle and Zeeman effects. To this end, we have applied the quantum theory of spectral line polarization, which is described in great detail in the monograph by Landi degl’Innocenti & Landolfi (2004). We have also applied several methods of solution of the Stokes-vector transfer equation, some of which can be considered as particular cases of the two general methods explained in §6 of Trujillo Bueno (2003).
The geometry for the scattering event¶
The radiative transfer approach¶
The emergent Stokes vector \(\mathbf{I}(\nu,\mathbf{\Omega})=(I,Q,U,V)^T\) (with \(^T\)=transpose, \(\nu\) the frequency and \(\mathbf{\Omega}\) the unit vector indicating the direction of propagation of the ray) is obtained by solving the radiative transfer equation
where \(s\) is the geometrical distance along the ray under consideration, \(\mathbf{\epsilon}(\nu,\mathbf{\Omega})=({\epsilon}_I,{\epsilon}_Q,{\epsilon }_U,{\epsilon}_V)^T\) is the emission vector and
is the propagation matrix. Alternatively, introducing the optical distance along the ray, \({\rm d}{\tau}=-{\eta_I}{\rm d}s\), one can write the Stokes-vector transfer Eq. ([eq:rad_transfer]) in the following two ways:
The first one, whose formal solution requires the use of the evolution operator introduced by Landi degl’Innocenti & Landi degl’Innocenti (1985), is
\[{{d}\over{d{\tau}}}{\bf I}\,=\,{\bf K}^{*} {\bf I}\,-\,{\bf S}, \label{eq:rad_transfer_peo}\]where \({\bf K}^{*}={\bf K}/{\eta_I}\) and \({\bf S}=\mathbf{\epsilon}/{\eta_I}\). The formal solution of this equation can be seen in eq. (23) of Trujillo Bueno (2003).
The second one, whose formal solution does not require the use of the above-mentioned evolution operator is Rees et al. (1989)
\[{{d}\over{d{\tau}}}{\bf I}\,=\,{\bf I}\,-\,{\bf S}_{\rm eff}, \label{eq:rad_transfer_delo}\]where the effective source-function vector \(\,{\bf S}_{\rm eff}\,=\,{\bf S}\,-\, {\bf K}^{'}{\bf I},\,\,\,\) being \(\,{\bf K}^{'}={\bf K}^{*}-{\bf 1}\) (with \(\bf 1\) the unit matrix). The formal solution of this equation can be seen in eq. (26) of Trujillo Bueno (2003).
Once the coefficients \(\epsilon_I\) and \(\epsilon_X\) (with \(X=Q,U,V\)) of the emission vector and the coefficients \(\eta_I\), \(\eta_X\), and \(\rho_X\) of the \(4\times4\) propagation matrix are known at each point within the medium it is possible to solve formally Eq. ([eq:rad_transfer_peo]) or Eq. ([eq:rad_transfer_delo]) for obtaining the emergent Stokes profiles for any desired line of sight. Our computer program considers the following levels of sophistication for the solution of the radiative transfer equation:
Numerical Solutions. The most general case, where the properties of the slab vary along the ray path, has to be solved numerically. To this end, two efficient and accurate methods of solution of the Stokes-vector transfer equation are those proposed by Trujillo Bueno (2003) (see his eqs. (24) and (27), respectively). The starting points for the development of these two numerical methods were Eq. ([eq:rad_transfer_peo]) and Eq. ([eq:rad_transfer_delo]), respectively. Both methods can be considered as generalizations, to the Stokes-vector transfer case, of the well-known short characteristics method for the solution of the standard (scalar) transfer equation.
Exact analytical solution of the problem of a constant-property slab including the magneto-optical terms of the propagation matrix. For the general case of a constant-property slab of arbitrary optical thickness we actually have the following analytical solution, which can be easily obtained as a particular case of eq. (24) of Trujillo Bueno (2003):
\[{\bf I}={\rm e}^{-{\mathbf{K}^{*}}\tau}\,{\bf I}_{\rm sun}\,+\,\left[{\mathbf{K}^{*}}\right]^{-1}\, \left( \mathbf{1} - {\rm e}^{-{\mathbf{K}^{*}}\tau} \right) \,\mathbf{S}, \label{eq:slab_peo}\]where \(\mathbf{I}_{\rm sun}\) is the Stokes vector that illuminates the slab’s boundary that is most distant from the observer. We point out that the exponential of the propagation matrix \({\mathbf{K}^{*}}\) has an analytical expression similar to eq. (8.23) in Landi degl’Innocenti & Landolfi (2004).
Approximate analytical solution of the problem of a constant-property slab including the magneto-optical terms of the propagation matrix. An approximate analytical solution to the constant-property slab problem can be easily obtained as a particular case of eq. (27) of Trujillo Bueno (2003):
\[\mathbf{I} = \left[ \mathbf{1}+\Psi_0 \mathbf{K}' \right]^{-1} \left[ \left( e^{-\tau} \mathbf{1} - \Psi_M \mathbf{K}' \right) \mathbf{I}_{\rm sun} + (\Psi_M+\Psi_0) \mathbf{S} \right], \label{eq:slab_delo}\]where the coefficients \(\Psi_M\) and \(\Psi_0\) depend only on the optical thickness of the slab at the frequency and line-of-sight under consideration, since their expressions are:
\[\begin{split}\begin{aligned} \Psi_M&=& \frac{1-e^{-\tau}}{\tau} - e^{-\tau},\nonumber \\ \Psi_0 &=&1-\frac{1-e^{-\tau}}{\tau}.\end{aligned}\end{split}\]Note that Eq. ([eq:slab_delo]) for the emergent Stokes vector is the one used by Trujillo Bueno & Asensio Ramos (2007) for investigating the impact of atomic level polarization on the Stokes profiles of the He i 10830 Å multiplet. We point out that, strictly speaking, it can be considered only as the exact analytical solution of the optically-thin constant-property slab problem [3]_. The reason why Eq. ([eq:slab_delo]) is, in general, an approximate expression for calculating the emergent Stokes vector is because its derivation assumes that the Stokes vector within the slab varies linearly with the optical distance. However, it provides a fairly good approximation to the emergent Stokes profiles (at least for all the problems we have investigated in this paper). Moreover, the results of fig. 2 of Trujillo Bueno & Asensio Ramos (2007) remain also virtually the same when using instead the exact Eq. ([eq:slab_peo]), which from a computational viewpoint is significantly less efficient than the approximate Eq. ([eq:slab_delo]).
Exact analytical solution of the problem of a constant-property slab when neglecting the second-order terms of the Stokes-vector transfer equation. Simplified expressions for the emergent Stokes vector can be obtained when \(\epsilon_I{\gg}\epsilon_X\) and \(\eta_I{\gg}(\eta_X,\rho_X)\), which justifies to neglect the second-order terms of Eq. ([eq:rad_transfer]). The resulting approximate formulae for the emergent Stokes parameters are given by eqs. (9) and (10) of Trujillo Bueno & Asensio Ramos (2007), which are identical to those used by Trujillo Bueno et al. (2005) for modeling the Stokes profiles observed in solar chromospheric spicules. We point out that there is a typing error in the sentence that introduces such eqs. (9) and (10) in Trujillo Bueno & Asensio Ramos (2007), since they are obtained only when the above-mentioned second-order terms are neglected in Eq. ([eq:rad_transfer]), although it is true that there are no magneto-optical terms in the resulting equations.
Optically thin limit. Finally, the most simple solution is obtained when taking the optically thin limit (\(\tau{\ll}1\)) in the equations reported in the previous point, which lead to the equations (11) and (12) of Trujillo Bueno & Asensio Ramos (2007). Note that if \(\mathbf{I}_{\rm sun}=0\) (i.e., \(I_0=X_0=0\)), then such optically thin equations imply that \({X/I}\,{\approx}\,{\epsilon_X}/{\epsilon_I}\).
The coefficients of the emission vector and of the propagation matrix depend on the multipolar components, \(\rho^K_Q(J,J^{'})\), of the atomic density matrix. Let us recall now the meaning of these physical quantities and how to calculate them in the presence of an arbitrary magnetic field under given illumination conditions.
The multipolar components of the atomic density matrix¶
We quantify the atomic polarization of the atomic levels using the multipolar components of the atomic density matrix. We assume that the atom can be correctly described under the framework of the \(L\)-\(S\) coupling Condon & Shortley (1935). The different \(J\)-levels are grouped in terms with well defined values of the electronic angular momentum \(L\) and the spin \(S\). We neglect the influence of hyperfine structure and assume that the energy separation between the \(J\)-levels pertaining to each term is very small in comparison with the energy difference between different terms. Therefore, we allow for coherences between different \(J\)-levels pertaining to the same term but not between the \(J\)-levels pertaining to different terms. As a result, we can represent the atom under the formalism of the multi-term atom discussed by Landi degl’Innocenti & Landolfi (2004).
In the absence of magnetic fields the energy eigenvectors can be written using Dirac’s notation as \(|\beta L S J M\rangle\), where \(\beta\) indicates a set of inner quantum numbers specifying the electronic configuration. In general, if a magnetic field of arbitrary strength is present, the vectors \(|\beta L S J M\rangle\) are no longer eigenfunctions of the total Hamiltonian and \(J\) is no longer a good quantum number. In this case, the eigenfunctions of the full Hamiltonian can be written as the following linear combination:
where \(j\) is a pseudo-quantum number which is used for labeling the energy eigenstates belonging to the subspace corresponding to assigned values of the quantum numbers \(\beta\), \(L\), \(S\), and \(M\), and where the coefficients \(C_J^j\) can be chosen to be real.
In the presence of a magnetic field sufficiently weak so that the magnetic energy is much smaller than the energy intervals between the \(J\)-levels, the energy eigenvectors are still of the form \(|\beta L S J M\rangle\) (\(C_J^j(\beta L S, M) \approx \delta_{Jj}\)), and the splitting of the magnetic sublevels pertaining to each \(J\)-level is linear with the magnetic field strength. For stronger magnetic fields, we enter the incomplete Paschen-Back effect regime in which the energy eigenvectors are of the general form given by Eq. ([eq:eigenfunctions_total_hamiltonian]), and the splitting among the various \(M\)-sublevels is no longer linear with the magnetic strength. If the magnetic field strength is further increased we eventually reach the so-called complete Paschen-Back effect regime, where the energy eigenvectors are of the form \(|L S M_L M_S\rangle\) and each \(L\)-\(S\) term splits into a number of components, each of which corresponding to particular values of (\(M_L+2M_S\)).
Within the framework of the multi-term atom model the atomic polarization of the energy levels is described with the aid of the density matrix elements
where \(\rho\) is the atomic density matrix operator. Using the expression of the eigenfunctions of the total Hamiltonian given by Eq. ([eq:eigenfunctions_total_hamiltonian]), the density matrix elements can be rewritten as:
where \(\rho^{\beta L S}(JM,J'M')\) are the density matrix elements on the basis of the eigenvectors \(| \beta L S J M\rangle\).
Following Landi degl’Innocenti & Landolfi (2004), it is helpful to use the spherical statistical tensor representation, which is related to the previous one by the following linear combination:
where the 3-j symbol is defined as indicated by any suitable textbook on Racah algebra.
Statistical equilibrium equations¶
In order to obtain the \({^{\beta LS}\rho^K_Q(J,J')}\) elements we have to solve the statistical equilibrium equations. These equations, written in a reference system in which the quantization axis (\(Z\)) is directed along the magnetic field vector and neglecting the influence of collisions, can be written as Landi degl’Innocenti & Landolfi (2004):
The first term in the right hand side of Eq. ([eq:see]) takes into account the influence of the magnetic field on the atomic level polarization. This term has its simplest expression in the chosen magnetic field reference frame (Landi degl’Innocenti & Landolfi 2004). In any other reference system, a more complicated expression arises. The second, third and fourth terms account, respectively, for coherence transfer due to absorption from lower levels (\(\mathbb{T}_A\)), spontaneous emission from upper levels (\(\mathbb{T}_E\)) and stimulated emission from upper levels (\(\mathbb{T}_S\)). The remaining terms account for the relaxation of coherences due to absorption to upper levels (\(\mathbb{R}_A\)), spontaneous emission to lower levels (\(\mathbb{R}_E\)) and stimulated emission to lower levels (\(\mathbb{R}_S\)), respectively.
The stimulated emission and absorption transfer and relaxation rates depend explicitly on the radiation field properties (see eqs. 7.45 and 7.46 of Landi degl’Innocenti & Landolfi 2004). The symmetry properties of the radiation field are accounted for by the spherical components of the radiation field tensor:
The quantities \(\mathcal{T}^K_Q(i,\mathbf{\Omega})\) are spherical tensors that depend on the reference frame and on the ray direction \(\mathbf{\Omega}\). They are given by
where \(R'\) is the rotation that carries the reference system defined by the line-of-sight \(\mathbf{\Omega}\) and by the polarization unit vectors \(\mathbf{e}_1\) and \(\mathbf{e}_2\) into the reference system of the magnetic field, while \(\mathcal{D}^K_{PQ}(R')\) is the usual rotation matrix Edmonds (1960). Table 5.6 in Landi degl’Innocenti & Landolfi (2004) gives the \(\mathcal{T}^K_Q(i,\mathbf{\Omega})\) values for each Stokes parameter \(S_i\) (with \(S_0=I\), \(S_1=Q\), \(S_2=U\) and \(S_3=V\)).
Emission and absorption coefficients¶
Once the multipolar components \({^{\beta L S}\rho^{K}_{Q}(J,J') }\) are known, the coefficients \(\epsilon_I\) and \(\epsilon_X\) (with \(X=Q,U,V\)) of the emission vector and the coefficients \(\eta_I\), \(\eta_X\), and \(\rho_X\) of the propagation matrix for a given transition between an upper term \((\beta L_u S)\) and an lower term \((\beta L_\ell S)\) can be calculated with the expressions of §7.6.b in Landi degl’Innocenti & Landolfi (2004). These radiative transfer coefficients are proportional to the number density of atoms, \(\mathcal{N}\). Their defining expressions contain also the Voigt profile and the Faraday-Voigt profile (see S5.4 in Landi degl’Innocenti & Landolfi 2004), which involve the following parameters: \(a\) (i.e., the reduced damping constant), \(v_\mathrm{th}\) (i.e., the velocity that characterizes the thermal motions, which broaden the line profiles), and \(v_\mathrm{mac}\) (i.e., the velocity of possible bulk motions in the plasma, which produce a Doppler shift).
It is important to emphasize that the expressions for the emission and absorption coefficients and those of the statistical equilibrium equations are written in the reference system whose quantization axis is parallel to the magnetic field. The following equation indicates how to obtain the density matrix elements in a new reference system:
where \(\mathcal{D}^K_{Q' Q}(R)^*\) is the complex conjugate of the rotation matrix for the rotation \(R\) that carries the old reference system into the new one.
Inversion¶
Our inversion strategy is based on the minimization of a merit function that quantifies how well the Stokes profiles calculated in our atmospheric model reproduce the observed Stokes profiles. To this end, we have chosen the standard \(\chi^2\)–function, defined as:
where \(N_\lambda\) is the number of wavelength points and \(\sigma_i^2(\lambda_j)\) is the variance associated to the \(j\)-th wavelength point of the \(i\)-th Stokes profiles. The minimization algorithm tries to find the value of the parameters of our model that lead to synthetic Stokes profiles \(S_i^\mathrm{syn}\) with the best possible fit to the observations. For our slab model, the number of parameters (number of dimensions of the \(\chi^2\) hypersurface) lies between 5 and 7, the maximum value corresponding to the optically thick case. The magnetic field vector (\(B\), \(\theta_B\) and \(\chi_B\)), the thermal velocity (\(v_\mathrm{th}\)) and the macroscopic velocity (\(v_\mathrm{mac}\)) are always required. This set of parameters is enough for the case of an optically thin slab. In order to account for radiative transfer effects, we need to define the optical depth of the slab along its normal direction and at a suitable reference wavelength (e.g., the central wavelength of the red blended component for the 10830 Å multiplet). In addition, we may additionally need to include the damping parameter (\(a\)) of the Voigt profile if the wings of the observed Stokes profiles cannot be fitted using Gaussian line profiles.
Global Optimization techniques¶
In order to avoid the possibility of getting trapped in a local minimum of the \(\chi^2\) hypersurface, global optimization methods have to be used. We have chosen the DIRECT algorithm Jones et al. (1993), whose name derives from one of its main features: dividing rectangles. The idea is to recursively sample parts of the space of parameters, improving in each iteration the location of the part of the space where the global minimum is potentially located. The decision algorithm is based on the assumption that the function is Lipschitz continuous. The method works very well in practice and can indeed find the minimum in functions that do not fulfill the condition of Lipschitz continuity. The reason is that the DIRECT algorithm does not require the explicit calculation of the Lipschitz constant but it uses all possible values of such a constant to determine if a region of the parameter space should be broken into subregions because of its potential interest.
Since the intensity profile is not very sensitive to the presence of a magnetic field (at least for magnetic field strengths of the order of or smaller than 1000 G), we have decided to estimate the optical thickness of the slab, the thermal and the macroscopic velocity of the plasma and the damping constant by using only the Stokes \(I\) profile, and then to determine the magnetic field vector by using the polarization profiles. The full inversion scheme begins by applying the DIRECT method to obtain a first estimation of the indicated four parameters by using only Stokes \(I\). Afterwards, some LM iterations are carried out to refine the initial values of the model’s parameters obtained in the previous step. Once the LM method has converged, the inferred values of \(v_\mathrm{th}\), \(v_\mathrm{mac}\) (together with \(a\) and \(\Delta \tau\), when these are parameters of the model) are kept fixed in the next steps, in which the DIRECT method is used again for obtaining an initial approximation of the magnetic field vector (\(B\),\(\theta_B\),\(\chi_B\)). According to our experience, the first estimate of the magnetic field vector given by the DIRECT algorithm is typically very close to the final solution. Nevertheless, some iterations of the LM method are performed to refine the value of the magnetic field strength, inclination and azimuth. In any case, although we have found very good results with this procedure, the specific inversion scheme is fully configurable and can be tuned for specific problems.
Our experience has proved that the following strategy is appropriate for inverting prominences. Two initial DIRECT+LM cycles with weights \((1,0,0,0)\) to invert the thermodynamical parameters. Then, two DIRECT+LM cycles in which \(B\), \(\theta_B\) and \(\chi_B\) are left free with weights \((0,0.1,0.1,1)\) which tries to set the correct polarity of the field given by Stokes \(V\). An additional LM cycle in which we fit only \(\theta_B\) and \(\chi_B\) with the weights \((0,1,1,0.3)\) and a last LM cycle with weights \((0,0.3,0.3,1)\) leaving the full magnetic field vector free.
Convergence¶
We let the DIRECT algorithm locate the global minimum in a region whose hypervolume is \(V\). This hypervolume is obtained as the product of the length \(d_i\) of each dimension associated with each of the \(N\) parameters:
When the hypervolume decreases by a factor \(f\) after the DIRECT algorithm has discarded some of the hyperrectangles, its size along each dimension is approximately decreased by a factor \(f^{1/N}\). In order to end up with a small region where the global minimum is located, many subdivisions are necessary, thus requiring many function evaluations.
The most time consuming part of any optimization procedure is the evaluation of the merit function. The DIRECT algorithm needs only a reduced number of evaluations of the merit function to find the region where the global minimum is located. For this reason, we have chosen it as the initialization part of the LM method. Since the initialization point is close to the global minimum, the LM method, thanks to its quadratic behavior, rapidly converges to the minimum.
Stopping criterium¶
We have used two stopping criteria for the DIRECT algorithm. The first one is stopping when the ratio between the hypervolume where the global minimum is located and the original hypervolume is smaller than a given threshold. This method has been chosen when using the DIRECT algorithm as an initialization for the LM method, giving very good results. The other good option, suggested by Jones et al. (1993), is to stop after a fixed number of evaluations of the merit function.


Building style guides with kss-node
This software is a Node.js implementation of Knyle Style Sheets (KSS), "a documentation syntax for CSS" that's intended to have syntax readable by humans and machines. Hence, the kss-node software can be used to create a "living style guide".
- Write human-readable documentation using "KSS syntax" comments. Can be added to CSS, Sass, LESS, or any other CSS Preprocessor files.
- Have
kss-node
auto-generate a style guide from your stylesheets.
Here's an example KSS comment:
/*
Button
Your standard button suitable for clicking.
:hover - Highlights when hovering.
.shiny - Do not press this big, shiny, red button.
Style guide: components.button
*/
.button {
...
}
.button.shiny {
...
}
For more information on how to write KSS comments, see the KSS spec.
kss-node Fireball
This site is generated with the kss-node
command-line tool and parses the KSS documentation found in this Fireball project.
The styling of this site is a Fireball of kss-node's default style guide generator. By using the site navigation to the left (or above), you can see how your documentation would look with the default generator. Note that alternate generators are available.
JavaScript API
If you don't wish to use the default style guide template, you can either:
- write your own template that uses the default kssHandlebarsGenerator style guide generator, or
- write your own style guide generator, or
- use the JavaScript object representation of the style guide, KssStyleguide.
For more information on how to integrate kss-node with your own JavaScript, see the JavaScript API documentation.
Project homepage
Check out the project on Github for more information about the code.


The resort website is meant to show various services offred by a resort company. These include accomodation,leisure,food among others.
The travel agency website is meant to show various travel destinations. These include summer vaccations,tropical vacations ,safari vacations among others.
This project was my very first webpage. The project was basically to show the basic html elements.
The cookie recipe project is just a step by step guide on how to bake cookies. This invloves the basic ingredients as well as instructions.


Disclaimer
The information contained in this website is for general information purposes only. I make no representations or warranties of any kind, express or implied, about the completeness, accuracy, reliability, suitability, or availability with respect to the website or the information, products, services, or related graphics contained on the website for any purpose. Any reliance you place on such information is therefore strictly at your own risk.
In no event will I be liable for any loss or damage including without limitation, indirect or consequential loss or damage, or any loss or damage whatsoever arising from loss of data or profits arising out of or in connection with the use of this website.
Through this website you are able to link to other websites which are not under my control. I have no control over the nature, content and availability of those sites. The inclusion of any links does not necessarily imply a recommendation or endorse the views expressed within them.


Buttons
Examples
Primary
Secondary
Success
Danger
Warning
Info
Light
Dark
Link
Button tags
Link
Button
Outline buttons
Primary
Secondary
Success
Danger
Warning
Info
Light
Dark
Sizes
Large button
Large button
Small button
Small button
Block level button
Block level button
Active state
Primary link
Link
Disabled state
Primary button
Button
Primary link
Link
Button plugin
Toggle states
Single toggle
Checkbox and radio buttons
Checked
Active
Radio
Radio


World's top 10 easy mountains to climb for beginners
by Ben GroundwaterYou won't need any special equipment or skills (other than fitness) to reach these peaks.
MOUNT KOSCIUSZKO, AUSTRALIA
It's a rare thing to be able to scale the tallest peak on a continent with no mountaineering or climbing experience. Enter Mount Kosciuszko, mainland Australia's not-exactly-gargantuan high-point, the sort of mountain that would be classified as a lump were it somewhere like Switzerland. This is a climb for true beginners: a chairlift from Thredbo can get you part way up, which means the gentle wander to the 2228 metre peak can be done in a four-hour round trip.
HALF DOME, US
Here's more of a challenge. Set within climber paradise in Yosemite National Park, Half Dome is an impressive granite peak that tops out at 2694 metres. There's no specialist equipment required to reach that summit; however, you will need a good level of fitness and some hiking experience. This is an almost 27-kilometre round trip with plenty of challenging vertical – though the stunning views of forests, lakes and waterfalls will distract from the effort.
See nps.gov
BEN MACDUI, SCOTLAND
Plenty of hikers come to Scotland keen to "bag a Munro" – that is, climb a mountain more than 3000 feet (914 metres) high – and Ben Macdui is one of the most spectacular. This 1309 metre peak is the second highest in the UK, and it's in the heart of the Cairngorms, a stunningly beautiful area of white-topped peaks and green valleys. It's wild territory where the weather can close in quickly, but still, this 17-kilometre hike is achievable for most.
MOUNT MERU, TANZANIA
Plenty of inexperienced tourists try, and fail, to climb Mount Kilimanjaro, Africa's highest peak. It's a relatively gentle climb, but the almost 6000 metres of elevation tends to halt the plans of the unprepared. An easier climb – and one that's great preparation for Kilimanjaro – is Mount Meru, a 4566 metre peak that's the fifth highest in Africa. Not only is the scenery here lovely, but there's also the chance to spot giraffe and water buffalo.
MOUNT FUJI, JAPAN
Few mountains are as instantly recognisable as Japan's Mount Fuji, so elegant is its volcanic silhouette rising almost 4000 metres above the Tokyo skyline. This is one of the most climbed mountains in the world, with no technical terrain to concern yourself with, so you certainly won't be alone as you rise early in the morning from your hut and attempt to hit the summit for dawn. Incredible.
See jnto.org.au
TOFANA DI ROZES, ITALY
Want to feel like a hardcore climber without the danger? This is the mountain for you. Ascending to the top of Tofana di Rozes in northern Italy takes about five hours, and four of those are spent clinging to iron rungs and ladders above dizzying drops on a via ferrata (iron path). Climbers here are tethered at all times to a thick wire anchored to the mountain; it's safe, but it's still hard work, and mildly terrifying.
See summitpost.org
PIKES PEAK, US
There's good news and bad news at Pikes Peak, a genuine Colorado "fourteener" – that is, a mountain above 14,000 feet, or 4267 metres. First, the bad news: this is a proper hike. The Barr Trail is almost 22-kilometres long and climbs 2250 vertical metres. The good news, however, is that there's no technical terrain to tackle, and Pikes Peak is accessible by road, which means you can have someone pick you up from the summit.
See pikes-peak.com
VILLARRICA, CHILE
Climbing a live volcano sounds purely the domain of the experienced or the insane; however, in central Chile, it's on offer to pretty much everyone. Villarrica is a one of the most active volcanoes in South America, an almost-3000 metre peak that rises above gorgeous Lake District scenery. Though you'll need a guide, as well as crampons and ice-axes, this is a straightforward climb that can be done in a six- to seven-hour round trip.
See chile.travel
MOUNT TOUBKAL, MOROCCO
Summiting the highest mountain in North Africa sounds impressive, and it's true that you'll feel a real sense of achievement at the top of the 4167 metre Mount Toubkal. But that doesn't make this a particularly challenging or intimidating mountain. There's some loose rock to deal with, and reasonable altitude. Mostly, however, the climb is memorable for the Berber villages you pass through, and the spectacular views.
See visitmorocco.com
MOUNT YASUR, VANUATU
Strap yourself in for one of the easiest ascents of your life. Mount Yasur, on Tanna Island in Vanuatu, is a live volcano that's a mere 361 metres high, and has a road that leads to a carpark about a 10-minute walk from the caldera. What's the point then? Just wait for the fireworks show at the top: this is a seriously active volcano, and you'll see jets of lava flying into the air from far below.
See vanuatu.travel


Understand variables in Python.
a variable is a named location in memory
case-sensitive
begin with a letter or underscore(_)
cannot be a Python keyword
message = "spam"
variables can hold any datatype
message = 42
message = 42
print(message * 2)
message = 42
print(message * 2)
#=> 84


Interfaces and implementation of the Context model through which runtime context can be applied by a manager to a component.
Specification of meta-information related to context and context entries is currently under discussion.
Specification of standard attribute entries related to context is currently under discussion.


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--- layout: post title: ! 'HAxxors: Use SQL Server as a NOSql DB' ---
I was in an environment where I only had SQL Server available, but I really wanted a key-value store, so what did I do:
In order to be a proper key-valuestore, one would need to add the ability to do searching etc, but as this was only a quick hack where I did not require the search, I did not implement it.
In case I would have implemented a search, I probably would have used something like Elastic Search.
While this approach is probably not advisable, it helped my to resolve my issue in a very short time. The biggest effort was in getting the upsert command correct. Do not hold me responsible if you use this in a production environment and it blows up on you!!


| Employee ID | Name | Designation | Skills | Years Of Experience | Date of Join | Training | Total No of Days |
|---|---|---|---|---|---|---|---|
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There are many variations of passages of Lorem Ipsum available, but the majority have suffered alteration in some form, by injected humour, or randomised words which don't look even slightly believable. If you are going to use a passage of Lorem Ipsum, you need to be sure there isn't anything embarrassing hidd
on the Internet tend to repeat predefined chunks as necessary, making this the first true generator on the Internet. It uses a dictionary of over 200 Latin words, combined with a handful
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Lorem Ipsum is simply dummy text of the printing and typesetting industry. Lorem Ipsum has been the industry's standard dummy text ever
Lorem Ipsum is simply dummy text of the printing and typesetting industry. Lorem Ipsum has been the industry's standard dummy text ever
Lorem Ipsum is simply dummy text of the printing and typesetting industry. Lorem Ipsum has been the industry's standard dummy text ever
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Lorem Ipsum is simply dummy text of the printing and typesetting industry. Lorem Ipsum has been the industry's standard dummy text ever
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Lorem Ipsum is simply dummy text of the printing and typesetting industry. Lorem Ipsum has been the industry's standard dummy text everLorem Ipsum is simply dummy text of the printing
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Graph of incremental ranking points earned per miles traveled from one tournament to another:
Graph of most frequent routes traveled in consecutive weeks by the top 30 players in 2018:
The analysis employs a multilinear regression to quantify the effect of travel.
There is 1 dependent and 8 independent variables that make up the model:
Dependent variable:
PTW: Ranking points earned this week
Independent variables:
ALW: Age of the player last week
MLW: Number of matches played last week
OLW: Average rank of opponents last week
Tournament category last week (expressed in dummy variables)
TTW: Miles traveled between last week's and this week's tourament
MTW: Number of matches played this week
OTW: Average rank of opponents this week
Tournament category this week (expressed in dummy variables)
Data Source: WTA records for full season 2018 for the year-end top 30 women's tennis players. Full research paper with citations available here.


@* * 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 play.twirl.api.Html @this() @(label:String, data:String, dataScreenReaderText:String = "", hasChangeLink:Boolean = true, changeLink:String="", changeLinkHiddenText:String="", linkId: String="", isNested: Boolean = false )(implicit messages: Messages)


RTTTL to MikroTik RouterOS Script Generator
Preview
Ringtone
RouterOS script
Source code and license information are
here
.


- Introduction
- Tutorials
- Writing a TCP server
- Writing a TCP client
- Setting up the TwistedQuotes application
- Designing a Twisted application
- Tutorial: Twisted From
Scratch
- The Evolution of Finger: building a simple finger service
- The Evolution of Finger: adding features to the finger service
- The Evolution of Finger: cleaning up the finger code
- The Evolution of Finger: moving to a component based architecture
- The Evolution of Finger: pluggable backends
- The Evolution of Finger: a clean web frontend
- The Evolution of Finger: Twisted client support using Perspective Broker
- The Evolution of Finger: using a single factory for multiple protocols
- The Evolution of Finger: a Twisted finger client
- The Evolution of Finger: making a finger library
- The Evolution of Finger: configuration and packaging of the finger service
- Low-Level Networking and Event Loop
- High-Level Twisted
- Utilities
- Twisted RDBMS support
- Perspective Broker
- Appendix


--- title: Returning Tweets on a Schedule in R, using AWS (EC2 + RDS) and Cron author: Mike Page date: '2019-06-30' slug: returning-tweets-on-a-schedule-in-r-using-aws-ec2-rds-and-cron categories: [] tags: [] description: Desc hacker_news_id: '' lobsters_id: '' meta_img: /images/image.jpg ---
In this post, you will learn how to run R scripts on a schedule using Amazon Web Services (AWS). Specifically, you learn how to deploy R on an Amazon Elastic Cloud Computing (EC2) instance, how to write data collected in R to an Amazon Relational Database (RDS), and how to schedule tasks on EC2 using cron.
The R code you will be deploying on the EC2 instance is a script that returns Tweets from the Twitter API and then appends them to a MySQL database hosted on an RDS instance.  Note: as the search terms used to return the Tweets contains offensive material, the script has been tweaked (more details below).
Warning: To follow along with this guide, you will need to register for an AWS account. Fortunately, AWS provides a free tier of access to their services which will suffice for this task. To avoid incurring any costs, ensure you select the ‘free tier eligible’ option when appropriate.
In short, AWS is a cloud computing platform that provides a large array of web services that can stacked together like building blocks. The freedom to arrange these building blocks allows users to build highly customisable, cost effective, and powerful computing platforms in the cloud. Of course, there is a down side to this flexibility: it is accompanied by a large cognitive overhead. Trying to select, deploy, and communicate the correct services is no easy feat for the uninitiated (and I would argue even for the initiated).
The first building block you will deploy is an EC2 instance. An EC2 instance is just a virtual server in which you deploy an Amazon Machine Image (AMI). An AMI is just, as the name suggests, a virtual machine image, of which you have a vast array of options to choose from. Typically you build an AMI from scratch, selecting your desired operating system, technical specification, and so on, as specified in this short AWS tutorial. Once your AMI has been built, you can download any required software (such as R) by connecting to the server remotely via SSH.
Fortunately for any R developers out there, Louis Aslett has pre-built AMI images containing R and RStudio, among other tools, to save users the hassle of building an image themselves (if you would like to build a similar image from scratch, see this tutorial). To get started with one of these pre-built images, click the link to an AMI image in your desired region and follow the AWS instructions to complete the build. Once the build has completed and you have saved your SSH key pair, open a terminal window and check the connection to the server (note in this instance you use ‘ubuntu@’ as the AMI image you have just built uses Ubuntu):
ssh -i {full path of your .pem file} ubuntu@{instance IP address}
Once a successful connection has been made, next check that R functions correctly by opening up a new R session (you use sudo here so that you can download R packages in the next step):
sudo R
Once connected, download the R packages required for the rest of the tutorial that aren’t pre-installed on the AMI:
install.packages("RMySQL")
install.packages("rtweet")
The next building block you will deploy is an RDS instance, a distributed relational database service. Login to the RDS Dashboard on the AWS Management Console and select ‘Create database’. Create a MySQL database, selecting your requirements as necessary. Make sure you note down the username, password, and database name, as these will be required later.
Now comes the crucial part: once created, you need to edit the security settings on your RDS database to allow it to communicate with your EC2 instance. To do this, follow the instructions under the ‘To create a rule in a VPC security group that allows connections from another security group, do the following’ subheading of this AWS guide. Essentially, you want the security group of your RDS database to allow inbound access from the security group of your EC2 instance.
To test if your EC2 instance can communicate with your RDS database, connect to your EC2 instance as was done previously and open up a new R session. Once in the R session run the following code, tweaking the connection details as necessary:
library(DBI)
con <- dbConnect(drv = RMySQL::MySQL(),
username = "insert_username",
password = "insert_password",
host = "example_host.rds.amazonaws.com",
port = 3306,
dbname = "insert_dbname")
Set the username
, password
and dbname
to those your noted down previously. To find the RDS host
, while on your AWS Management Console, click ‘RDS’, then ‘DB Instances’, then the name of your database. In the ‘Connectivity & Security’ panel, you can then find your host
labelled under the ‘Endpoint’ subheading.
If your connection was successful, the above code should be run with no errors thrown. Be sure to disconnect the connection once you are done:
dbDisconnect(con)
At this stage you should have a virtual server with R (EC2) running that can communicate to a MYSQL database (RDS). The next step is to write an R script and set a run schedule for it using cron, the Unix-like job scheduler.
In this instance, you will create an R script that returns Tweets from the Twitter API, matched by search terms, using the rtweet package (you downloaded previously). Before you can use the rtweet package on your EC2 instance, you need to create and store personal authorisation tokens to access the Twitter API. To do this, open up an R session on your EC2 instance and follow along with the rtweet auth vignette, selecting the ‘2. Access token/secret method’ option. Be sure to close the R session once done.
Once you have your access tokens stored, you want to create a script that when runs, opens a connection to the RDS database, appends the new Tweets, and then closes the connection. To create this script, make sure you have an open connection to your EC2 instance, cd
into the desired directory (I recommend just sticking in the home directory) and then create and edit a file using your editor of choice. For example:
nano twitter_script.R
Next copy and paste the following script into the editor, amending the search_terms
and con
settings as necessary (see the search_tweets()
documentation for info on valid search terms):
library(tidyverse)
library(rtweet)
library(DBI)
# list of search terms to pass into search_tweets q argument
search_terms <- c(
"search_term_1",
"search_term_2",
"search_term_3"
)
# create get_tweets func that iterates over search_terms and returns tweets
get_tweets <- function() {
tweets <- tibble()
for(term in search_terms) {
more_tweets <- search_tweets(q = term,
n = 100,
include_rts = FALSE,
retyonratelimit = TRUE)
tweets <- bind_rows(tweets, more_tweets)
}
return(tweets)
}
# call get_tweets
new_tweets <- get_tweets()
# connect to RDS database
con <- dbConnect(drv = RMySQL::MySQL(),
username = "insert_username",
password = "insert_password",
host = "example_host.rds.amazonaws.com",
port = 3306,
dbname = "insert_dbname")
# write to database
dbWriteTable(conn = con,
name = "tweets",
value = new_tweets,
append = TRUE)
# disconncet database
dbDisconnect(con)
The Twitter search API imposes a return rate limit of 18,000 tweets per 15 minute window. To return the maximum number of Tweets per search term while respecting the rate limit in the script above, divide 18,000 by the number of search terms and set this value to the n
argument of the search_tweets()
function. For example, if you want to search across 20 search terms, set n
equal to 900 (18000/20 = 900).
Once finished, save the file and exit the editor. Next, set a cron schedule by opening up crontab, the file which contains the list of cron entries. The -e
tag below just stands for ‘edit’:
crontab -e
Once in the crontab file, set the Twitter script to run every 15 minutes (to respect the rate limit window). Be sure that the you include the full path to the script (the script below just lives in the home directory):
*/15 * * * * Rscript twitter_script.R > temp.log 2>&1 || cat temp.log
You are all done! Now let AWS do the hard work of collecting data for you.
To recap: you set up a virtual machine in the cloud using an AWS EC2 instance loaded with a pre-built machine image (AMI) containing R and RStudio (and more). You then set up a MySQL database on an RDS server, and altered the security group settings to allow inbound access from the EC2 instance. Next you loaded an R script on the EC2 instance and set a run schedule for the script using cron. Now, every 15 minutes, your R script automatically runs and appends new data to your RDS database.


The Rock Cycle The rock cycle is a series of processes that create and transform the types of rocks in Earth’s crust.for more information (nationalgeographic).
There are three kinds of rock: igneous, sedimentary, and metamorphic.
rock Home Science Earth Science, Geologic Time & Fossils Earth Sciences rock geology BY Robert S. Carmichael | See All Contributors | View Edit History TOP QUESTIONS What are the types of geologic rocks? What are igneous rocks? What are sedimentary rocks? What are metamorphic rocks? What is a rock cycle? rock, in geology, naturally occurring and coherent aggregate of one or more minerals. Such aggregates constitute the basic unit of which the solid Earth is composed and typically form recognizable and mappable volumes. Rocks are commonly divided into three major classes according to the processes that resulted in their formation. These classes are (1) igneous rocks, which have solidified from molten material called magma; (2) sedimentary rocks, those consisting of fragments derived from preexisting rocks or of materials precipitated from solutions; and (3) metamorphic rocks, which have been derived from either igneous or sedimentary rocks under conditions that caused changes in mineralogical composition, texture, and internal structure. These three classes, in turn, are subdivided into numerous groups and types on the basis of various factors, the most important of which are chemical, mineralogical, and textural attributes
Igneous are formed from melted rock deep inside the Earth.
Igneous rock, or magmatic rock, is one of the three main rock types, the others being sedimentary and metamorphic. Igneous rock is formed through the cooling and solidification of magma or lava. The magma can be derived from partial melts of existing rocks in either a planet's mantle or crust.
Basalt is a fine-grained, dark-colored extrusive igneous rock composed mainly of plagioclase and pyroxene. The specimen shown is about two inches (five centimeters) across.
Andesite is a fine-grained, extrusive igneous rock composed mainly of plagioclase with other minerals such as hornblende, pyroxene, and biotite. The specimen shown is about two inches (five centimeters) across
Dacite is a fine-grained, extrusive igneous rock that is usually light in color. It has a composition that is intermediate between rhyolite and andesite. The specimen shown is about four inches (ten centimeters) across.
Click Here(Goelogy.Com).
are formed from layers of sand, silt, dead plants, and animal skeletons.
Sedimentary rocks are types of rock that are formed by the accumulation or deposition of mineral or organic particles at Earth's surface, followed by cementation. Sedimentation is the collective name for processes that cause these particles to settle in place.Wikipedia
Limestone and dolostone make up the majority of carbonate rocks. Carbonate Rocks. algal limestone; bafflestone; beachrock; biocalcarenite; biomicrite ...
Muddy sandstones with abundant (>10%) muddy matrix are called wackes. Six sandstone names are possible using the descriptors for grain composition (quartz-, ...
shale. Noun. type of sedimentary rock. stalactite. Noun. rock formed by mineral-rich water dripping from the roof of a cave.
Click Here(Example Of Sedimentary Rocks)
formed from other rocks that are changed by heat and pressure underground.
Metamorphic rocks arise from the transformation of existing rock to new types of rock, in a process called metamorphism. The original rock is subjected to temperatures greater than 150 to 200 °C and, often, elevated pressure of 100 megapascals or more, causing profound physical or chemical changes.Wikipedia
Slate is a fine-grained metamorphic rock that exhibits a foliation called slaty cleavage that is the flat orientation of the small platy crystals of mica ...
Some examples of metamorphic rocks are gneiss, slate, marble, schist, and quartzite. Slate and quartzite tiles are used in building construction.
A picture gallery of metamorphic rocks including amphibolite, gneiss, hornfels, marble, novaculite, phyllite, quartzite, schist, skarn, slate and soapstone.
Click Here(USGS)


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Filename: controllers/main.php
Line Number: 122
Unable to relate sms_inbound with category.


Approve my PR
Approve my PR now
Approve my PR again
Approve my PR again #2
Approve my PR for the final time, #hctbrfst


Workshops
Web Development
Git
Security
IOT.
4th Sept
Stay updated about the events conducted by UPES-MTC
Consisting of Group Discussions, Mock Interviews, Workshops, Bootcamps, CV building session, etc.
C
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Azure Bootcamp
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|
Results for the 2003 Utah State IDPA Match
To view the results, click the following links: 1- Standard results displayed by Division/Classification 2- Results displayed by Division Only (without regard
for Classification) 3- Results displayed by Overall Time (without regard for Division or Classification) 4- Results displayed by Total Points Down (without regard for Division or Classification) Note: All results and notations in the #2, 3 and 4 formats
|


--- layout: post title: Touch Blue a Review date: 2011-04-21 15:39:27.000000000 -07:00 type: post parent_id: '0' published: true pd: '' status: publish categories: - Book Reviews - Classroom Talk tags: - book club - Book Reviews - books for tweens - Cynthia Lord - middle grade books - Touch Blue author: login: k email: k@k display_name: mcary first_name: '' last_name: '' ---
Author: Cynthia Lord Book review written by StorySnoops.com
Touch Blue is a story about an eleven-year old girl named Tess who lives with her family on a tiny island off the coast of Maine. When’s Tess’s best friend moves away, her school no longer has enough students to stay open, and the government threatens to shut it down. To solve this problem, her community comes up with a plan. They increase the number of students on the island by having a few families take in foster children — Tess’s family included. Tess is thrilled that she is going to have a new thirteen-year-old brother, and can hardly wait to meet Aaron. But when Aaron arrives, it is not as easy as she had imagined. He never wants to play with Tess and has a giant attitude problem. The only thing he cares about is his music – and secretly getting back in touch with his “real” mom. Will Aaron ever come to accept Tess, her family, and small town island life as much as Tess wants him to? Or will he leave the island to find his real mom?
Written by an award-winning author, Touch Blue is a short book with a lot of depth, without being boring or hard to read. Tess is a superstitious girl and each chapter opens with a different superstition (Chapter One – ”Touch Blue and your wish will come true”). This book is beautifully written and descriptive, with messages about the meaning of family, and the importance of kindness and community. It’s a great choice for a classroom read aloud or a middle grade book report.
To purchase Touch Blue from Amazon, click here.
Happy reading!
-The StorySnoops
For more reviews and recommendations by StorySnoops, visit the StorySnoops website at http://www.storysnoops.com


Author: Carolina Obando, March 6th, 2021
Point-to-Point antennas are used for links of large distances so it requires two nodes the receiver and the emitter at point 1 the network is received that will be sent to point 2 which will be the one that has the function either of station or simply of bridge since with this station options is to receive one network and convert it to another totally independent but related to point 1, instead the option bridge works to make a simple bridge or link between the point 1 to the network of point 2 making an extension of the main network so it provides the configuration facilities or locks established in the routers programmed in the network 1
It is an asymmetric antenna (60 and 90) contains lateral luboli are very attenuated and very low radiation in the rear lobes, it offers an excellent front-to-back ratio. These antennas are symmetrical (30 and 45º) and are ideal to be installed in sectors with high location requirements.
This horn type antenna is interchangeable and helps us to shape the beam for specific deployments and the needs of the environment.
| 450Mbps | Speed |
| 5GHz (5150–5875MHz) | Frequency |
| 45 Degree 14 dBi | Symmetry |
| improved noise immunity | Yes |
| 1 10/100 / 1000Mbps data port | Ethernet |
| 10/20/30/40/50/60/80 MHz | Adjustable channel widths |
| Atheros MIPS | Processor |
| WPA2 AES | Strong security |
| 24 V, 0.5 A | Food |
| 24V 0.5A Gigabit PoE | Adapter |
| 600 + Mbps | Speed |
| US / CAU-NII-1U-NII-2AU-NII-2CU-NII-35150 - 52505250 - 53505470 - 57255725 - 5850 | Frequency |
| 26 dB | Symmetry |
| improved noise immunity | Yes |
| (1) 10/100/1000 Ethernet Ports | Ethernet |
| 10/20/30/40/50 MHz | Adjustable channel widths |
| Atheros MIPS | Processor |
| WPA2 AES | Strong security |
| 24 V, 0.5 A | Food |
| 24V 0.5A Gigabit PoE | Adapter |
Features
PtMP CPE
1024 QAM
10/20/30/40/50 MHz channel bandwidth
Central configuration management from the AP side
Frequency division
Automatic power adjustments
Router mode support
Works in a PtMP environment with LTU-Rocket as base station
Features
PtMP CPE
1024 QAM
10/20/30/40/50 MHz channel bandwidth
Central configuration management from the AP side
Frequency division
Automatic power adjustments
Router mode support
Works in a PtMP environment with LTU-Rocket as base station
Features
High performance GPON CPE
Supports GPON links up to 20 km
Powerful Layer 2/3 management features
(1) GPON WAN port
(4) RJ45 Gigabit LAN port
Powered via supplied power supply or passive PoE
WiFi 802.11n with internal antennas
These devices allow you to connect two access points. It is understood by Multipoint to the ability to make connections with several nodes of a network.
Our router communicates with two access points. Before setting up the Multipoint router, you have to enable the other two points as a bridge and point-to-point towards the router.
Once finished, the MAC address of the router and the other access points are copied using the address <IP_ADDRESS> in the browser of your choice. Then the LAN IP of the router is changed, the changes are saved, restart and return to enter with the new IP address.
To change the router to a multipoint configuration, within the router's web application look for the Wireless option or similar (it depends on the router model) we locate the Point to multi-Point option, then mark or select in the box Mac addresses, you enter the access point addresses which you want to communicate with the Point to Multipoint configuration.
This image defines 5 types of router
Point to Point: Two routers connected through a link (WAN).
Broadcast Multiaccess: Several routers connected to an Ethernet network
Non-Broadcast Multi-Access (NMBA): Several routers interconnected in a network that does not allow broadcast transmission.
Point to Multipoint: Several routers interconnected in a hub-and-spoke topology through an NBMA network.
Virtual Links: An OSPF network is used to interconnect different areas and backbone.
The parasitic element can be a reflector or director that defines the maximum radiation direction, while the active element is a ½ wave dipole. The simplest Yagi antenna consists of 3 elements. For the VHF and UHF bands, this type of antenna uses 30 There is a reflector and several directors between them.
Due to its simplicity and relatively large bandwidth, Yagi-Uda antennas are widely used in broadcast television applications, amateur radio stations and they have been used in other types of services in recent years, such as point radio links. Some yagis with frequencies above 1.5 GHz require the use of covers to protect against rainwater.
| 268.1x136.5x31.1mm | Dimensions |
| 20W | Max. power consumption |
| 1GHz 4-core 4MIPS64 | Processor |
| 1GB DDR3 RAM | System memory |
| 4GB EMMC, 8MB SPI NOR | Integrated flash storage |
| (1) RJ45 serial port, (10) Ethernet ports (default port 0) (10) 10/100/1000 RJ45 ports Port 0 supports PoE IN; Port 9 supports PoE output (2) 1 Gbps SFP ports | Interface management networks |
| Atheros MIPS | Processor |
| WPA2 AES | Strong security |
| 24 V, 0.5 A | Food |
| 24V 0.5A Gigabit PoE | Adapter |
5 ports powered by 802.3af / at PoE or 5V, 1A USB-C power adapter. The UniFi Switch, model USW-Flex-Mini, is an intelligently managed Gigabit switch. 5 RJ45 Ethernet ports, providing 1 Gigabit links to your devices. Power on the USW-Flex-Mini with the included USB Type-C power adapter or with 802.3af PoE Ethernet on port 1.
Managed by UniFi Network Controller Version: 5.12.5 or higher
Works with UniFi Network Controller
Manage your networks from a single interface
Enjoy intuitive configuration options, as well as robust device monitoring and control.
Update device firmware remotely.
Easily manage network users and guests.
Customize the design, architecture and privacy of guest access points.
Features
for(12) SFP + ports
(4) 10G RJ45 ports
(1) RJ45 serial console port
Non-blocking performance: 160 Gbps
Switching capacity: 320 Gbps
Forwarding rate: 238.10 Mpps
Rack mount with rack mount brackets (included)
DC input option (redundant or independent)
1U all-in-one rack appliance for small and medium businesses
Combines the new UniFi operating system with 8-port switch and security gateway
UniFi Protect video surveillance NVR with 3.5 "HDD support available on the market
8-port Gigabit switch with 1 Gbps RJ45 and 10G SFP + LAN
Enterprise-class IPS / IDS, DPI and Wi-Fi capabilities
Powered by a fast 1.7 GHz quad-core processor
Features
(1) 24V Gigabit passive PoE input port
(3) 24V Gigabit passive PoE output ports
Outdoor weatherproof enclosure
RTL8367N-VB processor
Built-in 4Kbits flash storage
Total non-blocking line rate 4Gbps
TYP. Power consumption 1.5 W
Power method 24V passive PoE input
Network interfaces (4) 10/100/1000 Mbps Ethernet RJ45
PoE interfaces 24V passive PoE input
Maximum PoE + wattage per port per PSE 24V at 1A per port / Total 24V at 1.5A for three ports
IT Student at UTN, Costa Rica


Internal Server Error
if this is from test_variable then this is planned for now.
we still need to implement that better


7
We have seen that a Prolog program is a logicbase of predicates, and so far we have entered clauses for those predicates directly in our programs. Prolog also allows us to manipulate the logicbase directly and provides built-in predicates to perform this function. The main ones are
The ability to manipulate the logicbase is obviously an important feature for Nani Search. With it we can dynamically change the location of the player, as well as the stuff that has been picked up and moved.
We will first develop goto/1, which moves the player from one room to another. It will be developed from the top down, in contrast to look/0 which was developed from the bottom up.
When the player enters the command goto, we first check if they can go to the place and if so move them so they can look around the new place. Starting from this description of goto/1, we can write the main predicate.
goto(Place):- can_go(Place), move(Place), look.
Next we fill in the details. We can go to a room if it connects to where we are.
can_go(Place):- here(X), connect(X, Place).
We can test can_go/1 immediately (assuming we are in the kitchen).
?- can_go(office). yes ?- can_go(hall). no
Now, can_go/1 succeeds and fails as we want it to, but it would be nice if it gave us a message when it failed. By adding a second clause, which is tried if the first one fails, we can cause can_go/1 to write an error message. Since we want can_go/1 to fail in this situation we also need to add a fail to the second clause.
can_go(Place):- here(X), connect(X, Place). can_go(Place):- write('You can''t get there from here.'), nl, fail.
This version of can_go/1 behaves as we want.
?- can_go(hall). You can't get there from here. no
Next we develop move/1, which does the work of dynamically updating the logicbase to reflect the new location of the player. It retracts the old clause for here/1 and replaces it with a new one. This way there will always be only one here/1 clause representing the current place. Because goto/1 calls can_go/1 before move/1, the new here/1 will always be a legal place in the game.
move(Place):- retract(here(X)), asserta(here(Place)).
We can now use goto/1 to explore the game environment. The output it generates is from look/0, which we developed in chapter 5.
?- goto(office). You are in the office You can see: desk computer You can go to: hall kitchen yes ?- goto(hall). You are in the hall You can see: You can go to: dining room office yes ?- goto(kitchen). You can't get there from here. no
We will also need 'asserta' and 'retract' to implement 'take' and 'put' commands in the game.
Here is take/1. For it we will define a new predicate, have/1, which has one clause for each thing the game player has. Initially, have/1 is not defined because the player is not carrying anything.
take(X):- can_take(X), take_object(X).
can_take/1 is analogous to can_go/1.
can_take(Thing) :- here(Place), location(Thing, Place). can_take(Thing) :- write('There is no '), write(Thing), write(' here.'), nl, fail.
take_object/1 is analogous to move/1. It retracts a location/2 clause and asserts a have/1 clause, reflecting the movement of the object from the place to the player.
take_object(X):- retract(location(X,_)), asserta(have(X)), write('taken'), nl.
As we have seen, the variables in a clause are local to that clause. There are no global variables in Prolog, as there are in many other languages. The Prolog logicbase serves that purpose. It allows all clauses to share information on a wider basis, replacing the need for global variables. 'asserts' and 'retracts' are the tools used to manipulate this global data.
As with any programming language, global data can be a powerful concept, easily overused. They should be used with care, since they hide the communication of information between clauses. The same code will behave differently if the global data is changed. This can lead to hard-to-find bugs.
Eliminating global data and the 'assert' and 'retract' capabilities of Prolog is a goal of many logic programmers. It is possible to write Prolog programs without dynamically modifying the logicbase, thus eliminating the problem of global variables. This is done by carrying the information as arguments to the predicates. In the case of an adventure game, the complete state of the game could be represented as predicate arguments, with each command called with the current state and returning a new modified state. This approach will be discussed in more detail in chapter 14.
Although the database-like approach presented here may not be the purest method from a logical standpoint, it does allow for a very natural representation of this game application.
Various Prologs provide varying degrees of richness in the area of logicbase manipulation. The built-in versions are usually unaffected by backtracking. That is, like the other I/O predicates, they perform their function when called and do nothing when entered from the redo port.
Sometimes it is desirable to have a predicate retract its assertions when the redo port is entered. It is easy to write versions of 'assert' and 'retract' that undo their work on backtracking.
backtracking_assert(X):- asserta(X). backtracking_assert(X):- retract(X),fail.
The first time through, the first clause is executed. If a later goal fails, backtracking will cause the second clause to be tried. It will undo the work of the first and fail, thus giving the desired effect.
1- Write put/1 which retracts a have/1 clause and asserts a location/2 clause in the current room.
2- Write inventory/0 which lists the have/1 things.
3- Use goto/1, take/1, put/1, look/0, and inventory/0 to move about and examine the game environment so far.
4- Write the predicates turn_on/1 and turn_off/1 for Nani Search. They will be used to turn the flashlight on or off.
5- Add an open/closed status for each of the doors. Write open and closepredicates that do the obvious. Fix can_go/1 to check whether a door is open and write the appropriate error message if its not.
6- In the order entry application, write a predicate update_inventory/2 that takes an item name and quantity as input. Have it retract the old inventory amount, perform the necessary arithmetic and assert the new inventory amount.
NOTE: retract(inventory(item_id,Q)) binds Q to the old value, thus alleviating the need for a separate goal to get the old value of the inventory.
7- We can now use the various predicates developed for the customer order entry system to write a predicate that prompts the user for order information and generates the order. The predicate can be simply order/0.
order/0 should first prompt the user for the customer name, the item name and the quantity. For example
write('Enter customer name:'),read(C),
It should then use the rules for good_customer and valid_order to verify that this is a valid order. If so, it should assert a new type of record, order/3, which records the order information. It can then update_inventory and check whether its time to reorder.
The customer order entry application has been designed from the bottom up, since that is the way the material has been presented for learning. The order predicate should suggest that Prolog is an excellent tool for top-down development as well.
One could start with the concept that processing an order means reading the date, checking the order, updating inventory, and reordering if necessary. The necessary details of implementing these predicates could be left for later.
8- The expert system currently asks for the same information over and over again. We can use the logicbase to remember the answers to questions so that ask/2 doesn't re-ask something.
When ask/2 gets a yes or no answer to a question about an attribute-value pair, assert a fact in the form
known(Attribute, Value, YesNo).
Add a first clause to ask/2 that checks whether the answer is already known and, if so, succeeds. Add a second clause that checks if the answer is known to be false and, if so, fails.
The third clause makes sure the answer is not already known, and then asks the user as before. To do this, the built-in predicate not/1 is used. It fails if its argument succeeds.
not (known(Attr, Val, Answer))
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The objective of this lesson is to implement some functions in JavaScript and include some tests as well. The tests results are gonna be output in the console. Please check the console to see the results.


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