How Much Water Can You Pour Into a Tesseract?
April 24, 2017
The Red Box.
An artist’s conception of the two boxes now on your kitchen table.
Two empty boxes now sit on your kitchen table. The one on the left is red, the one on the right is blue, but near as you can tell they’re otherwise identical. For the moment let’s focus on the red box. It is a cube, so its edges are identical, and each edge happens to be one meter in length, or about three feet. Now a simple question: How much water could you pour into this red cube?
“Well, a cubic meter of water,” you reply, which is the volume of the cube. And you’re not wrong, of course, but what does that look like? In more everyday units, a cubic meter corresponds to 1,000 liters. That’s two-liter bottles of soda, or if this makes more visceral sense to you, about bottles of wine. That seems a lot.
And because water is so dense, about kg/m³, this means the topped-off red box weighs a metric ton, or lbs. A metric ton! This seems wrong. An 8 oz glass of water weighs hardly anything at all, yet a three foot cube filled with water, which cube fits comfortably on your kitchen table, weighs a ton? It’s true, but why is it surprising? The shock stems from our faulty intuition about how volume scales with size. That 8 oz glass of water seems smaller than the box, sure, but not that much smaller, not so much smaller that it weighs half a pound to the box’s metric ton. But in fact the volume is quite a bit smaller. While the red cube boasts a volume of 1.0 m³, that eight ounce glass of water is an ignominious m³, or times smaller, volume-wise.
If we make the red cube larger, things get predictably worse. Doubling its edge does not double its volume, but rather increases it by a factor of . A two-meter cube filled with water would weigh eight metric tons, or more than lbs, and would require two liter bottles to fill it. This is now starting to be a structural issue for your kitchen table, your kitchen, and possibly your marriageHence we will perform this experiment only in our minds. .
That three in comes about because the red cube resides in three spatial dimensions. The volume of a cube with edge length is given by,
If we increase the size of the cube by a factor of , its volume increases by a factor of , or . That power of three is the explanation for the alarmingly vast difference between the weight of that glass of water and the weight of that red box, and is fundamentally tied to the number of dimensions of the spacetime in which we live.
The Blue Box.
But now to the empty box on the right, the blue one. In all obvious respects it is a one-meter cube like its red compatriot. Except it’s not. This is no blue cube at all, but rather a blue hypercube. Or a tesseract. Or a four-dimensional box. We will use these terms interchangeably, and we will not worry how I came to possess the thing, what strings I pulled, what favors I called in, or how I got it into your kitchen.
Limited as you are to three spatial dimensions, you might well walk past the blue box without realizing it is special. After all you cannot detect, in three dimensions, how this box pokes into the fourth. But it does nevertheless. Its volume is not m³, but rather m⁴. In general, a hypercube with edge length has a volume is given by,
Now as before, we ask the question: how much water can we pour into this thing? How many of those two liter soda bottles, or those ml wine bottles will it take to fill this blue hyperbox? If you turn on your kitchen faucet and start filling bottles, how much municipal water will you store in that one-meter tesseract? What would such a thing weigh?
This is the sort of question that strains the imagination and keeps a certain type of person from a good night’s sleep. We rightly wonder, Does the Question Even Make Sense? Water being a three-dimensional fluid lives in the space defined by the , , and -axes. The tesseract on the other hand is a four-dimensional beast, residing in the hyperspace defined by the , , and and, let’s say, -axes. How do we make sense of this? Let’s attack the problem step-by-step. First, what exactly do we mean by tesseract?
What Is a Tesseract?
A tesseract is the four-dimensional analogue of the three-dimensional cube. It is to a cube what a cube is to a square, what a square is to a line segment, or what a line segment is to a point. The figure below may or may not help you make sense of this.
We begin, simply enough, on the far left, with a single point, an object of zero dimension. We can think of it as a zero-dimensional cube. To create its higher-dimensional counterpart, we drag the point along the blue -axis, creating a line segment, which we can think of as a 1-dimensional cube. In an analogous fashion, we drag the line segment along a perpendicular dimension, the green -axis, to trace a square (a 2-D cube) in the - plane. If we drag that square along the red -axis, we trace a cube (that is, our familiar, everyday 3-D cube) in the -- space. The cube in the third panel is not really a cube, of course, since the screen is only two-dimensional, but rather a projection or shadow of a cube.
But now the hard part, the impossibleIf you have an iPhone, I recommend the excellent app called The Fourth Dimension, which builds intuition on these matters by allowing you to interact with, rotate, and otherwise muck around with hypercubes. leap: to create a hypercube, we must drag our cube along a dimension perpendicular to each of the , , and -axes. We’ll call this the -axis. Human imagination, or at least mine, is limited, which makes the matter of visualizing a 4-D cube a bit maddening. The far-right panel above nevertheless illustrates the hypercube — the object we obtain by dragging the cube along the yellow w-axis. We’re not really seeing four dimensions here of course. Just as with the cube, we are merely seeing its two-dimensional shadow.
An animated projection of a rotating hypercube. It makes sense if you think about it long enough.
Consider the animation to the right. It shows a projection of a hypercube as it rotates through the -dimension. Though unintuitive at first, you may be surprised at the insight you can gain by trying to understand why it is doing that. On the other hand, if you fail, you will be delighted to know that we need not be able to visualize four-dimensional objects in order to reason about them, as we’ll see below.
So much for the hypercubes. What about the water?
Water, Simplified.
Water is a molecule comprising two hydrogen atoms and an oxygen atom, but we’ll not be too concerned with its chemistry beyond a few salient properties. In fact, we won’t worry about the structure of the water molecule at all but, like proper physicists, treat the water molecules as spheres. From here on out, we’ll think of the water molecules as hard spherical masses with a fixed radius, R, as illustrated in the diagram below.
In three dimensions, the position of every water molecule is specified by three coordinates. Molecule , for example, can be found at position . Another molecule, , will collide with the first if the following is true:
That is, the two molecules will collide if the Euclidean Distance between their centers is less than twice their common radius.
Thinking about water in this way is useful because we can readily segue to four dimensions. In that case — inside the tesseract, for example — we must specify four coordinates, not three; i.e., . And now collision between two molecules occurs if,
The difference here being we calculate the distance between molecules using the four-dimensional Euclidean metric, rather than the three-dimensional one.
Now an important side note: aside from this extra coordinate and its geometric implications, we assume that the introduction of a fourth dimension does nothing to substantially alter physics. In fact, adding an extra spatial dimension will certainly muck up our chemistry, perturbing quantum mechanics, changing the nature of water, altering its rotational and vibrational modes, absorption spectra, effective radius, and so forth. We could explore extensions to standard physics such Kaluza-Klein theory, string theory, and M-theory, which posit or demand the existence of additional spatial dimensions, and which might provide insight into how the underlying physics is thereby perturbed. But we shall not be heading down those rabbit holes here. We will focus exclusively on on the geometry of the problem.
Recall that a mole is a unit of measurement corresponding to the number of representative particles in a chemical substance equal to the number of atoms in 12 grams of Carbon-12. That number is known as Avogadro’s constant, which has a value of just over 602 sextillion mol-1; you can regard it as a conversion factor of sorts between the atomic and macroscopic worlds.
In that case, here is all the chemistry we’ll need. The effective radius of a water molecule is about nm. It has a mass of 0.018 kg/mole, which means that a collection of water molecules weighs 0.018 kg. Under everyday conditions, as we’ve already noted, liquid water has a density of kg/m³.
In three dimensions, we find that the volume of a single water molecule — what is typically known as its specific volume — is very tiny:
where we’ve used the usual equation for the volume of a sphere in three dimensions. The red box, that ordinary three-dimensional cube, when filled with water, weighs kg. This means it contains kg/( kg/mole) moles of water, or around individual water molecules.
The total volume occupied by all these molecules (given the specific volume of a water molecule à la Eq. ), is:
And here we find a surprise. We have filled a box with water but find the total volume occupied by the water molecules amounts only to 30% of the total volume! Water, it seems, is 70% empty space.
Why all that space? The reason is that water molecules are not densely packed like oranges at a grocery store. They’re not constantly in contact with one other, but are free to jiggle and collide — and this leaves a lot of empty room between. Chemists define the packing fraction of a substance, , as the total volume of space that is occupied by the constituent particles. The packing fraction of water is therefore . Gaseous water vapor, on the other hand, which is far less dense than liquid water, has a packing fraction on the order of .
One may find slightly different values for the effective radius of water kicking around in the literature. Do not let this ruin your day; a slightly different effective radius implies a slightly different packing fraction in order to obtain the observed density. More important is the order of magnitude of the quantities involved.
We may write down a relation for the total number of molecules that can be stored in a box of given volume in terms of the specific volume of the constituent molecules and the fluid’s packing fraction:
To put this in words: to determine the total number of particles in a box, we simply divide the total effective volume we are filling, which is , by the volume occupied by a single molecule, . Importantly, this relation holds for any number of dimensions, so long as we compute volumes (or lengths, or areas, or hypervolumes) consistently for both box and molecule.
A Brief Digression: Packing Fractions.
Let’s take a quick moment to talk more about sphere packing, the object of which is to find the arrangement of spheres that occupies the largest possible proportion of a space, or to describe how spheres, when left to their own devices and subject to various constraints, manage to arrange themselves.
The illustration below shows two different packings of 2-D spheres in the plane, so: circle packing.
The arrangement on the left, known as a square packing because the circle centers are arranged in a square, has circles occupying 79% of the plane. The packing on the right, known as a hexagonal packing, which is provably optimal, has circles occupying 91% of the plane. In one dimension, the best packing ratio for spheres (which on a line is just line segment packing) is 1. In three dimensions, the best packing fraction drops to 0.74. In dimensions higher than three the sphere packing problem remains unsolved—except, thanks to the exploitation of certain symmetries, in dimensions eight and twenty-four.
The point of this discursiveness is that spheres pack differently in different dimensions, even if they’re not being optimally packed, and if we’re going to pour water molecules into the fourth dimension, we should worry at least a little bit about how they might decide to arrange themselves once there. As a general rule, as we increase the dimension of the space, the packing fraction of spheres decreases precipitously, at least according to computer simulations. In one investigation, the average random packing ratio scales with the dimension, , according to the following empirically determined formula,
For , we find that the packing ratio is . For , it becomes , a 25% decrease. But a caveat: these results were derived for a specific packing scenario known as disordered jammed spheres, which is not exactly the scenario at hand.
Water molecules are not in constant contact, but their mean free path (i.e., the average distance a molecule can travel between collisions) is less than the average intermolecular separation. It would be an interesting exercise to simulate how spheres pack in this scenario, and I leave this as an exercise to the motivated reader, but at this point we take the possibly dubious and certainly hand-wavy step of assuming that the packing fraction of water in four dimensions will be discounted according to the above formula. That is, if the packing fraction of water in three dimensions is 0.3, then in four dimensions it will be about 0.25.
This may not be quite right, but as we’ll see, for all this garment rending, the precise packing fraction will not make too much of a difference. In four or five dimensions, at least, it is on the order of unity.
Let’s Do It: Pouring Water Into the Tesseract.
When we pour our first liter of water into the blue box, what happens? The water molecules, entering the box, find themselves liberated from the confines of three-dimensional space; they acquire a new coordinate, , and can suddenly move in the -direction. Their specific volume, too, changes. They are still spheres defined by a radius of nm, but in four dimensions, volume is no longer given by Eq. . It must be computed as the volume of a four-dimensional hypersphere. That volume is given by,
We’ll call this water’s specific hypervolume. Note that it is many orders of magnitude smaller than its three-dimensional analogue (though understand we’re not comparing apples to apples here, but to ).
We are finally in a position to calculate the total number of water molecules we can fit into your tesseract. Using Eqs. and and with we find,
All of Lake Zurich could be poured into that four-dimensional hypercube on your kitchen table.
That is something like moles of water, which would weigh about billion metric tons, and, in three dimensions, occupy a cubic mile. For comparison, that is roughly the size of Lake Zurich, in Switzerland. A cubic mile of water! Sitting on your kitchen table! Recall that it took 500 two liter soda bottles to fill our red 3-D cube; it would take over two billion such bottles to fill our blue tesseract. It seems there is a lot of extra space in four dimensions.
Now that we know how to calculate these things, we can run wild. Suppose that instead of the one meter hypercube, we had a more reasonably sized, one inch, pocket-sized hypercube? How much water can we fit in one of those? Running the same calculations above with a hypervolume of yields an effective volume of . This is nearly the volume of an Olympic-sized swimming pool. And you could carry it around in your pocket, except that it would weigh metric tons.
Quite expectedly, hypervolumes grow even faster than 3-D volumes as length scale increases. If we had a four-dimensional Olympic swimming poolThat is, an ordinary three-dimensional Olympic swimming pool that happens to extend into the fourth dimension a distance equal to the (3-D) length of the pool. , for example, we could accommodate the entire Black Sea. Such is the power of powers of four.
And since we’re bending the rules of our Universe anyway, why not consider even higher dimensional containers—a five-dimensional box, perhaps? We should expect even more dramatic storage capacities. If I were to loan you my green, five-dimensional hypercube, how much water could you fit in that? I’ll leave it to the reader to calculate the details, but it would exceed , enough to accommodate all the water on Earth, and then some.
A five-dimensional hypercube with one meter edges could easily contain all the water in all the oceans on Earth.
On your now very distressed kitchen table.


Imagine flipping a switch on a set of train tracks. A mungebit
behaves like this: once the trained
switch is flipped,
it can only run the predict_function
, otherwise it will
run the train_function
.
The train function is responsible for performing a munging step and storing metadata that can replicate the munging step in a live production environment without the full reference data set.
The predict function is responsible for performing a munging step using metadata it computed during an earlier training step. This is usually done in a live production environment setting.
The majority of data projects are overcome by the burden of excessive data wrangling. Part of the problem lies in the fact that when new data is introduced that was drawn from the same source as the original, such as a training set for a statistical model, different code needs to be written to achieve the same transformations. Mungebits solve this problem by forcing the user to determine how to correctly munge on out-of-sample data (such as live streaming data in the form of one-row data.frames) at "munge-time", when the reason for the wrangling is still apparent. A frequent source of data errors is treating this process as an afterthought.
mungebit_run(data, ...) mungebit_train(data, ..., `_envir` = parent.frame()) mungebit_predict(data, ..., `_envir` = parent.frame()) mungebit
| data | environment or data.frame. Essentially an environment
containing a |
|---|---|
| ... | additional arguments to the mungebit's |
| _envir | environment. Internal argument used for determining
the execution context of the invoked |
The modified data
, whether it is an environment
or data.frame
.
The modified data
, whether it is an environment
or data.frame
. Side effects on the input
local variable
provided to the train_function
will be recorded on the mungebit
object.
The modified data
, whether it is an environment
or data.frame
. Side effects on the input
local variable
provided to the predict_function
will be recorded on the mungebit
object.
The purpose of the train function is to
Perform some munging on the data set, such as renaming columns, creating derived features, performing principal component analysis, replacing some values, removing outliers, etc.
Storing the metadata necessary to replicate the munging operation
after the original training set is no longer available. For example,
if we are imputing a variable, we would need to remember its mean
so we can use it later to replace NA
values.
The purpose of the predict function is to
Perform some munging on the data set, such as renaming columns, creating derived features, performing principal component analysis, replacing some values, removing outliers, etc.
Use the metadata computed during the train
step
to correctly perform this munging.
Consider the following problem. Imagine we wish to discretize a variable, say determined algorithmically with cuts [0, 0.5), [0.5, 1.5), [1.5, 3). When we apply the same transformation on a new data set, we cannot run the same discretization code, since it may produce new cutoffs, and hence invalidate the results if, for example, we had trained a model on the prior cutoffs. To ensure the exact same mathematical transformation is performed on new data--whether a new test set derived from recent data or a one-row data.frame representing a single record streaming through a production system--we must run different code on the "original" set versus the new set.
Mathematically speaking, a transformation of a data set can be represented by a single mathematical function that is implemented differently during "training" versus "prediction." Here, "training" refers to the first time the transformation is performed, and "prediction" refers to subsequent times, such as on newly obtained data or a one-row data.frame representing a single new record in a production system.
Therefore, the correct approach to data preparation, if you
wish to re-use it in the future on new data sets or in a live production
environment, is to treat it as a collection of tuples
(train_function, predict_function, input)
, where
train_function
represents the original code, input
represents
an arbitrary R object such as a list, used for storing "metadata"
necessary to re-create the original transformation, and the
predict_function
takes this input
metadata and produces
the identical transformation on an out-of-sample data set.
For example, if we wish to impute a data set, train_function
might compute the mean, store it in input$mean
, replace
the NA
values with the mean, and return the dataset. Meanwhile,
the predict_function
simply replaces the NA
values
with the cached input$mean
.
Usually, these steps would be in disjoint code bases: the modeler
would perform the ad-hoc munging while playing with the dataset,
and a software engineer would take the computed input$mean
and hard code it into a "data pipeline". It would be infeasible
to recompute the mean on-the-fly since it depends on the
original data set, which may be prohibitively large. However,
while it may require a lot of space and time to compute the
original input
, as they are parameterized potentially by
a very large data set, usually the input
itself is small
and the resulting predict_function
is inexpensive.
The fundamental problem of data preparation, and the reason why data scientists spend over 90% of their time on data preparation, is a lack of respect for this dichotomy. Using mungebits makes this duality blatantly apparent in all circumstances and will hopefully reduce the amount of time wasted on cumbersome wrangling.
not_run({ mb <- mungebit(column_transformation(function(col, scale = NULL) { if (!isTRUE(trained)) { # trained is an injected keyword cat("Column scaled by ", input$scale, "\n") } else { input$scale <- scale } col * input$scale })) iris2 <- mb$run(iris, "Sepal.Length", 2) # iris2 now contains a copy of iris with Sepal.Length doubled. iris3 <- mb$run(iris2, "Sepal.Length") # > Column scaled by 2 head(iris3[[1]] / iris[[1]]) # > [1] 4 4 4 4 4 4 })


Artistic Photo displays - Our Packaging, Brand, and How We Got Here
From Dorm Room Idea to World Maker Faire
Our Story
Learning to stage great photos while making wonderful memories
Fritz Bacon
UConn Phi Rho
Cailyn Criniti
... and so many more
Reach out to us for layouts, pricing, and more.
Contact Us


This paper, from Google Research (now Google AI, I guess), is well-written and clear, so I’ll just confine my notes to giving the context for the problem and what is unique and interesting about the paper’s solution.
This work fits into the category of using deep learning to enhance speech, with possible future applications to hearing assistance. People are generally pretty good at focusing on a single voice in a crowded room where there is background noise and many people talking at once. However, for people with hearing loss this ability rapidly diminishes, so there has long been interest in developing technology to compensate.
The challenge was dubbed “the cocktail-party problem” in 1953 and despite many attempts to solve it since then, success has been limited. Audio enhancements such as amplification and frequency adjustments aren’t effective, and computer algorithms struggle with it.
Some promising results have been achieved in the modern era of deep learning, beginning a couple of years ago with a technique called Deep Clustering[3]. Mixtures of voices could be separated into separate audio streams, one for each voice. Follow-on work provided several improvements, but still had several limitations:
the algorithms operate on clean speech samples that are well recorded with close-up mics
in other words, there is basically no background noise
you sort of have to know how many speakers are in the mixture
the quality of the separated speech is not spectacular
there’s no inherent way to indicate which speaker you want to listen to
This is far from the real-world problem we’d like to solve. Despite impressive progress, it is beginning to feel like some new ingredients are needed. Maybe hardware, maybe a language model that can infer from context like humans do, or maybe a new data source, like video. The video idea seems to have been in the air: three groups working on it independently published papers within a few days of each other [2][1][4].
Looking to Listen
This paper takes a new approach to combining video and audio to advance the state of the art on the various subproblems of the cocktail-party problem:
separating speech from simultaneous talkers (source separation)
suppressing background noise (speech enhancement)
designating which speaker you want to focus on (attention)
The algorithm is not doing lip reading, at least not explicitly. (Other groups are working on this though.) The authors just feed both audio and video data into a network and let it figure out what it needs to do.
It makes sense that video should help. I saw an estimate once that 30% of speech intelligibility comes from visual information. A convincing demonstration of this is the McGurk effect.
Training Data: AVSpeech
Where do you get training data for such a network? This is one of the major contributions of the paper: scraping YouTube and other online sources, filtering it down to usable samples, and extracting features. The result is a data set called AVSpeech that Google promises to release to other researchers.
Although the authors have some nice demos on real-world data, the training data is synthesized from separate, clean sources which also serve as ground truth. The sources are mixed together and noise is added to create a training sample. This solves the problem of acquiring enough labeled training data.
The video features are interesting. They first pick out all faces in a frame, then use face recognition to pick out one face, and create an embedding based on that face data.
The audio features are standard for speech processing work: a spectrogram, which is the collection of time-frequency (T-F) bins for the audio after segmenting into overlapping time frames and doing a Fourier transform in each frame. A spectrogram by its nature consists of complex numbers. Most algorithms take the magnitude and discard the phase. In this paper however, they kept the full complex values to get the best results.
The output of the network is a mask, which is a set of numbers, one for each T-F bin in the spectrogram, that are applied to the spectrogram by multiplying pointwise. The resulting spectrogram is inverted to produce an an audio (time-domain) signal.
The Network
The network is basically an RNN with some bidirectional LSTM (BLSTM) and fully connected layers. The loss function is the squared error between the clean and masked spectrograms.
They trained a separate network for each possible number of speakers. This seems like an unfortunate limitation, but they allude to not needing the number of speakers.
It is trained for 5 million (!) epochs, using Adam with a learning rate schedule.
The results are exciting (to me, anyway). Especially impressive are the applications to real-world situations, something not often seen in papers like these. The processing is not real-time, but presumably can get better with further work.
I found it unsurprising, but sad, that they had to code up their own benchmark algorithms <rant>because this area of machine learning is not as open and sharing as it should be</rant>. They beat the benchmark substantially for speech separation tasks.
They didn’t see a lot of improvement on the straight speech enhancement task. This is surprising to me, but they explain it by saying that the frequency content of noise is sufficiently different from speech that video doesn’t add that much new information. I’m not convinced—it depends on the noise, which after all could be a babble of voices.
The speech separation is quite effective on same-gender mixtures, which is noteworthy. Such data is generally quite challenging. The “double Brady” video is particularly interesting because not only is it an M-M mixture, it’s the same male voice that is being separated from itself!
The authors seem a little disappointed in the audio quality. I’m not. The outputs are fairly intelligible (by people with normal hearing).  It’s a good start.
Finally, it is worth noting, as the authors emphasize, that including video in the mix suggests a natural user interface for indicating what speaker you want to attend to: point.
References
[1] Triantafyllos Afouras, Joon Son Chung, Andrew Zisserman: “The Conversation: Deep Audio-Visual Speech Enhancement”, arXiv preprint arXiv:1804.04121, 2018.
[2] Ariel Ephrat, Inbar Mosseri, Oran Lang, Tali Dekel, Kevin Wilson, Avinatan Hassidim, William T Freeman, Michael Rubinstein: “Looking to Listen at the Cocktail Party: A Speaker-Independent Audio-Visual Model for Speech Separation”, arXiv preprint arXiv:1804.03619, 2018.
[3] John R Hershey, Zhuo Chen, Jonathan Le Roux, Shinji Watanabe: “Deep clustering: Discriminative embeddings for segmentation and separation”, Acoustics, Speech and Signal Processing (ICASSP), 2016 IEEE International Conference on, pp. 31—35, 2016.
[4] Andrew Owens, Alexei A Efros: “Audio-Visual Scene Analysis with Self-Supervised Multisensory Features”, arXiv preprint arXiv:1804.03641, 2018.


Progress in this course(100%)
Progress in the specialization capstone(20%)
Progress in life goals(67%)
I grew up in Ashtabula Ohio.I lived near Lake Erie and I really miss the sunsets over the water.
This Page was created by your name & Collen van Lent. To learn more about
web design,visit Intro to WEb Design.


{% extends 'register/base.html' %} {% load i18n %} {% block title %} {% trans "Contact Us" %} {% endblock %} {% block content %}
Phone: 1-833-694-1709
Teletypewriter (TTY): 1-866-694-8389
Hours of operation are Monday to Friday from 8:30 am to 5 pm Eastern Time
{% trans "We usually reply within 24 hours, except for weekends and holidays." %}
{% trans "What do you want to do?" %}
{% include "includes/cds_form.html" with submit_text=_("Send") %} {% endblock %}


{{set . "title" "Telepresence Robot"}} {{template "header.html" .}}
Enter commands one per line. Each command consists of three parameters separated by a space. The first parameter is the 3 digit signed left motor speed ranging from -255 to +255. The second parameter is the 3 digit signed right motor speed ranging from -255 to +255. The last parameter is the duration of the command in milliseconds.


--- layout: minimal title: Request for Proposals ---
Level Up is searching for candidates who have experience with creating and shipping modern software products within our four themes; ideate, design, build, and launch.


Puck.js Sensor Logger
Turn your Puck.js into a simple passive tracker. Collect the current temperature, light level and accelerometer data every 5 minutes.
Once installed the Puck.js will collect sensor data every 5 minutes.
The collected data includes the temperature, light level and accelerometer data every 5 minutes.
No apps needed: Press the install button above, select your Puck.js and you're good to go. And downloading the data is just as easy.
Web Bluetooth currently only works in Chrome & Opera browsers. With them you can install the Sensor Logger app on your Puck.js and download the data right from this website. But no information is ever transmitted to the web. Whatever you track, it's between your Puck.js and your browser.
Everything is open source for you to tweak: The Puck.js with all of its hardware, firmware & software and this website is as well.
You can get involved! All the code etc. for the Puck.js are on GitHub. And so is the code for this website & the Puck Logger.


How to upgrade BeoLiving Intelligence to PRO?
BeoLiving Intelligence could be upgraded through its web interface pressing in “BASIC” at upper-left top bar and clicking at “Click to upgrade” link in License type.
How do I get my BeoLiving Intelligence IP address?
The following methods to discover BeoLiving Intelligence IP are suggestions (this doesn’t mean that they are the only ones):
- Use a network scanner/IP-scanner, e.g. the free-ware: Fing. The best result is obtained using a hand held device; remember to access the Wi-Fi network used by the BeoLiving Intelligence.
- Using a computer on the same network as the BeoLiving Intelligence and an application that supports Bonjour discovery (e.g. the Safari browser , avahi-browse), lookup for “_hipservices._tcp.” service and the application will discover the IP addresses of the BeoLiving Intelligence in the network.
- Access to your LAN router and search for the assigned IP to BeoLiving Intelligence.
How to link Alexa with your BeoLiving Intelligence?
Refer to our specific guide: BeoLiving Intelligence link to 3rd party Cloud Service guide.
How to link IFTTT with your BeoLiving Intelligence?
Refer to our specific guide: BeoLiving Intelligence link to 3rd party Cloud Service guide.
How can I control my devices with Alexa? What to say?
Refer to our specific guide: BeoLiving Intelligence Alexa skill guide.
Alexa does not understands when trying to control an specific device
Sometimes, devices name are not suitable for Alexa to understand. Some workarounds to fix this issue are described at BeoLiving Intelligence Alexa skill guide.
Can’t link IFTTT or Alexa with BeoLiving Intelligence
Make sure you first enabled Remote Access of your BeoLiving Intelligence through BeoLiving App. Refer to BeoLiving Intelligence Quick Setup guide for a detailed description.
How do I report an issue with my BeoLiving Intelligence?
Refer to our specific guide: BeoLiving Intelligence Troubleshooting guide. You will find instructions about how to proceed in case of error reporting.
My BeoLiving Intelligence is not responding, what should I do?
Refer to our specific guide: BeoLiving Intelligence Troubleshooting guide. You will find instructions to follow in case your BeoLiving Intelligence isn’t responding or isn’t returning to a normal operation mode.
Can not establish connection with a certain HA system, what should I do?
Check that BeoLiving Intelligence and the HA system are connected to the same LAN network. Check connectivity for each system (e.g.: ping BeoLiving Intelligence and HA system).
At Systems section of BeoLiving Intelligence web interface, check that Connection settings of the HA system are correctly configured.
Try to provoke a system reset of the HA system and check if connection can be established.
If connection can not be restored, follow the instructions at BeoLiving Intelligence Troubleshooting Guide of how to create and send a Service report of your BeoLiving Intelligence.
How can I find a specific source of an A/V device in BLApp?
Sources showed in BLApp are managed in the Interface section of BeoLiving Intelligence web interface. Selecting the device owner of the specific source, check that the source has not the checkbox “Hidden” selected. For more information regarding configuration of user interfaces check Interfaces section of BeoLiving Intelligence PRO User Guide.
What does the BeoLiving Intelligence_ Led color/patter means?
BeoLiving Intelligence Led color displays the actual state of your BeoLiving Intelligence. The combination between color and pattern represent an specific BeoLiving Intelligence state:
| Activity | LED state |
|---|---|
| Normal operation | Constant Green |
| Critical error | Flash Red / Yellow |
| Firmware update | Quick flash Green |
| Loading configuration | Quick flash Green |
| Waiting for User confirmation | Quick flash Green / Yellow |
| User confirmation acknowledge | Constant Yellow |
| Boot | Transition Red / Yellow |
What are the upgrades in the BeoLiving Intelligence PRO?
BeoLiving Intelligence has most of his capabilities reduced. Upgrading your BeoLiving Intelligence to BeoLiving Intelligence PRO, will let you experience all your BeoLiving Intelligence can offer, as the next table shows:
| Functionalities | BeoLiving Intelligence | BeoLiving Intelligence PRO |
|---|---|---|
| Control B&O NetworkLink products | + | + |
| Remote access | + | + |
| Alexa, IFTTT integration | + | + |
| Configuration with BeoLiving App (Limited compared with configuration through web interface) | + | + |
| Control over BeoLiving App | + | + |
| Configuration with web interface | + | |
| Control over WebPanel (Browser) and TV’s Home Control | + | |
| Integration with Home Automation systems | + | |
| Customization of BeoLiving App intallation control | + |
Can I controll my devices outside my house?
Remote access is available in all firmware versions of BeoLiving Intelligence. You can activate it by going to your BeoLiving Intelligence settings in the BLApp.
How can I control my BeoLiving Intelligence?
BeoLiving Intelligence has multiple ways of user interfaces for control your building. From factory, BeoLiving Intelligence could be controlled only by BeoLiving App and Voice (linking your BeoLiving Intelligence with Alexa). After upgrading your BeoLiving Intelligence to BeoLiving Intelligence PRO, control through BeoLiving Intelligence web interface and Home Control native application of Bang & Olufsen TV’s becomes available.
If the power goes off, do I lost BeoLiving Intelligence configuration?
BeoLiving Intelligence’s configuration is persistent, so all configuration and programmation will be safe if any power-off occurs.
What kind of devices can I control?
BeoLiving Intelligence supports any Bang & Olfusen NetworkLink TV or speaker device. However if you upgrade it to BeoLiving Intelligence PRO it could support any of the following resources (if the driver for that Home Automation system is available and it supports the product):
- DIMMER: Any Light/Dimmer.
- SHADE: Any Curtain/Shade/Blinds.
- THERMOSTAT: Thermostat of 1 or 2 set points.
- BUTTON: Wall buttons or keypads.
- GPIO: General purpose input output.
- AV RENDER: Any Bang & Olfusen NetworkLink TV or speaker device.
- ALARM: Alarm system.
All of these resources are called “Standard resources” and most of them (less the GPIO’s) have a graphic representation in each user interface. On the other hand, BeoLiving Intelligence also supports “Custom resources” that are system dependent and can not be represented as a standard resource. Those don’t have a graphic respresentation in user interfaces but could be controlled through Scenes programming.
How can I know which Home Automation systems can be integrated?
As this market never stops growing, we don’t stop integrating new Home Automation systems and cloud services. The list of all supported systems are showed at System Drivers Guide page. For being updated with the latest news of new supported systems and functionalities don’t miss our Newsletter.
Are the firmware updates necessary?
BeoLiving Intelligence comes by default with automatic firmware updates enabled, you can choose to turn-off that option and check for firmware updates manually. Firmware updates are highly recommended in order to avoid malfunction or abnormal operation.


{% extends "base.html" %} {% block title %}Not Found{% endblock %} {% block content %}
OK, so this page doesn't exist. Go back and try a different link or navigate around the website again.


[gecode-users] Shuffling around files
Guido Tack
tack at ps.uni-sb.de
Tue Apr 11 16:08:10 CEST 2006
Hi everyone.
After the release, we thought it was time to shuffle some files
around in the trunk. We have changed the way our library is organized
in the source tree. Everything belonging to the library proper is now
in a directory trunk/gecode. This means that now you can, in a client
program, just include "gecode/kernel.hh", and the gecode directory
doesn't have to be on the include path.
This makes the overall structure more regular, and accessing header
files like int.hh has less risk of clashes.
Cheers,
Guido
More information about the gecode-users
mailing list


Around the Globe
By:Hiame
About
Around the World
Destinations by Continents
Morocco
Kenya
India
Japan
Thailand
Dubai
Tanzania
World
Image:Globe
http://maps.bpl.org [
CC BY 2.0
],
via Wikimedia Commons


×
"MOST WANTED"
# MAKETHEDIFERENCE
Casti presents "Café por favor"
Innovating with our "healthy fashion" concept, in Casti oficial we believe that fashion with its imposing world-wide pressense must take a message and an action to create a useful purchase habit with a durable life cycle for the buyer and for other people through every acquisition.Our social commitment is our causality and goes hand to hand with this new healthy fashion for you and the world. And this is why we want to share it day to day, in every moment like a good cup of coffee.
"Buy what you like, drinking what you like, helping who needs it the most”PREORDER
Customer Service
We use cookies to improve our website and shopping experience. To learn more about cookies and how to change settings,
please consult the
cookie policy


Prefect Kasman:
To find the second scroll needed in order to become a Monk, you must meet Khavatari Toruku. To meet him, you must follow the path that heads north from the village. He will be near the fork in the road. When you meet him, give him this fig.
Come back after you have completed his Trial of Steel and you receive the scroll.


PhyloBox currently supports PhyloXML files. We hope to support other formats very soon, but for now...
If you want to learn more about phyloXML files, head over here
For now though, you can just grab our example file here (right click and download if not automatic), download it, then head back to our homepage and upload it through the dialog. You will be all set up to start playing.


1898 — Born in Belfast, Northern Ireland
1917 — Enlisted in the British army
1925 — Elected a Fellow of Magdalen College, Oxford
1931 — Converted to Christianity following a conversation with J.R.R. Tolkien and Hugo Dyson
1933 — Lewis' circle of friends known as The Inklings began meeting together regularly. Members included J.R.R. Tolkien, Warnie, Hugo Dyson, Charles Williams, Dr. Robert Havard, Owen Barfield, Weville Coghill and others.
1935 — Agreed to write the volume on 16th Century English Literature for the Oxford History of English Literature series. Published in 1954, it became a classic.
1937 — Received the Gollancz Memorial Prize for Literature in recognition of The Allegory of Love
1938 — Published The Out of the Silent Planet, the first book in his “Space Trilogy”
1940 — Published The Problem with Pain
1941 — Released The Screwtape Letters in weekly installments
1942 — Gave five live BBC radio talks on the subject “What Christians Believe” in January and February and then a second series of eight talks, entitled “Christian Behavior” in September through November
1944 — Gave seven prerecorded radio talks on the BBC entitled “Beyond Personality”
1947 — Published Miracles. A revised version was republished in 1960
1950 — Published the first book in the Chronicles of Narnia series, The Lion, the Witch and the Wardrobe. The series is widely regarded as a classic of children's literature.
1952 — Published Mere Christianity, one of the most influencial books on Christian teaching in the last century
1954 — Accepted the Chair of Medieval and Renaissance Literature at Cambridge
1955 — Published Surprised by Joy, a partial autobiography that focuses on his conversion to Christianity
1956 — Received the Carnegie Medal in recognition of The Last Battle, the last book in the Chronicles of Narnia series
1957 — Married Joy Davidman at her bedside in Churchill Hospital
1963 — Died on November 22
If you look for truth, you may find comfort in the end; if you look for comfort you will not get either comfort or truth only soft soap and wishful thinking to begin, and in the end, despair.
C.S. Lewis


OLEANNA A film review by Chuck Dowling Copyright 1996 Chuck Dowling
**1/2 - C:William H. Macy.
The content of a film has never made me angry. I have never seen a film where one of the character's actions were so frustrating that I just wanted to reach into the film and beat them. The story involves a college professor (Macy) who tries to help one of the girls in his class understand what he's teaching. Keep in mind that throughout the film the teacher does absolutely nothing wrong.The student returns later and accuses the professor of sexual harassment. Even though the professor explains to her that he was only helping her to understand, she says it's not his intentions that are the issue, it's how she interprets his actions. That's like if you are driving along and way off in the distance there's a car behind you. You then drive into a ditch because you think the car will catch up with you and crash into you.
This female character is clearly insane and if there are people like her who think how she thinks, then society as we know it will surely crumble. The film is well acted by Macy and not at all well acted by the psychotic student. The dialog seems forced, however, and for the first thirty minutes or so, the two characters have a conversation that would take normal people thirty seconds to have. Written and directed by David Mamet.
-- Chuck Dowling
Please visit my movie reviews web site at http://users.southeast.net/~chuckd21/ You'll be glad you did.
The review above was posted to the
rec.arts.movies.reviews newsgroup (de.rec.film.kritiken for German reviews).
The Internet Movie Database accepts no responsibility for the contents of the
review and has no editorial control. Unless stated otherwise, the copyright
belongs to the author.
Please direct comments/criticisms of the review to relevant newsgroups.
Broken URLs inthe reviews are the responsibility of the author.
The formatting of the review is likely to differ from the original due
to ASCII to HTML conversion.
Related links: index of all rec.arts.movies.reviews reviews


Class: Aws::FSx::Types::CreateFileSystemFromBackupRequest
| Relationships & Source Files | |
| Super Chains via Extension / Inclusion / Inheritance | |
|
Class Chain:
self,
Struct
|
|
|
Instance Chain:
self,
::Aws::Structure ,
Struct
|
|
| Inherits: |
Struct
|
| Defined in: | gems/aws-sdk-fsx/lib/aws-sdk-fsx/types.rb |
Overview
The request object for the CreateFileSystemFromBackup
operation.
Constant Summary
Instance Attribute Summary
-
#backup_id ⇒ String
rw
The ID of the source backup.
-
#client_request_token ⇒ String
rw
A string of up to 63 ASCII characters that Amazon FSx uses to ensure idempotent creation.
-
#file_system_type_version ⇒ String
rw
Sets the version for the Amazon FSx for Lustre file system that you're creating from a backup.
-
#kms_key_id ⇒ String
rw
Specifies the ID of the Key Management Service (KMS) key to use for encrypting data on Amazon FSx file systems, as follows:
-
#lustre_configuration ⇒ Types::CreateFileSystemLustreConfiguration
rw
The Lustre configuration for the file system being created.
-
#open_zfs_configuration ⇒ Types::CreateFileSystemOpenZFSConfiguration
rw
The OpenZFS configuration for the file system that's being created.
-
#security_group_ids ⇒ Array<String>
rw
A list of IDs for the security groups that apply to the specified network interfaces created for file system access.
-
#storage_capacity ⇒ Integer
rw
Sets the storage capacity of the OpenZFS file system that you're creating from a backup, in gibibytes (GiB).
-
#storage_type ⇒ String
rw
Sets the storage type for the Windows or OpenZFS file system that you're creating from a backup.
-
#subnet_ids ⇒ Array<String>
rw
Specifies the IDs of the subnets that the file system will be accessible from.
-
#tags ⇒ Array<Types::Tag>
rw
The tags to be applied to the file system at file system creation.
-
#windows_configuration ⇒ Types::CreateFileSystemWindowsConfiguration
rw
The configuration for this Microsoft Windows file system.
Instance Method Summary
Instance Attribute Details
#backup_id ⇒ String
(rw)
The ID of the source backup. Specifies the backup that you are copying.
# File 'gems/aws-sdk-fsx/lib/aws-sdk-fsx/types.rb', line 1470
class CreateFileSystemFromBackupRequest < Struct.new( :backup_id, :client_request_token, :subnet_ids, :security_group_ids, :, :windows_configuration, :lustre_configuration, :storage_type, :kms_key_id, :file_system_type_version, :open_zfs_configuration, :storage_capacity) SENSITIVE = [] include Aws::Structure end
#client_request_token ⇒ String
(rw)
A string of up to 63 ASCII characters that Amazon FSx uses to ensure idempotent creation. This string is automatically filled on your behalf when you use the Command Line Interface (CLI) or an Amazon Web Services SDK.
A suitable default value is auto-generated. You should normally not need to pass this option.
# File 'gems/aws-sdk-fsx/lib/aws-sdk-fsx/types.rb', line 1470
class CreateFileSystemFromBackupRequest < Struct.new( :backup_id, :client_request_token, :subnet_ids, :security_group_ids, :, :windows_configuration, :lustre_configuration, :storage_type, :kms_key_id, :file_system_type_version, :open_zfs_configuration, :storage_capacity) SENSITIVE = [] include Aws::Structure end
#file_system_type_version ⇒ String
(rw)
Sets the version for the Amazon FSx for Lustre file system that
you're creating from a backup. Valid values are 2.10
and 2.12
.
You don't need to specify FileSystemTypeVersion
because it will
be applied using the backup's FileSystemTypeVersion
setting. If
you choose to specify FileSystemTypeVersion
when creating from
backup, the value must match the backup's FileSystemTypeVersion
setting.
# File 'gems/aws-sdk-fsx/lib/aws-sdk-fsx/types.rb', line 1470
class CreateFileSystemFromBackupRequest < Struct.new( :backup_id, :client_request_token, :subnet_ids, :security_group_ids, :, :windows_configuration, :lustre_configuration, :storage_type, :kms_key_id, :file_system_type_version, :open_zfs_configuration, :storage_capacity) SENSITIVE = [] include Aws::Structure end
#kms_key_id ⇒ String
(rw)
Specifies the ID of the Key Management Service (KMS) key to use for encrypting data on Amazon FSx file systems, as follows:
- Amazon FSx for Lustre
PERSISTENT_1
andPERSISTENT_2
deployment types only.
SCRATCH_1
and SCRATCH_2
types are encrypted using the Amazon
FSx service KMS key for your account.
Amazon FSx for NetApp ONTAP
Amazon FSx for OpenZFS
Amazon FSx for Windows File Server
If a KmsKeyId
isn't specified, the Amazon FSx-managed ::Aws::KMS
key for
your account is used. For more information, see Encrypt in the
Key Management Service API Reference.
# File 'gems/aws-sdk-fsx/lib/aws-sdk-fsx/types.rb', line 1470
class CreateFileSystemFromBackupRequest < Struct.new( :backup_id, :client_request_token, :subnet_ids, :security_group_ids, :, :windows_configuration, :lustre_configuration, :storage_type, :kms_key_id, :file_system_type_version, :open_zfs_configuration, :storage_capacity) SENSITIVE = [] include Aws::Structure end
#lustre_configuration ⇒ Types::CreateFileSystemLustreConfiguration (rw)
The Lustre configuration for the file system being created.
AutoImportPolicy
ExportPath
ImportedChunkSize
ImportPath
# File 'gems/aws-sdk-fsx/lib/aws-sdk-fsx/types.rb', line 1470
class CreateFileSystemFromBackupRequest < Struct.new( :backup_id, :client_request_token, :subnet_ids, :security_group_ids, :, :windows_configuration, :lustre_configuration, :storage_type, :kms_key_id, :file_system_type_version, :open_zfs_configuration, :storage_capacity) SENSITIVE = [] include Aws::Structure end
#open_zfs_configuration ⇒ Types::CreateFileSystemOpenZFSConfiguration (rw)
The OpenZFS configuration for the file system that's being created.
# File 'gems/aws-sdk-fsx/lib/aws-sdk-fsx/types.rb', line 1470
class CreateFileSystemFromBackupRequest < Struct.new( :backup_id, :client_request_token, :subnet_ids, :security_group_ids, :, :windows_configuration, :lustre_configuration, :storage_type, :kms_key_id, :file_system_type_version, :open_zfs_configuration, :storage_capacity) SENSITIVE = [] include Aws::Structure end
#security_group_ids ⇒ Array
<String
> (rw)
A list of IDs for the security groups that apply to the specified
network interfaces created for file system access. These security
groups apply to all network interfaces. This value isn't returned
in later DescribeFileSystem
requests.
# File 'gems/aws-sdk-fsx/lib/aws-sdk-fsx/types.rb', line 1470
class CreateFileSystemFromBackupRequest < Struct.new( :backup_id, :client_request_token, :subnet_ids, :security_group_ids, :, :windows_configuration, :lustre_configuration, :storage_type, :kms_key_id, :file_system_type_version, :open_zfs_configuration, :storage_capacity) SENSITIVE = [] include Aws::Structure end
#storage_capacity ⇒ Integer
(rw)
Sets the storage capacity of the OpenZFS file system that you're
creating from a backup, in gibibytes (GiB). Valid values are from 64
GiB up to 524,288 GiB (512 TiB). However, the value that you specify
must be equal to or greater than the backup's storage capacity
value. If you don't use the StorageCapacity
parameter, the
default is the backup's StorageCapacity
value.
If used to create a file system other than OpenZFS, you must provide
a value that matches the backup's StorageCapacity
value. If you
provide any other value, Amazon FSx responds with a 400 Bad Request.
# File 'gems/aws-sdk-fsx/lib/aws-sdk-fsx/types.rb', line 1470
class CreateFileSystemFromBackupRequest < Struct.new( :backup_id, :client_request_token, :subnet_ids, :security_group_ids, :, :windows_configuration, :lustre_configuration, :storage_type, :kms_key_id, :file_system_type_version, :open_zfs_configuration, :storage_capacity) SENSITIVE = [] include Aws::Structure end
#storage_type ⇒ String
(rw)
Sets the storage type for the Windows or OpenZFS file system that
you're creating from a backup. Valid values are SSD
and HDD
.
Set to
SSD
to use solid state drive storage. SSD is supported on all Windows and OpenZFS deployment types.Set to
HDD
to use hard disk drive storage. HDD is supported onSINGLE_AZ_2
andMULTI_AZ_1
FSx for Windows File Server file system deployment types.
The default value is SSD
.
# File 'gems/aws-sdk-fsx/lib/aws-sdk-fsx/types.rb', line 1470
class CreateFileSystemFromBackupRequest < Struct.new( :backup_id, :client_request_token, :subnet_ids, :security_group_ids, :, :windows_configuration, :lustre_configuration, :storage_type, :kms_key_id, :file_system_type_version, :open_zfs_configuration, :storage_capacity) SENSITIVE = [] include Aws::Structure end
#subnet_ids ⇒ Array
<String
> (rw)
Specifies the IDs of the subnets that the file system will be
accessible from. For Windows MULTI_AZ_1
file system deployment
types, provide exactly two subnet IDs, one for the preferred file
server and one for the standby file server. You specify one of these
subnets as the preferred subnet using the WindowsConfiguration >
PreferredSubnetID
property.
Windows SINGLE_AZ_1
and SINGLE_AZ_2
file system deployment
types, Lustre file systems, and OpenZFS file systems provide exactly
one subnet ID. The file server is launched in that subnet's
Availability Zone.
# File 'gems/aws-sdk-fsx/lib/aws-sdk-fsx/types.rb', line 1470
class CreateFileSystemFromBackupRequest < Struct.new( :backup_id, :client_request_token, :subnet_ids, :security_group_ids, :, :windows_configuration, :lustre_configuration, :storage_type, :kms_key_id, :file_system_type_version, :open_zfs_configuration, :storage_capacity) SENSITIVE = [] include Aws::Structure end
#tags ⇒ Array
<Types::Tag> (rw)
The tags to be applied to the file system at file system creation.
The key value of the Name
tag appears in the console as the file
system name.
# File 'gems/aws-sdk-fsx/lib/aws-sdk-fsx/types.rb', line 1470
class CreateFileSystemFromBackupRequest < Struct.new( :backup_id, :client_request_token, :subnet_ids, :security_group_ids, :, :windows_configuration, :lustre_configuration, :storage_type, :kms_key_id, :file_system_type_version, :open_zfs_configuration, :storage_capacity) SENSITIVE = [] include Aws::Structure end
#windows_configuration ⇒ Types::CreateFileSystemWindowsConfiguration (rw)
The configuration for this Microsoft Windows file system.
# File 'gems/aws-sdk-fsx/lib/aws-sdk-fsx/types.rb', line 1470
class CreateFileSystemFromBackupRequest < Struct.new( :backup_id, :client_request_token, :subnet_ids, :security_group_ids, :, :windows_configuration, :lustre_configuration, :storage_type, :kms_key_id, :file_system_type_version, :open_zfs_configuration, :storage_capacity) SENSITIVE = [] include Aws::Structure end


Day One
- Date: 20th June, 2018
- 2.00pm – 5pm: Delegate Arrival & Registration
- 4.00pm – 5.00pm: Delegate Training Sessions
Day Two
- Date: 21st June, 2018
- 8.00am – 9.30a.m: Registration and check-in process
- 10.00am – 11.30a.m: Opening Ceremony
- 11.30am – 12.45pm: Diplomatic briefing
- 1.00pm - 2.00pm: Lunch
- 2.00pm – 4.00pm: Committee Session I
- 4.00pm – 4.30pm: Break
- 4.30pm – 6.00pm: Committee Session II
- 6.30pm – 9.00pm: Informal Social
Day Three
- Date: 22nd June, 2018
- 9.00am – 12:00pm: Committee Session III
- 12.00pm – 1.30p.m: Lunch
- 1.30pm – 2.30pm: Policy Workshops
- 2.30pm - 3.00pm: Break
- 3.00pm – 6.00pm: Committee Session IV
- 6.30pm – 9.00pm: Networking reception/li>
Day Four
- Date: 23rd June, 2018
- 10.00am – 12.00p.m: Closing Ceremony
- 12.00pm – 1.30p.m: Lunch
- 1.30pm – 2.30pm: Opportunity Expo/International exhibition
- 4.00pm – 7:00p.m: Diplomatic Dinner/Award night


Below, we give APE-plots of linear logistic regression and minimum-MSE fusions of the scores of the 9 component systems that were entered by Spescom DataVoice in the 2005 NIST Speaker Recognition Evaluation.
(These are lazy experiments, in the sense that we measured performance on the same data that was used to train the fusion weights. We found that for these low-capacity fusions and calibrations, this (dubious) practice does not influence the results much. I.E. the results on new test data is much the same.)
The APE-plots show discrimination and calibration loss. We give plots for both kinds of fusion, and for three different prior-weightings (p in the plots). In all three cases we see:
· Discrimination (green bar-graph) is very similar in both cases. (The DET-curves also coincide.)
· Overall calibration (red bar-graph) is better for the logistic regression, but local (at logit p) calibration (vertical distance between red and green curves) seems to be better for the MSE case.
· Although the prior-weighting does make a difference in both methods, logistic regression is much less sensitive to this parameter.


Each configs.ini file represents a single deck.
- In the main Receiver menu, note the deck number you would like to copy.
- Look at the bottom of your Receiver, there is a small grey text that says either
Local
or Appdata
- Local - go to
LioranBoard Receiver
folder and copy the configs.ini file with the same number-1 you noted in step 1. I.e. if your deck number is 2, the file containing your deck is configs1.ini
.
- Appdata - go to
C:/user/%username/appdata/local/lioranboard
and copy the configs.ini file with the same number-1 you noted in step 1. I.e. if your deck number is 2, the file with containing deck is configs1.ini
.
- To make sure you’re copying the right deck file, you can open the
configs.ini
file and find [configs]
section. The name value should be the name of your deck.


This template encourages to use akka-camel module for supporting EIP(Enterprise Integration Patterns).
In this example It will be shown how to request weather information to CDYNE weather public web service
It mainly has 3 methods:
The way to interact with these services is available at its WSDL document
Due to the interaction with the web server must be done with XML, and just to avoid writing a lot of boilerplate, we will use the support that JAXB gives us. With CXF wsdl2java tool we are able to generate JAXB annotated Java classes using the WSDL document we talked about before
This can be achieved by executing this:
wsdl2java -client -d -p -autoNameResolution `
Once these classes are generated, we're able to use them as sendable objects to camel endpoint.
Akka allows to integrate very easily with its camel module. In this example we're going to show how to implement an akka actor that receives 'weather objects' (let's call that way to the instances of the earlier generated classes) as requests and it will respond with some other 'weather objects'.
Main parts of this actor are:
The code looks like this:
class MyProducerActor(responseMail: ActorRef) extends Actor {
import helpers._
val camel = CamelExtension(context.system)
val uri = "cxf:http://wsf.cdyne.com/WeatherWS/Weather.asmx?" +
"serviceClass=com.cdyne.ws.WeatherSoap"
def receive = {
case WeatherMessage(body, headers) =>
camel.template.requestBodyAndHeaders(uri, body, headers) match {
case Response(List(awd: ArrayOfWeatherDescription)) => responseMail ! awd
case Response(List(wr: WeatherReturn)) => responseMail ! wr
case Response(List(fr: ForecastReturn)) => responseMail ! fr
}
}
}


태양의 후예
Organization
Kbs school
Ratings
Nielsen provided Korea: 38.8 %
The staff members
Directing ieungbok, gimeunsuk
script
Baek Sang Hoon, Helped
story
Unfamiliar place of extremes in the young soldier who dream of love and success and doctors to capture the value of the blockbuster human life by melodramatic.
DRAMA VIEW »
성균관 스캔들
Organization
Kbs school
The staff members
Directing Helped by
script
Hwang In Hyuk
story
The growth of the space of Joseon's off-limits to women attending the Youth Gang of Four that was going on melodrama.
DRAMA VIEW »
세상 어디에도 없는 착한 남자
Organization
Kbs school
The staff members
Directing gimjinwon, Lee Na Jung plays igyeonghui
script
igyeonghui
story
Strep and Chloe to death for his desire, but there is a man down the river. The man is Revenge out when conflict and recognize the betrayal of a woman become familiar with the love between soap opera.
DRAMA VIEW »


OLGA ROZHDESTVINA
Home
Paper
Canvas
Panel
Subscribe/Login
Subscribe Details
click the button
Username:
Email Address:
Optional
Login Details
click the button
Username:
Password:
Remember me
Cancel
Forgot
password?


|
Azure C++ Utils 1.2.9+3
Azure REST API Helpers for Modern C++
|
| Collection | Description |
|---|---|
siddiqsoft::ConversionUtils | Conversion helpers (via the Win32 WideFromMultiByte methods.): asciiFromWide, wideFromAscii, utf8FromWide, wideFromUtf8. |
siddiqsoft::DateUtils | Helpers for RFC7231 and RFC1123 as well as ISO8601 formatd time strings. Supports std::string and std::wstring output. |
siddiqsoft::Base64Utils | encode and decode support for std::string only. |
siddiqsoft::EncryptionUtils | Encryption helpers for: MD5, HMAC, JWTSHA256, SASToken and CosmosToken Supports output to std::string and std::wstring containers. |
NOTE The "keys" are binary contained within a
std::string
. Do not attempt to store them by conversion tostd::wstring
as they will produce different values and will fail against Azure. You can take the resulting "signed" string and convert it tostd::wstring
as they are url-safe utf-8.
Project is on GitHub


| quantmod-defunct {quantmod} | R Documentation |
The functions listed here are no longer part of quantmod.
# Defunct in 0.4-13 getFin(Symbol, env = parent.frame(), src = "google", auto.assign = TRUE, ...) getFinancials(Symbol, env = parent.frame(), src = "google", auto.assign = TRUE, ...) getSymbols.google(Symbols, env, return.class = "xts", from = "2007-01-01", to = Sys.Date(), ...)
Google Finance stopped providing data in March, 2018. This included historical
price data, and also financial information. This affected getFinancials
,
getFin
, and getSymbols.google
.


Craft your story
your experience is a great benefit to us allhuman
{% extends 'base.html' %} {% from 'render_fields.html' import render_textfield, render_submitfield, render_textareafield %} {% block content %}
your experience is a great benefit to us allhuman


Skin Diagnosis
About Our Vision
This application was created in order to provide you with a way to self-diagnose your
own skin conditions. In the case that our application does not adequately meet your
needs, we have provided an option for you to send your detailed information over to a
personal physician for further analysis and diagnosis.
To begin the self-diagnosis process, please click the button below!


Database Primer
Entity Relationships
One-to-many relationship
We have a company which manages multiple software projects. We hire people and assign them to projects. Consequently, each project will have several people working on it. From this statement, it is easy to observe that project-to-workers constitute a one-to-many relationship, i.e. multiple people work on one project.
Note that in this relationship, we are assuming that one person may not work on more than one project.
If we had to represent a one-to-many relationship in the relational database, it would do it like this:
Notes:
1. We only included a minimum set of fields to demonstrate the point of the current topic.
Let us analyze this design.
Each table must have a unique primary key. In both EMPLOYEE table and PROJECT tables, this field is named "ID". There are times when the primary key is made up of multiple keys, referred to as "composite key", however, we will not consider this case here.
For the EMPLOYEE table, we could have designated the SSN as the primary key since we know that the Social Security number would be unique. This would not be a great idea for at least two reasons:
1. We may hire some foreign workers who do not have a Social Security number and whatever unique ID they may have, will likely not conform to the SSN format - "xxx-xx-xxxx".
2. If we chose SSN to be the primary key, its datatype would be STRING. Primary keys are used for joining data from multiple tables. Joining on a field whose type is INTEGER is a lot faster than if its type were STRING.
All databases have a SEQUENCE GENERATOR. We can designate the primary key as a SEQUENCE GENERATED key and the database will created it for us. Thus, when we try to insert our first employee into the PEOPLE table, it's ID will be 1.
From EMPLOYEE and PROJECT tables above we can see that both have a primary key named "ID".
To express the one-to-many relationship, the EMPLOYEE table also has a key named "PROJECT_ID". The PROJECT_ID is a foreign key. A foreign key is the primary key of another table, in this case table PROJECT.
From the demonstration above, we can see that people whose IDs are 1 & 2 work for project ID=1, people with IDs 3, 4, and 5 work for project ID=2, etc.
The one-to-many (or many-to-one) relationships are incredibly common.
Consider another situation where we want to store information about each employee. In addition to the obvious fields such as "First Name", "Last Name", "SSN", each employee also has a phone number, email address, and residence address. However, many employees will have more than one phone number, email address, and may have multiple residences. The only logical way to represent this would be with a one-to-many relationship:
One-to-one relationship
One-to-one relationships are less common than many-to-one but they are still used very extensively. Lets go back to the task of storing data for each employee. In addition to storing employee's name, phone-numbers, etc., we also want to store employee's salary, start and end date (end data would be set to null for current employees), and other sensitive information. SSN field may also be considered sensitive data. While many applications will need access to employee's general information, such as name, department number, title, etc., only HR applications that are entrusted to few employees should have access to sensitive data, such as employee's salary.
Each database table can have associated privileges indicating who can see and modify data. Thus, we can create other tables for storing employee's sensitive data and assign privileges to this table to select few.
The one-to-one relationships are represented the same as the many-to-many relationships, that is with a foreign key.
Note:
1. EMPLOYEE_ID in EMPLOYEE_HR table is the foreign key. It contains values from EMPLOYEE.ID field.
2. Unlike the primary key, a foreign need need not (and usually will not) be unique and it may be null.
3. In the case of a one-to-one relationship, we could have placed the "foreign" key in either table.
For example, our design could look like this, where we place the foreign key - EMPLOYEE_HR_ID in the EMPLOYEE table.
However, since most people in the organization will be privy to data in the EMPLOYEE table, and only people who work in HR will be able to see the EMPLOYEE_HR table, it is better to place the foreign key into the EMPLOYEE_HR table so that those who examine contents of the EMPLOYEE table would not even know that EMPLOYEE_HR table exists.
There are other reasons to create one-to-one relationships.
Let's say we also want to store a single hobby for our employees. The description of a hobby may contain many fields. Most employees are very boring and do not have any hobbies. If we added Hobby fields to the EMPLOYEE table, most records would contain "holes", i.e. empty values. Thus, we can make a decision to define a HOBBY table and link it to EMPLOYEE with a one-to-one relationship.
Many-to-many relationship
Next, we expand our original definition by allowing one person to work on many projects. For example, some person may dedicate 60% of his time working on project #1 and 40% working on project #2. Any one person may work on more than two projects. Following this rule, we progress from a one-to-many relationship to a many-to-many relationship. In this many-to-many relationship, we have many people working on one project and each person may work on many projects. To support the many-to-many relationship, we need to introduce a new "MAPPING" table.
Note that table PROJECT_WORKER_MAP, maps Projects to Employees (Workers). For example,
From the PROJECT_EMPLOYEE_MAP table we can see that employees with IDs 1 and 2 work on project 1, employee with IDs 2, 4, and 5 work on project 2, employees with IDs 1, 7, and 8 work on project 3, etc. We can also observe that employee with ID 2 works on projects 1 and 2, employee with ID 1 works on projects 1 and 3.
With many-to-many relationships, it is quite possible to have some employees who do not work on any projects, let's say that an active employee goes on a sabbatical and will not be involved on any project. It is also possible to have a project that does not have any employees, for example, an upstart project that is still in the research phase. In cases where employees are not assigned to any projects or project do not have any employees, the PROJECT_EMPLOYEE_MAP table will not have a row for associating employee to a project.
Note that in the example above, no employee is assigned to project ID=5 and Employee ID=9 does not work on any projects.
Database Commands - DDL and DML
All databases support two types of commands: DDL that stands for Data Definition Language and DML that stands for Data Manipulation Language.
DDL Commands
The list of DDL commands is exhaustive. You use DDL commands to created and alter tables and indexes, drop (i.e. delete) tables, manage privileges, and much-much more.
Create Table
Before we can execute any database commands we need to create required tables and populate them with data. Let us examine the CREATE TABLE command:
|
create table worker ( id integer not null, created_by varchar(255), in_utc timestamp not null, last_modified_by varchar(255), out_utc timestamp, audit_id varchar(255), compensation double not null, worker_code varchar(255), worker_name varchar(255), primary key (id) ); |
The WORKER table in our real project has following fields:
Each field is listed along with its datatype. For STRING fields (i.e. varchar) we also need to specify maximum length.
Some fields may require a value, i.e. may not contain nulls. For example, "compensation double not null"
One or more fields must be designated as primary. (primary key (id)). A Primary key in unique and non-nullable by definition.
Indices and Unique Indices
Databases support many types of indices and we can't cover this topic exhaustively. Let's first discuss an index in a general sense.
Suppose we have an ORDERS table with 1,000,000 rows. We may want to perform certain types of operations on the ORDERS table very frequently. For example, find order where SELLER_NAME is "One First". With 1M rows, we would have to check 1M records in the worst case (order O(n)).
|
SELECT * FROM ORDERS WHERE SELLER_NAME = 'One First' |
However, if we create an index for field SELLER_NAME, we would be able to locate this record in almost constant time (O(1)).
The DDL command to create an index may look like this:
|
CREATE INDEX INDEX_SELLER_NAME ON ORDERS(SELLER_NAME) |
One of the common interview questions goes something like this:
"You work on your application and test it continuously in your dev (development) environment. Everything works great so you decide to deploy it to the production environment. However, in production, your application's performance becomes very sluggish. Why is that?"
Your answer may be as follows:
"It is quite possible that the dev database has been property tuned with required indices and it is therefore performant. However, production environments uses a different database and it is possible that it does not have all the required indices".
In addition to a simple index, databases support a notion of a unique index.
Let's say that we want our database to enforce business rules and one of our business rules is that the combination of values in audit_id and out_utc fields must be unique. Thus, it would be an error if two records had same values in both audit_id and out_utc fields. The DDL command for a unique index would look like this:
|
create unique index UKbe6uin1lttt8dh3oddmrb6g6d on worker (audit_id, out_utc); |
The name of the index ("UKbe6uin1lttt8dh3oddmrb6g6d" in the example above) was randomly generated and the name itself is not important. The only thing that is important is to identify a set of fields that must be unique.
Constraints
Let's go back to our many-to-many illustration and consider what would happen if someone decided to delete an employee with ID=1
|
delete from employee where id = 1 |
We would be left with records in table PROJECT_EMPLOYEE_MAP that would not make sense. (See records with ID 1 and 6 where the EMPLOYEE_ID is 1 which was deleted)
We can still delete employee with ID=1, however, we first need to delete records from the PROJECT_EMPLOYEE_MAP table that associate employee ID=1 with projects. This constraint can be enforced with command:
|
alter table project_worker_map add constraint FK6baomleyjvq2jkfy8n5tscn0l foreign key (worker_id) references worker; |
There are too many DDL commands and it is not important to know them all, only to know that they exist and can be easily discovered. Most of the common DDL commands affect tables and indices, such as:
|
create table ... alter table ... drop table ... create index ... create unique index ... drop index ... |
Privileges
We had mentioned earlier the need for a one-to-one relationship. In that example, we decided to store sensitive employee information inside EMPLOYEE_HR table, accessible to HR staff only. For people working in HR who do need this access, we can assign them to a user (or group) with a special name, i.e. USER_HR. Then, we can execute the following command:
|
GRANT ALL ON TABLE EMPLOYEE_HR TO USER USER_HR |
One may think that knowing the syntax of this command might allow you to peek at other employee's salary. However, only database admins, or other users with special privileges, would be able to execute the GRANT command.
DML Commands
The good news about Data manipulation commands (DML) is that they comprise only four commands: INSERT, UPDATE, DELETE, and SELECT. In the industry, these are often referred to as CRUD commands for Create, Read, Update, Delete.
The bad news is that some of these commands, particularly SELECT could get very complex. In this document we will only cover the basics.
INSERT Command
Most of the INSERT commands are very simple.
For example:
|
INSERT INTO WORKER(ID, AUDIT_ID, IN_UTC, OUT_UTC, WORKER_CODE, WORKER_NAME, COMPENSATION, CREATED_BY, LAST_MODIFIED_BY) VALUES(1, '00000000-0000-0000-0000-000000000001', CURRENT_TIMESTAMP - CURRENT_TIMEZONE, '9999-12-31', 'CODE-1', 'One First', 120000.00, 'unknown', 'unknown'); |
This example could also be written like this:
|
INSERT INTO WORKER VALUES(1, '00000000-0000-0000-0000-000000000001', CURRENT_TIMESTAMP - CURRENT_TIMEZONE, '9999-12-31', 'CODE-1', 'One First', 120000.00, 'unknown', 'unknown'); |
The reason why the above syntax would work is because we are populating every single field in the WORKER table. If we only wanted to populate some of the fields, we would need to list them, as in:
|
INSERT INTO WORKER(ID, AUDIT_ID, WORKER_CODE, WORKER_NAME, COMPENSATION) VALUES(1, '00000000-0000-0000-0000-000000000001', 'CODE-1', 'One First', 120000.00); |
Note that if you don't specify a field inside the INSERT statement, that field must be nullable.
UPDATE Command
To change values in an existing record we can do this:
|
update worker set compensation = 200000, worker_code = 'CODE-X' where id = 3 |
Naturally, this syntax could get a lot more complex and we will return to this command later.
DELETE Command
The simplest delete command looks like this:
|
delete from worker |
This command will delete all records from table WORKER.
One of the common interview questions it to ask about the difference of this delete command and the drop table command:
|
DELETE |
DROP |
|
delete from worker |
drop table worker |
When you use the delete command, the table still exists but contains no records. When you drop the table, the table is destroyed and you would need to create it again if you decide to add records to it.
More often than not, we will add a condition to the delete command, for example:
|
Command |
Description |
|
delete from worker where compensation < 100000 |
Delete workers who make less than 100,000 |
|
delete from worker where worker code in ('CODE-1', 'CODE-2') |
Delete workers with WORKER_CODE CODE-1 and CODE-2 |
SELECT Command
This is where all the fun is. Many books and PhD decertations are dedicated to this topic. Let us start simple:
Note:
1. To select all fields use "select * ..."
2. We use "where" to filter records to be displayed. Multiple expressions may be strung together with and, or, in, and other operators.
3. Note the usage of like operator
4. Aliases are often used with SELECT commands.
GROUP BY and HAVING Clauses
Another powerful feature of SELECT is to aggregate records via GROUP BY. Let's start with example. We would like to find out how many people work on each project. We use the PROJECT_WORKER_MAP table to map workers to projects:
|
Query |
Response |
|
select project_id, count(worker_id) as WorkerCount from project_worker_map group by project_id |
PROJECT_ID WORKERCOUNT -------------------------- 1 2 2 2 3 4 |
Suppose we are interested in seeing only those projects where the worker count is greater than 2
|
Query |
Response |
|
select project_id, count(worker_id) as Worker_Count from project_worker_map group by project_id having count(worker_id) > 2 |
PROJECT_ID WORKER_COUNT --------------------------- 3 4 |
Note:
having to group by is what where is to select
Above command is incredibly useful and you should store it somewhere in your memory bank. Often you run a process which will populate rows in some table. It may be an error to have records with a duplicate value in some field. Thus, you would execute the following query to check:
|
Query |
|
select some_field from some_table group by some_field having count(some_field) > 1 |
Joining Tables
Let us take a leap into something more interesting. We would like to determine the total compensations for each project. The compensation is specified in the WORKER table, so we need to join WORKER and PROJECT_WORKER_MAP tables.
|
Query |
Result |
|
select p.project_id, sum(w.compensation) as TotalComp from worker w, project_worker_map p where� = p.worker_id group by project_id |
PROJECT_ID TOTALCOMP ---------------------- 1 310000.0 2 425000.0 3 735000.0 |
Let us observe several things from above command:
In group by selects, fields that are listed on the select clause must match fields that appear in the group by clause. However, the select clause may also specify aggregate operations such as SUM, AVG, and others.
As a slight variation to above, let's say we only want to see projects whose total compensation is greater than 500,000.
|
Query |
Result |
|
select p.project_id, sum(w.compensation) as TotalComp from worker w, project_worker_map p where� = p.worker_id group by project_id having sum(w.compensation) > 500000 |
PROJECT_ID TOTALCOMP ---------------------- 3 735000.0 |
Notes:
In the previous query, I used alias w for worker and p for project_worker_map. If I had not used aliases, I would need to type the full name of the table, as in:
|
select project_worker_map.project_id, sum(worker.compensation) from worker, project_worker_map where worker = project_worker_map.worker_id group by project_id having sum(worker.compensation) > 500000 |
Min and Max
These examples will be provided without explanations:
|
Query |
Response |
|
select max(compensation) as Max from worker |
MAX -------- 240000.0 |
|
select min(compensation) as Min from worker |
MIN ------- 40000.0 |
Subqueries
Suppose we only have information on WORKER_CODE, i.e. 'CODE-1' and 'CODE-2' and we would like to find out what projects they are working on. To join table WORKER to table WORKER_PROJECT_MAP we need to have WORKER.ID and WORKER_PROJECT_MAP.WORKER_ID. However, we do not know values for WORKER.ID, we only know WORKER_CODE.
Before we accomplish our final task, let's perform some intermediate steps, like joining three tables: PROJECT, WORKER, and PROJECT_WORKER_MAP.
Note:
Second command uses order by clause to sort results by worker_name field.
However, for our current task, we don't have IDs of workers, we have worker_code. Thus, we need to use the worker_code to get to the WORKER.ID.
|
Query |
Result |
|
select p.project_name, w.worker_name from project p, worker w, project_worker_map m where m.project_id = p.id and m.worker_id = w.id and m.worker_id in ( select id from worker where worker_code in('CODE-1', 'CODE-2') ) |
PROJECT_NAME WORKER_NAME ------------------------- P-1 One First P-2 Two Second P-3 One First P-3 Two Second |
Note:
We need to join three tables and define the filtering criteria
We can combine this result with GROUP BY clause to determine the total compensation for these projects:
|
Query |
Result |
|
select p.project_name, sum(w.compensation) as TotalComp from project p, worker w, project_worker_map m where m.project_id = p.id and m.worker_id = w.id and m.worker_id in ( select id from worker where worker_code in('CODE-1', 'CODE-2') ) group by p.project_name |
PROJECT_NAME TOTALCOMP ----------------------- P-1 120000.0 P-2 240000.0 P-3 360000.0 |
Next Steps
The information presented so far does not even scratch the surface. There are things that you need to be aware of even though they are not demonstrated in this document.
SQL Standards
Like everything else, SQL went through a lot of iterations over many years. The SQL presented here follows the original SQL-86 format. I believe the latest is called SQL:2003. The syntax for SELECT commands has changed, however, the original syntax is still supported. Some operations differ by database providers. For example, to perform a left outer join (discussed shortly), you will need to adhere to the format of the database provider such as Oracle, Sybase, Postgres, DB2, etc.
The main point is to understand what capabilities are possible. It is easy to find the syntax for a specific command on the internet.
LEFT and RIGHT OUTER JOINS
So far, the examples provided here used a standard, or "INNER" join. For example, we can join multiple tables using INNER join to see all projects and people who are assigned to them. Some projects may not have any people assigned. Suppose we want to see all projects. If people are assigned to them, we will see person name in the WORKER column. If a project has no workers assigned, that project will not appear in the response. Often, we want to see projects and workers assigned to them and also projects that have no workers. This is the job for a LEFT OUTER join. If no one is assigned to some project, the project will still appear but the value in the WORKER column will be null. RIGHT OUTER join is similar to LEFT OUTER join but works in the right-to-left order.
SELF JOIN
Here is one of the most common problems for a SELF JOIN. Let's say we have a table of employees, along with their salaries and ID of the manager. Let's say our fictitious table looks like this:
We need to answer following question: "Provide a list on employees who make more money than their manager." From table's data we can observe that Employee IDs 1, 2 3, 4 all report to employee whose ID is 5. Only employee ID=4 makes more money than his manager.
This question comes up so often at interviews that I owe you a demonstration.
Let's create a new table with data as shown above:
|
Create Table |
create table workerX (id integer not null, name varchar(255), compensation double not null, manager_id integer not null) |
|
Populate |
insert into workerX (id, name, compensation, manager_id) values (1, 'One First', 50000, 5) insert into workerX (id, name, compensation, manager_id) values (2, 'Two Second', 70000, 5) insert into workerX (id, name, compensation, manager_id) values (3, 'Three Third', 90000, 5) insert into workerX (id, name, compensation, manager_id) values (4, 'Four Fourth', 180000, 5) insert into workerX (id, name, compensation, manager_id) values (5, 'Five Fifth', 160000, 9) |
Now we can execute a query to find all employees who make more money than their managers:
|
Query |
Result |
|
select employee.* from workerX employee, workerX manager where employee.manager_id = and employee.compensation > manager.compensation |
ID NAME COMPENSATION MANAGER_ID ---------------------------------------- 4 Four Fourth 180000.0 5 |
Note how use of aliases, employee and manager, were absolutely essential for a SELF JOIN query.
UNIONS
There may be times when we would like to combine results from multiple tables. Our SELECT clause identifies fields and they datatype. As long as the fields in the SELECT clause match, data from multiple tables may be combined with a UNION command.
Stored Procedures, Triggers, and Temporary Tables
SELECT command is extremely powerful and provides many clauses to wield incredible power. In addition to standard features of the SQL, each database provide furnishes a library of functions to works with strings, dates, and just about anything else. However, sometimes all this power is still not enough. There may be times when it would be useful to create intermediate results and stored them in the temp table. Next, subsequent commands can me used in combination with data in the temp table to produce more elaborate answers.
For anything that can't be done with SQL, there are stored procedures. Each database provider has its own programming language to interact with databases. A program written in this language is called the stored procedure. Some companies build their entire applications with stored procedures. In my view, this is a terrible idea but it may be justified for certain types of projects. One of the problems if stored procedures is that they can't be debugged. You may need tp place results of some intermediate computation into a table for debugging purposes.
It is also important to realize that a stored procedure is often composed to several SQL statements without resorting to any other programming aspects. To support transactions, you will need to place your SQL commands inside the stored procedure.
A Trigger is a stored procedure. It is triggered when a certain action occurs, such as inserting a new row or updating it. Some time ago, triggers where relied on very heavily, however, over the years they usefulness has diminished.
Transactions and RollBacks
Let's say we have a site for taking customer orders. When the order is placed we need to update ORDERS table, INVENTORY table, and possible CUSTOMERS table to keep track of all the money they had spent on our crap.
Say we update the ORDERS table first and then try to update the INVERTORY table, but that update fails. Now we have a system in an inconsistent state. To prevent this inconsistent state we need to ROLL-BACK our transaction. Thus, either all commands complete successfully or none at all.
Failure to update the INVERNTORY table may happen for many diffident reasons, for example, the table may run out of storage space that was allocated for it.
Attachments:
image-20201125-180326.png (image/png)
image-20201125-180420.png (image/png)
image-20201125-180454.png (image/png)
image-20201125-180521.png (image/png)
image-20201125-180600.png (image/png)
image-20201125-180629.png (image/png)
image-20201125-180709.png (image/png)
image-20201125-180812.png (image/png)
image-20201125-181044.png (image/png)
image-20201125-181101.png (image/png)
image-20201125-181300.png (image/png)
image-20201125-181453.png (image/png)


One Pot
Game Rules:
There is only one magical pot of gold.
You can grab what's in the pot with the big button.
When no one grabs the gold, the pot grows faster.
No one has grabbed gold for X seconds.
If you grab now, you will get Y gold.
You got
0 gold!
A total of
0
gold belongs to
now.
Highscores


I was recently prescribed tramadol quite legitimately in Thailand, for severe headache. Whereas one (as rx) had no effect, upping the dose soon brought on very pronouced opiate effects, i began to feel extremley relaxed and pleasant with around 300mg, in a slightly different way to codeine, the experience was cleaner, without the nausea, gastric effects and scratching that codeine sometimes brings.
However i should point out that i have a regretably high tolerance to opiates and would urge caution with this, and all other opiates. Although i was advised that it was not addictive, i found increasing tolerance and dependance did occur with time, and i ended up taking 700mgs at a go. This was actually fantastic, the full opiate, laid out place of safety thing, but a non participating observer reported my behavior as extremely bizarre while under the influence. I was talking to myself and other non existent individuals, trying to rest on my outstetched arms in mid air,and appearing very irritated when disturbed from my reverie.
After two months use at around 500-700mg a day i moved on to malaysia where tramadol was unavailable. I experienced a very unpleasant cold turkey experience after about 48 hours with muscle cramps, fever,shaking and postural hypotension (Feeling faint on standing up) and some horrific trainspotting type nightmares.It took me three weeks to feel o.k again.
Tramadol is available over the counter in thailand for about two pounds a box. According informal word of mouth researched by myself, most people seem to have fun on 4-6 tablets - 200-300mg.I have heard of people having very unpleasant trips however,although i had nothing but fun till i tried to quit.one thing however,its really hard to pee after taking even small doses, this lasts for about 12 hours after the last dose and can be a little freaky.would i recommend it..? yeah,but thats me..caveat emptor as they say....(let the buyer beware!)
Experience Reports are the writings and opinions of the individual authors who submit them.
Some of the activities described are dangerous and/or illegal and none are recommended by Erowid.


Files | |
| file | nimu_eth.h |
| This file defines the interface applications can use when integrating the Network Interface Module Ethernet driver adaptation layer. | |
Functions | |
| void * | Osal_nimuMalloc (uint32_t num_bytes, uint32_t alignment) |
| void | Osal_nimuFree (void *dataPtr, uint32_t num_bytes) |
This file defines the interface applications can use when integrating the Network Interface Module Ethernet driver adaptation layer
| void Osal_nimuFree | ( | void * | dataPtr, |
| uint32_t | num_bytes | ||
| ) |
============================================================================
Osal_nimuFree
brief
This API frees and restores a given memory location pointer 'dataPtr' of size 'num_bytes' to its original heap location. Frees up memory allocated using Osal_nimuMalloc ()
| [in] | dataPtr | Pointer to the memory block to be cleaned up. |
| [in] | num_bytes | Size of the memory block to be cleaned up. |
| void* Osal_nimuMalloc | ( | uint32_t | num_bytes, |
| uint32_t | alignment | ||
| ) |
============================================================================
Osal_nimuMalloc
brief
This routine implements the memory handler for the NIMU library. The API allocates a memory block of a given size specified by input parameter 'num_bytes'.
This API should allocate memory from shared memory.
| [in] | num_bytes | Number of bytes to be allocated. |


@* * Copyright 2017 Interel * * 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. * * Page top navigation template *@ @import containers.UserData @(title: String, user: Option[UserData])(implicit environment: play.api.Environment)


Reports after Spilt Milk of taxi drivers demanding big cash up front and not using the meter
by Peter BrewerPassengers complaining of being charged three times the standard fares after leaving Canberra's Spilt Milk concert on Saturday are being urged to contact the taxi company and Access Canberra.
Reports have emerged from after the music festival of interstate passengers being charged $95 for a taxi trip from Civic to Holt which would usually cost around a third of that sum, and being told by the driver to pay "up front" or risk being refused travel.
The visitors accepted the conditions and paid the money for fear of losing their place in the lengthy queue at the city rank.
They noted that the taxi meter was not turned on for the journey, which is an offence under the Road Transport Act if the taxi is operating in that role and not in a ride sharing capacity.
Some of Canberra's taxi drivers operate as rideshare operators to supplement their income however some ride share operators, such as Uber, expressly forbid the use of large commercial graphics or branding on their vehicles.
Convention taxi signage would breach the minimum Uber requirements.
UberX rideshare operators are not permitted to be taxis.
Meanwhile, rival rideshare operator Ola states unequivocally on its website: "currently, we are only accepting private hire vehicles on our platform".
Access Canberra says that "delegated staff have the power to issue infringements for breaches of public transport law in addition to any other penalties which the transport booking service may impose as part of their disciplinary policies".
Under the Road Transport Act, a taxi driver "may ask the person to give the driver a fare deposit if the driver believes on reasonable grounds that the person may not be able to, or will not, pay the estimated fare for the hiring".
Police reported they were generally pleased with crowd behaviour at the music festival.
A small number of people were taken into protective custody due to intoxication and five people were "dealt with" for drug possession.
No major incidents were reported.


This Website is Create By Himanshu Singh, our Website on the topic of School-Management-System and I am from INDIA.


Congratulations! Yay, you've been accepted to present at Works in Progress 2019! We just need a few more things (and your exhibition fee) and you'll be on your way!
Something went wrong -- please scroll down to fix it so we can process your submission!
{% endif %}


This project is created for the Master of Data Science program course DSCI524 at the University of British Columbia. We strive to complete the assigned tasks to the best of our abilities. We all share the same goal of learning as much as we can, and creating a beautiful piece of work for a portfolio at the same time. In hopes of creating an effective, fair, and fun group we should all follow the following rules:
We are committed to creating a friendly and respectful place for learning, teaching and contributing. This project is created and maintained by people of different backgrounds orginating from the UBC Masters of Data Science program. As such, this project will adhere to the MDS code of conduct and the UBC Student Code of Conduct. Similarly, anyone contributing towards this project are expected to be courteous, understanding and welcoming of diversity.
All participants in our events and communications are expected to show respect and courtesy to others. In accordance with the Inclusion Statement, all interactions regarding this project are expected to:
Examples of unacceptable behaviour include, but are not limited to:
Any form of inappropriate behavior should be reported as soon as possible, and will be dealt with accordingly.