WHY CHOOSE VAMOS SPANISH SCHOOL IN BUENOS AIRES?
Personalized Spanish learning experience with our professional Academic Team
- We have a dedicated Academic Director oversees and plans every single class to make sure each Spanish lesson is right for your level and progresses in a continuous manner.
- We create specially designed learning materials for each level and every class.
- The best way to learn a language is full immersion. All classes are taught entirely in Spanish.
- Group class size is strictly kept small at no more than 6 students per class.
- Classes are held inside a beautiful French-style building on a tree lined street.
- We provide weekly updates on what is happening in and around Buenos Aires, to make sure you are well-informed and get the most out of your time in this wonderful city.
- Our knowledgeable staff are always on hand to help you and to answer your questions.
- We serve as a great base and point of contact when you are in need while travelling around in Argentina.
International and Social Atmosphere
- Every week we receive a diverse mix of students from all walks of life from all over the globe.
- A welcome orientation on your first day of class while you meet your new schoolmates.
- Our after-class workshops and social events make it easy to meet new friends.
Well-located in the dynamic Palermo neighborhood
- Just a few minutes walk to Subway Line D
- More than a dozen bus routes
- Trendy shopping mall and boutiques
- Many cafés, restaurants, ice-cream shops, bakeries and lush green parks nearby
- No registration fee or extra material charges for your Spanish classes
- We are located in the most popular neighborhood, Palermo
- Fair prices include Free Spanish language and cultural workshops
- Complimentary coffee/tea throughout the day to keep you motivated to learn!


--- layout: post title: Rarely seen 1974 promo for Sparks ‘This Town Ain’t Big Enough For The Both Of Us’ published: true ---
Amazing.


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$4,000 and 'a real bunny'? 10-year-old's lavish Christmas list goes viral
by Michelle Ewing, Cox Media Group National Content DeskLOS ANGELES -
Santa has his work cut out for him if he plans on making this 10-year-old girl's lavish Christmas dreams come true.
According to Fox News and the CBC, a Los Angeles dad known as @A_Johnson412 on Twitter shared a photo of his daughter's wish list last week, saying the girl "must be out of her mind." Her requests? "A real bunny," clothes for said bunny, Gucci slides, a Chanel purse, $4,000 and 21 other items. The list ends with the surprisingly affordable "alarm clock."
The post quickly went viral, racking up 128,000 likes, 25,000 retweets and nearly 6,000 replies by Wednesday morning.
"Sneaking in that 4K at the bottom is a rockstar move," one commenter wrote.
 "Nursing homes can get lonely."
But others were more critical.
"Get her that alarm clock sis!" one Twitter user replied, adding that the girl's father should "tell her it'll wake her up from that dream."
"Lmao wake her up for a job," another post read.


Anti-tax initiative promoter says he’s running for governor
OLYMPIA, Wash. (AP) - A career anti-tax initiative promoter who has been accused by the state attorney general of using campaign donations for his personal use has announced he’s running for governor.
Tim Eyman made the announcement while testifying at a Sound Transit board meeting Thursday in Seattle. The board was meeting about possible legal action against Eyman’s Initiative 976, which voters approved earlier this month. The measure cuts car tabs to $30, which the state has said will lead to deep cuts in road and public transit projects.
KIRO-TV reports Eyman says he will file paperwork Monday. If he does, he’ll join a handful of lesser-known candidates who have already declared against Democratic incumbent Gov. Jay Inslee.
Eyman has been the subject of a long-running lawsuit by Attorney General Bob Ferguson, who says that Eyman violated state campaign-finance laws and covertly used his initiative drives to enrich himself.
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| {{ state.name }} | National | |||||
|---|---|---|---|---|---|---|
| Year | Margin of victory (pts) | Margin of victory (pts) | ||||
| {{ row.year }} | {{ row.winnerState }} | +{{row.winningPctState | round(1)}} | {{ row.winnerFederal }} | +{{row.winningPctFederal | round(1)}} |


Red Hook Quantified Community
Quantifying a community is a crucial issue and it is important to measure it regarding to livable conditions of the society. This project aims to define and drive research of how micro-geography sensor data can be leveraged to explore neighborhood dynamics. In this perspective, Reed Hook Area is selected for implementing the idea of Quantifying Community with the sensors
Survey
Your ideas are important for us


I’m Philip Savenok, a 29-year-old Front-End Developer from New York where I work and study. With a background in engineering, my strength lies in problem-solving mind. I like to develop and create web applications. Keeping things organized helps me to increase my efficiency.
Proficient with:
If you want to know more about my work, please feel free to email me.


My name is Erika Zibelnik and I currently reside in Melbourne, Florida. I am learning full stack web development through UCF's coding bootcamp. This will prepare me for an environment that is looking for innovation, education, and creativity.
I have a diverse background which enables me to adapt and problem solve as needed. This is quite important in web development, and I believe will enable me to thrive. My past experiences have also had me work with diverse group of individuals, enabling me to work well with clients and co-operate with coworkers for the best results and productivity.
Email me at e.m.zibelnik@gmail.com


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TechCrunch
@TechCrunch -
17m
MacBook Air Refresh With Spec Bumps Said To Be Coming Tomorrow
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TechCrunch
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MacBook Air Refresh With Spec Bumps Said To Be Coming Tomorrow
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--- title: "MSc in behavioural ecology" author: "Julien Martin" date: 2021-02-18 categories: ["Opportunities"] tags: ["manatees", "UAV"] summary: MSc on behavioural ecology of manatees reading_time: false # Show estimated reading time? share: false # Show social sharing links? profile: false # Show author profile? comments: false # Show comments? ---
Using well known population of manatees along the east coast of Mexico, the project will be looking at the variation in foraging behaviour with reproductive status in manatees using a spatial ecology approach based on aerial imaging. Data collection will be done from the shore using aerial imaging from a small UAV (unmanned aerial vehicle).
The project will be supervised by Julien Martin (uOttawa, Canada). The project will be done in collaboration with Guillaume Rieucau (LUMCON, USA) and Nataly Castelblanco-Martínez (FINS). The student will be based at the Biology department of the University of Ottawa and will participate to field work in Mexico during the summer.
Available for 2 years. The student is expected to complete a minimum of two teaching assistantship per year.
Ideally September 2021 or January 2022
The ideal candidate should have:
Students that are interested should send by email to Julien Martin (julien.martin@uottawa.ca):


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Transport and logistics plays an essential role in all our lives.
The passenger transport industry employs hundreds of thousands of people in order to run, drive, and support transport and travel, from aviation to rail and bus to coach.
Meanwhile, logistics are essential in making sure the right amount of a product shows up at the right place at the right time. It deals with a range of functions, such as inventory management, warehousing, distribution, transportation and customer service.


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Practice: Implement a GRU Language Model¶
In this tutorial, we will train a neural language model on MSCOCO dataset.
We will focus on how to use cotk
rather than the neural networks,
so we assume you have known how to construct a neural network.
After reading this tutorial, you may know:
- How to use
cotk.dataloader
downloading and loading dataset. - How to train model with the support of
cotk
. - How to use
cotk.metric
evaluating models.
cotk
does not rely on any deep learning framework,
so you can even use shallow models like ngram language model.
However, this tutorial constructs neural networks with
pytorch
, so make sure you have installed the following package:
- Python >= 3.5
- cotk
- pytorch >= 1.0.0
- livelossplot (optional, just for showing loss)
Source codes
You can click here for the following ipynb files. You can also run the code online on google colab without installing any packages.
Preparing the data¶
cotk
provides dataloader
to download, import and preprocess data.
Therefore, we first construct a cotk.dataloader.MSCOCO
to load MSCOCO dataset.
from cotk.dataloader import MSCOCO
from pprint import pprint
dataloader = MSCOCO("resources://MSCOCO_small") # "resources://MSCOCO_small" is a predefined resources name
print("Vocab Size:", dataloader.vocab_size)
print("First 10 tokens:", dataloader.vocab_list[:10])
print("Dataset is split into:", dataloader.key_name)
data = dataloader.get_batch("train", [0]) # get the sample of id 0
pprint(data, width=200)
print(dataloader.convert_ids_to_tokens(data['sent'][0]))
Out:
INFO: name: MSCOCO_small
INFO: source: default
INFO: processor type: MSCOCO
100%|██████████| 1020154/1020154 [00:00<00:00, 1853831.54B/s]
INFO: resource cached at /root/.cotk_cache/9e4c0afe33d98fa249e472206a39e5553d739234d0a27e055044ae8880e314b1_unzip/mscoco
valid vocab list length = 2588
vocab list length = 12411
train set. invalid rate: 0.031716, unknown rate: 0.000000, max length before cut: 55, cut word rate: 0.000022
dev set. invalid rate: 0.034089, unknown rate: 0.000000, max length before cut: 46, cut word rate: 0.000000
test set. invalid rate: 0.031213, unknown rate: 0.000000, max length before cut: 27, cut word rate: 0.000000
Vocab Size: 2588
First 10 tokens: ['<pad>', '<unk>', '<go>', '<eos>', '.', 'a', 'A', 'on', 'of', 'in']
Dataset is split into: ['train', 'dev', 'test']
{'sent': array([[ 2, 6, 67, 651, 549, 11, 5, 65, 89, 10, 115, 349, 83,
4, 3]]),
'sent_allvocabs': array([[ 2, 6, 67, 651, 549, 11, 5, 65, 89, 10, 115, 349, 83,
4, 3]]),
'sent_length': array([15])}
['<go>', 'A', 'blue', 'lamp', 'post', 'with', 'a', 'sign', 'for', 'the', 'yellow', 'brick', 'road', '.']
cotk.dataloader.MSCOCO
has helped us construct vocabulary list and
turn the sentences into index representation.
Note
You can also import dataset from url (http://test.com/data.zip) or local path (./data.zip), as long as the format of the data is suitable.
Note
You may find data
contains similiar key sent
and sent_allvocabs
.
The difference between them is that sent
only contains
valid vocabularies and
sent_allvocabs
contains both valid vocabularies and
invalid vocabularies.
Training models¶
First we construct a simple GRU Language model using pytorch
.
import torch
from torch import nn
embedding_size = 20
hidden_size = 20
class LanguageModel(nn.Module):
def __init__(self):
super().__init__()
self.embedding_layer = nn.Embedding(dataloader.vocab_size, embedding_size)
self.rnn = nn.GRU(embedding_size, hidden_size, batch_first=True)
self.output_layer = nn.Linear(hidden_size, dataloader.vocab_size)
self.crossentropy = nn.CrossEntropyLoss()
def forward(self, data):
# data is the dict returned by ``dataloader.get_batch``
sent = data['sent']
sent_length = data['sent_length']
# sent is a LongTensor whose shape is (batch_size, sent_length)
# sent_length is a list whose size is (batch_size)
incoming = self.embedding_layer(sent)
# incoming: (batch_size, sent_length, embedding_size)
incoming, _ = self.rnn(incoming)
# incoming: (batch_size, sent_length, hidden_size)
incoming = self.output_layer(incoming)
# incoming: (batch_size, sent_length, dataloader.vocab_size)
loss = []
for i, length in enumerate(sent_length):
if length > 1:
loss.append(self.crossentropy(incoming[i, :length-1], sent[i, 1:length]))
# every time step predict next token
data["gen_log_prob"] = nn.LogSoftmax(dim=-1)(incoming)
if len(loss) > 0:
return torch.stack(loss).mean()
else:
return 0
If you are familiar with GRU, you can see the codes constructed a
network for predicting next token. Then, we will train our model with
the help of cotk
. (It may takes several minites too train the model.)
from livelossplot import PlotLosses
import numpy as np
net = LanguageModel()
optimizer = torch.optim.Adam(net.parameters(), lr=5e-3)
epoch_num = 100
batch_size = 16
plot = PlotLosses()
for j in range(epoch_num):
loss_arr = []
for i, data in enumerate(dataloader.get_batches("train", batch_size)):
# convert numpy to torch.LongTensor
data['sent'] = torch.LongTensor(data['sent'])
net.zero_grad()
loss = net(data)
loss_arr.append(loss.tolist())
loss.backward()
optimizer.step()
if i >= 40:
break # break for shorten time of an epoch
plot.update({"loss": np.mean(loss_arr)})
plot.draw()
print("epoch %d/%d" % (j+1, epoch_num))
Out:
loss:
training (min: 3.126, max: 6.401, cur: 3.152)
epoch 100/100
Evaluations¶
How well our model can fit the data? cotk
have provided
some standard metrics for language generation model.
Teacher Forcing¶
perplexity
is a common used metric and it need the predicted distribution
over words. Recall we have set data["gen_log_prob"]
in previous
section, we use it right now.
metric = dataloader.get_teacher_forcing_metric(gen_log_prob_key="gen_log_prob")
for i, data in enumerate(dataloader.get_batches("test", batch_size)):
# convert numpy to torch.LongTensor
data['sent'] = torch.LongTensor(data['sent'])
with torch.no_grad():
net(data)
assert "gen_log_prob" in data
metric.forward(data)
pprint(metric.close(), width=150)
Out:
test set restart, 78 batches and 2 left
{'perplexity': 32.94079849259241, 'perplexity hashvalue': '4f101c2986f1fe10ce1d2197c3086d3659aec3e6495f381d67f00b4dbb40a538'}
The codes above evaluated the model in teacher forcing mode, where every input token is the real data.
Note
The type of data['gen_log_prob']
is torch.Tensor
, but most metrics can
not receive a tensor input as we are trying to implement a library not
depending on any deep learning framework. metric.PerplexityMetric
just use torch
to accelerate the calculation, a numpy.ndarray
can also be accepted.
Free Run¶
A language model can also generate sentences by sending the generated token back to input in each step. We call it “freerun” or “inference” mode.
Pytorch
doesn’t provide a convenience api for freerun, here we implement a
simple version that all the prefixes will be recalculated at every step.
metric = dataloader.get_inference_metric(gen_key="gen")
generate_sample_num = 1
max_sent_length = 20
for i in range(generate_sample_num):
# convert numpy to torch.LongTensor
data['sent'] = torch.LongTensor([[dataloader.go_id] for _ in range(batch_size)])
data['sent_length'] = np.array([1 for _ in range(batch_size)])
for j in range(max_sent_length):
with torch.no_grad():
net(data)
generated_token = torch.multinomial(data['gen_log_prob'].exp()[:, -1], 1)
data['sent'] = torch.cat([data['sent'], generated_token], dim=-1)
metric.forward({"gen": data['sent'][:, 1:].tolist()})
pprint(metric.close(), width=250)
Out:
100%|██████████| 1000/1000 [00:00<00:00, 1063.21it/s]
{'bw-bleu': 0.04871277607530735,
'fw-bleu': 0.22873635755754274,
'fw-bw-bleu': 0.08032018568655393,
'fw-bw-bleu hashvalue': '3018dc317f82b6013f011c1f8ccd90c5affed710b7d7d06a7235cf455c233542',
'gen': [['A', 'red', 'bus', 'car', 'being', 'snow', 'behind', 'much', 'to', 'it', '.'],
['The', 'pair', 'of', 'cover', 'position', 'two', 'vases', 'screen', '.'],
['A', 'black', 'dog', 'walking', 'from', 'a', 'bush', '.'],
['The', 'zebra', 'sits', 'in', 'front', 'of', 'a', 'bathroom', 'lamp', '.'],
['<unk>', 'single', 'boys', 'using', 'a', 'baseball', 'game', ',', 'holds', 'her', 'dog', '.'],
['A', 'picture', 'of', 'a', 'shopping', 'colored', 'restroom', 'with', 'broccoli', 'on', 'it', '.'],
['A', 'people', 'that', 'is', 'stopped', 'seen', 'on', 'back', 'it', '.'],
['A', 'street', 'holding', 'black', 'with', 'grass', 'up', 'up', 'at', 'a', 'white', 'mirror', '.'],
['A', 'cow', 'sits', 'in', 'front', 'of', 'the', 'bowl', 'with', 'a', 'pan', 'are', 'playing'],
['A', 'woman', 'looking', 'hardwood', '<unk>', 'of', 'some', 'is', 'open', '.'],
['A', 'fire', 'hydrant', 'taking', 'a', 'red', 'toy', 'feet', '.'],
['A', 'woman', 'is', 'flying', 'on', 'a', 'cell', 'phone', 'somewhere', '.'],
['A', 'bear', 'holding', 'a', 'hill', 'suit', 'it', 'on', 'a', 'wooden', 'board', '.'],
['Woman', 'playing', 'frisbee', 'below', 'food', 'across', 'the', 'ocean', '.'],
['There', 'has', 'some', 'two', 'rice', 'screens', 'with', 'several', 'colorful', 'toy', 'on', 'a', 'white', 'tile', 'toilet', '.'],
['Large', '<unk>', 'with', 'many', 'pretty', 'an', 'apple', '.']],
'self-bleu': 0.07416490324471028,
'self-bleu hashvalue': '9f1121d3988ef4789943ef18c1c0b749eec0d8eee3f12270671605ce670225f6'}
Hash value¶
Hash value is for checking whether you use the test set correctly. We can refer to dashboard (TO BE ONLINE) for the state of art on this dataset, and we find our hashvalue is correct.
However, if teacher forcing is tested as following codes, we will see a different hash value, which means the implementation is not correct.
metric = dataloader.get_teacher_forcing_metric(gen_log_prob_key="gen_log_prob")
for i, data in enumerate(dataloader.get_batches("test", batch_size)):
# convert numpy to torch.LongTensor
data['sent'] = torch.LongTensor(data['sent'])
with torch.no_grad():
net(data)
assert "gen_log_prob" in data
metric.forward(data)
if i >= 15: #ignore the following batches
break
pprint(metric.close(), width=150)
Out:
test set restart, 78 batches and 2 left
{'perplexity': 31.883897093289583, 'perplexity hashvalue': '125a45af618245364a722ad3fcac59534f30e64aa7e2dfefd35402cd67a74cec'}
Additional: Word Vector¶
It is a common technique to use pre-trained word vector when
processing natural languages. cotk
also provides a module wordvector
that help you downloading and get word vectors.
from cotk.wordvector import Glove
wordvec = Glove("resources://Glove50d_small")
self.embedding_layer.weight = nn.Parameter(torch.Tensor(wordvec.load(embedding_size, dataloader.vocab_list)))
We can add these lines at the end of LanguageModel.__init__
.
Source code
You can find the results and codes with pretrained word vector at here for ipynb files or run the code on google colab.


Minkush Jain
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Minkush Jain
I am a
Enthusiast Programmer. Engineer at heart.
Python Script to Automate Mailing
GSoC 2018
Posted by
Minkush Jain
on March 22, 2018


NEStrisChamp works with the concepts of room. Each user has 2 rooms:
The key is for players to OCR their game frames into the correct room.
For single player rooms, you just need to send your game frames into the room and into the view for them to be rendered.
For Math room, you may invite as many people as you want to be producers, and you'll select who out of the room members gets to be player 1 and player 2.
In single player mode, frame data is passed straight from the producer into 1 or more views.
In competition mode, all producers emit data, but The room owner assigns a given producer to be player 1 and anotherproducer to be player 2. Only the game frame of these 2 players are sent to the views.
Since views are typically setup in OBS, the URL needs to identify the room owner by itself, This is achieved by assigning a secret to each user that can placed in the URL. It's not super secure, but whatever, this tool is not hosting state secrets -_-
http://nestrischamps.herokuapp.com/view/LAYOUT_NAME/USER_SECRET
The layouts available so far are as follow:
At your first login, a secret would have been generated for you and added to your user record. You can see it in your personl renderer links which are available here.
Hopefully in the future, users will be able to contribute their own template.
Several of the layouts have a black background with Tetris pieces. If you
do not like it and would prefer a transparent background to place the
layout above it, add the query string `?bg=0` into the view URL. Like
so:
http://nestrischamps.herokuapp.com/view/LAYOUT_NAME/SECRET?bg=0
To produce frame into your own private room, visit https://nestrischamps.herokuapp.com/room/producer
To attach yourself as a producer to another user's room (typically the link will be passed to you as an invitation), the links will be of the form
https://nestrischamps.herokuapp.com/room/u/TWITCH_USERNAME/producer
To administer your competition room, visit https://nestrischamps.herokuapp.com/room/admin
OCR is supported in browser for both device capture and screen capture.
2 default game roms are supported:
Classic Tetris
The fields that need to be OCR-ed per rom are fixed (see highlighted areas above)
There is a built-in automatic calibrator but it doesn't work to well, so you should always ajust the areas selected for calibration to be as close as possible to the desired outcome.
In both cases, start a game at level 0 BEFORE you press the "Calibrate and Capture button". In Das trainer, pause as soon as the game starts click the button. In Classic Tetris, click as soon as the game starts. In both cases, keep your fingers crossed that the auto calibrator takes you close to the desired state, and then fine tune all the capture areas to be pixel perfect.
Once calibration and tuning has been done, the capture window and the browser tab MUST stay focused.
The capture area should "hug" the digits on top, right, bottom, left, (using 0 as a reference), like this:
Note that if you calibrate something that starts with a 1, the capture area should NOT hug the one on the left (notice the black strip on the left).

The are 3 colors to read: color1, color2, and color3. They should be read from the pieces stats on the left by selecting one block from the T piece, J piece, and Z piece.
The blocks should be chosen like this
The selection should not include any black border, but color1 should include the block's border. They should look like this
To calibrate the field capture, try to stack pieces on the left, right, and bottom, and even all the way up on the top-left and top-right.
Having done that, hug the capture on right, left, top, bottom. do not leave black borders at the bottom and right!, like this:
All layouts so far are 720p (1280x720), which is a good compromise of real estate vs. draw time and upload bandwidth requirements. But feel free to stretch the layout to fit a 1080p canva
The Browser Source setup should look like this:
In the admin panel, you get to see who is connected to the room, and select the desired producers as player 1 and player 2
The Name and Avatar are taken from Twitch data, but can be updated to suit.
The number of match to get to victory can change ("Best of" dropdown)
Each player has a heart control, the heart can be clicked to attribute victories.
The "Winner" button displays a little animation in the field to show the winner and loser of the match. Do NOT click it until both players have topped out! If the winning player is chasing a maxout or what not, wait till he/she is done before clicking.
Finally the "Clear Victories" button resets the victory for both players to 0, and stops the winner animation.
All captured frames are sent in binary and weight 568 bits (71 bytes) per frame. On a capture setup of 60fps, the game stream requirements are therefore 71*60 = 4,260 B/s (~4KB/s).
They have the format below.
Game fields may be null (like das trainer's instant das when sending classic frames), in which case the field's bits should all be set to 1.
| Purpose | Size | Description | |
|---|---|---|---|
| 1 | Version | 3 bits | Specify the version of the format of binary frame. Currently 1. |
| 2 | Game type | 2 bits | Specify the type of game the frame is for, so a parser may know which fields are expected to be null. So far: 1: CLASSIC - 2:DAS_TRAINER |
| 3 | Player number | 3 bits | Specify which player this frame is for. Producers are expected to leave this at 0. While the frame broker may set the number to player 1 (0), or 2 (1), or more when layouts can supports having more players. |
| 4 | Game ID | 16 bits | Starts at zero when producer starts. Increases by 1 at every game. |
| 5 | Client time | 28 bits | Number of milliseconds since producer connected. Range: ~74 hours |
| 6 | Score | 21 bits | Unsigned int. Range: 2,097,152 (221) |
| 7 | Lines | 9 bits | Unsigned int. Range: 512 |
| 8 | Level | 6 bits | Unsigned int. Range: 64 |
| 9 | Instant DAS | 5 bits | Unsigned int. Das needs to record 17 values (0 to 16) + null. |
| 10 | Preview | 3 bits | Represents the piece in preview as follow: 0:T, 1:J, 2:Z, 3:O, 4:S, 5:L, 6:I, 7:null |
| 11 | Current Piece DAS | 5 bits | Unsigned int. |
| 12 | Current Piece | 3 bits | Piece in current piece area of Das Trainer. Same encoding as Preview. |
| 13 | T count | 8 bits | Piece count for T piece |
| 14 | J count | 8 bits | Piece count for J piece |
| 15 | Z count | 8 bits | Piece count for Z piece |
| 16 | O count | 8 bits | Piece count for O piece |
| 17 | S count | 8 bits | Piece count for S piece |
| 18 | L count | 8 bits | Piece count for L piece |
| 19 | I count | 8 bits | Piece count for I piece |
| 20 | Field | 400 bits | 2 bits per block for the 200 blocks in the field. Starts from top-left and travels right-bottom. |
Below is the bit representation of the fields described above
See the source file for implementation details.
As with any software, there's always more... "More, more, more, more, more" as the GOAT would have said.
The list of TODO items is tracked as issues in the github project. Feel free to open feature requests and bug reports there. There's no ETA and guarantee on when anything might get done though, so patience is key :).


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$id = preg_replace("/\s/", "", strtolower($cat)) . "_" . $points;
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Fuglafjørður expands into steep surrounding hills from the bay. The town centre is close to the harbour and is equipped with most services and shops. The town centre has a cultural centre, which has become famous as one of the main cultural attractions to see in Eysturoy.
Location: 62°14'31"N, 6°48'41"W
This fjord is traditionally rated as a winter harbour. The harbour is very secure.
Berth on the N of the outer wall or, if less than 34ft, it may be possible to use one of the slips in the small boat marina.
There is a good anchorage at the head of the fjord.
Water and provisions are available here, also diesel by arrangement with the boatyard.


Stack Exchange, Inc. Official Privacy Policy |
|
|
Legally Useless Summary for Short Attention Spans. (Yes, you still have to read the real one on the right. Sorry, but you do.) |
Who We Are and What This IsThe Stack Exchange network is a set of Q&A sites dedicated to providing high-quality questions and answers, with the modest goal of making the Internet a better place. It is owned and operated by Stack Exchange Inc. |
| We really, truly care about your privacy. We may joke around, but we mean it. | We take the private nature of your personal information very seriously, and are committed to protecting it. To do that, we’ve set up procedures to ensure that your information is handled responsibly and in accordance with applicable data protection and privacy laws. We’re grateful for your trust, and we’ll act that way. |
| This will teach you what info we collect and how we use it. If you wanted to learn to play the keytar, you’re in the wrong place. | This privacy policy describes what information we collect when you visit the network, how we use that information, and what choices we offer you to access, update, and control it. This version of the policy is effective as of March 8, 2017. This policy may be revised in order to establish compliance with the forthcoming General Data Protection Regulation (GDPR). |
Privacy Shield Overview |
|
| We follow the strict Privacy Shield Framework that complies with the EU privacy requirements. | We have chosen to comply with the principles of the Privacy Shield Framework developed by the U.S. Department of Commerce in consultation with the European Commission except where limited by any legal, regulatory, ethical or public interest considerations. Covered entities include Stack Exchange, Inc., and Stack Exchange, Ltd. More information about the principles that make up the Framework, as well as other frequently asked questions relating to Privacy Shield can be found at: https://www.privacyshield.gov/welcome. Stack Exchange is subject to the investigatory and enforcement powers of the Federal Trade Commission / Department of Transportation. |
Types of Information |
|
| “Personal” information can potentially identify who you are. | “Personal information” is any information that we could use to identify an individual. It does not include personal information that is encoded or anonymized, or publicly available information that has not been combined with non-public information. |
| “Sensitive” information can identify specific private attributes, such as ethnicity, health info, criminal history, or trade affiliations. | “Sensitive personal information” is information that meets the “personal information” criteria and also a) reveals race, ethnic origin, political opinions, religious or philosophical beliefs, trade union membership, or b) concerns health or sex life, information about social security benefits, or information on criminal or administrative proceedings other than in the context of pending legal proceedings. |
How We Collect Information |
|
| We collect information two ways: Information we get from your use of the network, and information you provide to us directly. | |
| Your web browser tells us stuff like your approximate location and how you use the site. It also bakes us yummy cookies. | Information we get from your use of the network is primarily non-personally- identifying information of the sort that web browsers, servers, and services like Google Analytics* typically make available, such as the browser type, language preference, referring site, and the time of each visit. Other non-identifying information that we might have access to includes how you use the service (e.g., search queries), your approximate location, cookies, etc. |
| We try to use this non-personal info to help make better Q&A sites, and to destroy spam. We eat the cookies. | We collect this non-personally identifying information in order to better understand how visitors use the service and where possible, to improve their experience. For instance, we may monitor the most common content on the network to help identify spam. In some cases, we may publicly display information that is not personally identifying in the aggregate, (e.g., by publishing a report on trends in the usage of the network,) or may provide it to third parties for educational or similar purposes other than for sale or profit. |
| Your browser also gives us your IP address, which could identify you, but we don’t use it to do that. For real. | When you use the network, we also collect potentially personally identifying information in the form of Internet Protocol (IP) addresses. But we don’t use that information to identify you, and we handle and disclose these addresses in the same way we handle other potentially personally identifying information as described below. |
| If you register an account, you may need to give us your email and other personal info, but we’re not the boss of you and can’t make you. | Information you provide to us directly. Certain visitors to the network choose to interact with it in ways that may require them to provide us with personally identifying information. The amount and type of information that is provided depends on the nature of the interaction. For example, we ask visitors who sign up for stackoverflow.com to provide a username and email address. Employers who engage in financial transactions with talent.stackoverflow.com are asked to provide additional information, such as the personal and financial information required to process those transactions. We use a payment gateway to protect financial information we collect online and secure payment processors to carry out financial transactions. We only collect as much information as is necessary or appropriate given the type of interaction. We do not disclose personally identifying information other than as described below. And you can always refuse to supply personally identifying information, with the caveat that it may prevent you from engaging in certain activities. |
| The non-identifying content of a service request may be made public. You want to help, don’t you? | If you send us a request, such as emailing us for support, we reserve the right to publish it (absent any personally identifying information) in order to help us clarify or respond to your request or help other users. |
| If you don’t like cookies or have other dietary restrictions, please tell your browser. | A cookie is a string of information that a website stores on a visitor’s computer, and that the visitor’s browser provides to the website each time the visitor returns. We use cookies to help us track visitors’ use of the network and their preferences. If you do not wish to have cookies placed on your computer, you should set your browser to refuse cookies, but should be aware that certain features of the network may not function properly without them. |
| Our servers live in the United States. So, if you send us your info, that’s where it’s going. | If you are outside the United States, you should know that any personally identifiable information you enter into the network will be transferred out of your country and into the United States, and possibly to other countries. By using the network, you consent to such transfer, and are representing that you have the right to transfer such information outside your country. |
| If you’re under 13, we want to mind our own business, not yours. | We do not knowingly collect any personally identifiable information from children under the age of 13. If you believe that a child has provided us with personally identifiable information without the consent of his or her parent or guardian, please contact us at<EMAIL_ADDRESS>If we become aware that a child under age 13 has provided us with personally identifiable information, we’ll delete it. |
Information You Choose to Display Publicly on the Network |
|
| If you decide to post personal information in the public parts of our sites, it’s… um, public. | Some users may elect to publicly post personally identifying or sensitive information about themselves in their normal use of the network. This could occur through use of the optional profile fields, in question or answer posts, or when an individual posts a job history on the Jobs site. Information like that, which is voluntarily posted in publicly visible parts of the network, is considered to be public, even if it would otherwise be considered to be personally identifying or sensitive. As such, it is not subject to the protocols listed below, because we don’t control it; you do. Additionally, voluntarily publicizing such information means that you lose any privacy rights you might normally have with regards to that information. It also increases your chances of receiving unwanted communications, like spam. |
Information You Give to Other People |
|
| We’re not responsible for any information you give other websites we link to. Sort of like how your TV maker isn’t responsible if you buy a lousy product, even if you saw it in an awesome commercial. | This Policy only applies to information collected by Stack Exchange. It does not apply to the practices of companies that we don’t own or control, or employees that we don’t manage. The network contains links to third party websites, and any information you provide to those sites will be covered by any privacy policies they may have. Please be sure to read the privacy policies of any third-party sites you visit. It is those sites’ responsibility to protect any information you give them, so we can’t be held liable for their wrongful use of your personally identifying information. |
How We Use Information We Collect |
|
| We will tell you what we’re collecting, what we’re doing with it, and when we might share it with others. (Almost never, unless you ask us to.) | Notice – Notice is what this Policy that you’re reading is all about. You are reading it, right? It’s important! When we collect your personal information, we’ll tell you how we’re using it, any types of third parties to which we might disclose it, (other than moderators or “agents,” such as vendors or contractors, who are only processing such information for us or at our direction), and the choices we offer you to limit the use of your information. |
| We’ll tell you all this stuff as soon as you register. | Notice will be provided in clear and conspicuous language when you are first asked to provide us with personal information, or as soon as practicable thereafter, and we’ll notify you before we use the information for something other than the purpose for which it was originally collected. If anything in this Policy seems unclear, please don’t hesitate to contact us at<EMAIL_ADDRESS>so we can address your question and possibly clarify this document. |
| If we change this policy, we’ll update this document to keep you in the loop. | Although most changes are likely to be minor, we may occasionally need to change this Policy. If we do update it, we’ll notify you either by posting the new policy on the network or by emailing you the changes or a link to the modified document. (See the “Choice” section below for information about how we’ll notify you if we change our policy regarding sensitive information.) In any case, the way we use information you provide will be covered by the privacy policy that was in effect at the time it was collected. |
| We mostly use your information to customize and improve your (and others’) experience. |
Here are some of the ways we may use personal information you provide us:
|
| Choice – Choice is all about making sure you have the ability to control how we share your personal information with others. We want you to be in control of your own data disclosure. To that end, we allow anonymous and pseudonymous participation, allow you to disable several features from public share settings, and to personalize your data features and share settings at: https://stackoverflow.com/users/prediction-data. We almost never share any of your personal information with non-agent third parties, with one exception, where you basically are asking us to do so: | |
| If you post a profile on Jobs, employers can see your name, and if you apply for a job, we give them your contact info. (Because they can’t hire you if they can’t contact you.) |
Users who post profiles on our Jobs site are generally doing so for the express
purpose of getting connected with potential employers. So, if you post a profile
on our Jobs site, and choose to make your profile visible to employers, your
name (which is required) and most of the other (optional) information in your profile
will be visible to employers searching for candidates. That said, your contact information
(email, phone, and address) will not be provided to employers in their candidate
searches. We will only allow employers to have access to your contact information
in two cases, both of which are under your control:
|
| Outside of when you apply for job listings, we don’t share your personal info with anyone. That could theoretically change in a merger, etc. but the buyer would still be bound by these rules. | Other than on Jobs, we won’t share your personal information with non-agent third parties unless we are required to do so by law, or if we believe in good faith that disclosure is reasonably necessary to protect our property, rights or those of third parties or the public at large. It is possible that we may, on occasion, buy or sell assets from or to other companies. If that should occur, user information is typically one of the assets that get transferred. Similarly, if Stack Exchange or most of its assets were acquired, or in the unlikely event that we go out of business or enter bankruptcy, user information could be transferred or acquired. You should be aware that such events can occur, and that if it does, the buyer may continue to use your personal and non-personal information, but only as set forth in this policy. Other than in these rare circumstances, Stack Exchange will not rent or sell potentially personally identifying information to anyone. |
| In the unlikely event that we should need to collect and transfer your sensitive information, we’ll ask first. | It’s hard to imagine that we would ever consider collecting, let alone sharing, sensitive information with a non-agent third party, but if such a day should come, we will first give you the opportunity to explicitly consent (opt-in) to such disclosure or to any use of the information for a purpose other than the one for which it was originally collected or previously authorized. |
| If you give us your email, we may email you. But probably not very often. We’re busy, too. | If you are a registered user of the network and have supplied your email address, we may occasionally send you an email to tell you about new features, solicit your feedback, or just keep you up to date with what’s going on with the network. We generally use the network to communicate this type of information, so we expect to keep this type of communication to a minimum. If we do send you information that you did not expressly request, we will provide you with a way to request that you don’t get any similar notices (opt-out). |
| Anyone that has access to your info will be required to treat it like we do. |
Onward Transfer – Prior to providing agents with any personal information,
we will obtain assurances that they will safeguard it in accordance with this policy.
Examples of assurances that may be provided include:
|
| In the unlikely event that we should discover that an agent is using personal information in way that conflicts with this policy, we will take all reasonable steps to stop them immediately. | |
| In cases of onward transfer to third parties of data of EU and Swiss individuals received pursuant to the EU-US Privacy Shield, Stack Exchange remains liable. | |
| We promise to work hard to keep your info safe, and to restrict who can access it. | Security – All records containing personal or financial information are considered to be our property and are afforded confidential treatment at all times. We work hard to protect against the unauthorized access, use, alteration or destruction of personal or financial information. All such electronic information is stored on restricted database servers, and is generally kept until such time as you may ask us to edit or delete it, as described below. We only disclose such information to our employees, agents or affiliates that a) need to know that information in order to process it for us or to provide other services, b) have agreed not to disclose it to others, and c) in response to lawful requests by public authorities, including to meet national security or law enforcement requirements. |
| We want to keep your data accurate and up to date, so… | Data Integrity – In addition to assuring you that we will protect your personal information, we also want to make sure that it is reliable, accurate, and up-to-date. In order to do that, we provide: |
| …we’ll provide it to you to review. Within reason. | Access – Upon request, we will provide you with reasonable access to the personal information we collect about you. You will have the opportunity to correct, update, modify or delete this information by sending an e-mail to<EMAIL_ADDRESS>Please note that some information may remain in our records even after you request deletion of your information as permitted by the Privacy Shield Principles. Additionally, there may be limits to the amount of information we can practically provide. For example, we may limit an individual’s access to personal information where the burden or expense of providing access would be disproportionate to the risks to the individual’s privacy or where doing so would violate others’ rights. |
| Enforcement – We will conduct internal audits of our compliance with this privacy policy, including an annual self-assessment. Our employees take your privacy as seriously as we do, and we will take all reasonable measures against any employee found to be in violation of this policy. | |
| If you have any concerns about your privacy, we genuinely want to know about it. | In compliance with the Privacy Shield Principles, Stack Exchange, Inc. and covered affiliates and subsidiaries commit to resolve complaints about our collection or use of your personal information. EU and Swiss individuals with inquiries or complaints regarding our Privacy Shield policy should first contact us (Stack Exchange, Inc.) at<EMAIL_ADDRESS>|
| In the really, really, super-unlikely event that we can’t help, you can contact PrivacyTrust. | Stack Exchange, Inc. has further committed to refer unresolved Privacy Shield complaints to the PrivacyTrust Shield Program, an alternative dispute resolution provider located in the United Kingdom. If you do not receive timely acknowledgment of your complaint from us, or if we have not addressed your complaint to your satisfaction, please contact or visit https://www.privacytrust.com/drs/stackexchange OR PrivacyTrust, Communications House, 26 York Street, London, W1U 6PZ, for more information or to file a complaint. The services of PrivacyTrust Privacy Shield Program are provided at no cost to you. |
| Alternatively, if you are unhappy with how we deal with your complaint, or the outcome of our resolution, you may by right invoke binding arbitration or refer your complaint to a data panel. | |
How to Contact Us |
|
| We’re here if you need us. | If you have any questions about this policy or our site in general, please contact us at<EMAIL_ADDRESS>|
| Our Data Protection Officer is Adam Francoeur. | |
| Who writes letters? Like with stamps and stuff? Ugh. |
Written Inquiries can be sent to:
Stack Exchange, Inc. |
Employees’ & Prospective Employees’ Information |
|
|
Working here rocks. We have insanely great health insurance, reimburse employees’
gym membership, and give employees free |
In accordance with the Privacy Shield principles, Stack Exchange, Inc., commits to cooperate with EU Data
Protection Authorities (DPAs) and comply with the advice given by such authorities with regard to human
resources data transferred from the EU in the context of the employment relationship.
This section covers any ways in which personal information we collect from employees or applicants might be treated differently than user information. You can probably stop here if you not an employee or interested in applying for a job with Stack Exchange. But maybe you should be interested: Who wouldn’t want to work with an amazingly talented team dedicated to making the Internet a better place to get expert answers to questions, especially at a company with free lunches, top-notch benefits, and a CEO who has literally written the book on how to make great workplaces for building amazing software. The more I think about it, the more I think maybe you should click here after all: https://stackexchange.com/about/hiring. And if you do, be sure to review the following non-comprehensive list of ways that we may use information provided to us by employees or applicants: |
|
If you do work or apply to work here, here’s how we handle your personal information.
The lawyers say I have to remind you again that you really need to read the long version on the right. Which hurts my feelings a little, but is still probably good advice. |
|
| * Google Analytics is a registered trademark of Google, Inc. |


mgmt/tm/security/antiFraud/profile/mobilesafe
This object has the following members.
Properties
| Name | Type | Default Value | Required | Access | Description |
alertThreshold | integer | 25 | optional | read/write | Specifies the minimal score for sending alerts from mobile devices. |
Associated Arrays and Lists
| Property Name | Type | Default Value | Required | Access | Description |
appIntegrity | string | | optional | read/write | |
malware | string | | optional | read/write | |
mitm | string | | optional | read/write | |
osSecurity | string | | optional | read/write | |
rootingJailbreak | string | | optional | read/write | |
Copyright © 2015 F5 Networks. All Rights Reserved.


Abide: Hidden and Ignored Fields
This form has a hidden field and a required text field.
Errors should be displayed properly.
This form has a required text field and an ignored field that is ignored after page load.
The ignored field should be ignored.


Control Panel
There is no settings or controls for Comment Uploads in the ExpressionEngine control panel. However, there's a few things you may be interested in knowing about:
File Upload Preference Creation
Upon installation/enabling of the Comment Uploads extension, it attempts to create a folder called comments in the ./images/uploads directory (if it has not yet been created), as well as a new File Upload preference called Comment Uploads Directory. This becomes the default upload directory for all of your comment uploads, unless otherwise specified in your Comment Form.
Deleting Entries and/or Comments
Comment Uploads does NOT orphan uploaded files or data in your database. Comment Uploads uses the following processes:
- Upon deletion of an individual comment, the related files are deleted from the server, and the related data is removed from the database.
- Upon deletion of an individual entry, the related files of all comments are deleted from the server, and the related data is removed from the database.
NOTE: disabling of the Comment Uploads extension does NOT delete any of the uploaded files, but DOES delete all of the comment upload data from the database.


Card Name
Merchant Type
Merchant Name
Reward Type
Reward Value
Reward Start Date
Reward End Date
Reward Note


namespace Doctrine\DBAL\Schema\
Namespaces
Interfaces
-
Constraint
Marker interface for constraints.
Classes
-
Column
Object representation of a database column.
-
AbstractAsset
The abstract asset allows to reset the name of all assets without publishing this to the public userland.
This encapsulation hack is necessary to keep a consistent state of the database schema. Say we have a list of tables
array($tableName => Table($tableName)); if you want to rename the table, you have to make sure -
TableDiff
Table Diff.
-
ColumnDiff
Represents the change of a column.
-
Table
Object Representation of a table.
-
ForeignKeyConstraint
An abstraction class for a foreign key constraint.
-
Index
-
Schema
Object representation of a database schema.
Different vendors have very inconsistent naming with regard to the concept
of a "schema". Doctrine understands a schema as the entity that conceptually
wraps a set of database objects such as tables, sequences, indexes and
foreign keys that belong to each other into a namespace. A Doctrine Schema
has nothing to do with the "SCHEMA" defined as in PostgreSQL, it is more
related to the concept of "DATABASE" that exists in MySQL and PostgreSQL.Every asset in the doctrine schema has a name. A name consists of either a
namespace.local name pair or just a local unqualified name.The abstraction layer that covers a PostgreSQL schema is the namespace of an
database object (asset). A schema can have a name, which will be used as
default namespace for the unqualified database objects that are created in
the schema.In the case of MySQL where cross-database queries are allowed this leads to
databases being "misinterpreted" as namespaces. This is intentional, however
the CREATE/DROP SQL visitors will just filter this queries and do not
execute them. Only the queries for the currently connected database are
executed. -
Sequence
Sequence structure.
-
SchemaException
-
Identifier
An abstraction class for an asset identifier.
Wraps identifier names like column names in indexes / foreign keys
in an abstract class for proper quotation capabilities. -
AbstractSchemaManager
Base class for schema managers. Schema managers are used to inspect and/or
modify the database schema/structure. -
View
Representation of a Database View.
-
SchemaConfig
Configuration for a Schema.


by [[question.owner_name]]
[[question.question_analytic.likes]] [[question.question_analytic.views]] Posted on [[question.created_on | date:'medium']]
[[question.description]]


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We make sure you recieve your trombone as soon as we have finished making it. We also provide free returns if you are not satisfied.
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This example demonstrates:
- The animation of spring and damper components
- A body can be freely moving without any connection to a joint.
In this case body coordinates are used automatically as states
(whenever joints are present, it is first tried to use the
generalized coordinates of the joints as states).
- If a body is freely moving, the initial position and velocity
of the body can be defined with the "Initialization" menu as shown
with the body "body1" in the left part (click on
"Initialization").
Generated at 2019-01-25T16:44:03Z by OpenModelica 1.14.0~dev-130-gefa44fb


Welcome to CiS!.
Go to downloads page CiS (Communications Infrastructure Services) comprises a large network of staff, associates and partners with a home base in Australia, providing network design, integration, specialist technical knowledge and project management, working with live ICT networks in the Asia Pacific Region.
We provide high value wireless and broadband consultancy services, and nationally has supplied over 2,000 fibre design services for backbone, GSM connect and customer connections, including surveys, drafting and environmental work, along with project management and quality control of contracted constructors


Trainee
Trainer
Who Are We?
Bringing top notch fitness trainers to you
Our Trainers
Experienced and Certified
Display trainers here!
Find trainers near you
Contact Us
Email
Construct contact form here!


A tree can be added into a sheet. To do so, there are two steps which must be done.
First, the value
attribute of the sheet must refer to a method, which return a tree instead of a list.
Second, to display the tree, use the <tc:columnNode/>
tag.
Tag Library Documentation:
There is a tree in the first column. You can expand and collapse the items.
The <tc:columnNode/>
tag can contain several tags for a tree.
In this example, it's a <tc:treeIndent/>
to intent the
single entries of the tree.


This package contains the SelectionGroup inheritance hierarchy and Iterators, which wrap the data structure holding all existing levels in a game and allow for multiple implementations (such as a List or a Graph).


German Quiz 4 - Food
Welcome to the German food quiz! You will be asked a question, and you must select the correct answer.
Welcome to the German food quiz! You will be asked a question, and you must select the correct answer.
Question 1. What is the German word for the food "fish"?.
Question 2. What is the German word for the food "chicken"?.
Question 3. What is the German word for the food "sausage"?.
Question 4. What is the German word for the food "raspberry"?.
Question 1: The correct answer was 1 - Fisch.
Question 2: The correct answer was 4 - Hähnchen.
Question 3: The correct answer was 1 - Wurst.
Question 4: The correct answer was 3 - Himbeere.
You answered all German food questions correctly, well done!


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