Halo - The Weather App ¶
Halo is a weather app written in python. You can quickly view the weather in your city and checkout the forecast and historic temperature trends.
Prerequisites¶
- Python 3
- Pip
Installation¶
Usage¶
After installing it, you can directly launch it either by searching for Halo among your installed apps, or from terminal by running
halo
Running directly from Source¶
You can directly run this code without the need of installing anything into your system. First, you will need to install the dependencies manually by running
pip3 install -r requirements.txt
Then run the python module by executing
python3 -m halo


It’s the first full week of the new year, and we’re slowly getting back to normal around here. This week, we’re highlighting terrific contributions from the Blog, Tutorials, Analysis, Bug Hunting, and Anti-abuse categories. These staff picks are all great examples to learn from.
Staff Picks
Proof-of-Brain or Power-of-Bid(bot), that is the question. by @lostmine27 [analysis]
The Steem blockchain is one of the largest and most used blockchains worldwide today. Many dApps have been successfully launched on this blockchain and more are still under development. This contribution gives a detailed analysis of the bidbot business on the blockchain. Not only is this detailed, but also very descriptive, and the data is presented in such a way that even a non-analyst could read and understand. It is rare to get a staff pick on the analysis category but this one is well worth being picked.
Total payout: 62.56 STU Number of votes: 163
The Steepshot series: Features of Steepshot Cont’d (Episode 7) by @curtwriter [blog]
@curtwriter is one of the backbones of the Blog category, providing consistent quality in his work, doing his research, and creating a knowledge base about the various dApps on the blockchain. This is his 7th post about Steepshot, in which he goes deep about three features of the app. Any contributor to the category can learn from his dedication and hard work, and continued drive to improve.
Total payout: 31.25 STU Number of votes: 54
How to set up and use multisignature accounts on Steem Blockchain. by @stoodkev [tutorials]
Beautiful write up by @stoodkev, tackling the task request proposed by @timcliff for a “Multisignature Transaction Guide” with a related bounty. The author takes us through the steps in performing such functionality on the Steem blockchain while relying on dsteem JS library, allowing multiple ownership and approvals to conduct an action on a given account. Well established steps, references, as well as screenshots and proof of results are at the core of this well-written tutorial. If interested in giving Multisig a try on Steem, we recommend you check this tutorial out.
Total payout: 119.51 STU Number of votes: 1093
[condenser_api][0.20.4-8] voting_power is set to zero for users who haven’t voted more than 5 days by @blockchainstudio [bug-hunting]
This is a very detailed and informative report made by @blockchainstudio to the Steem blockchain. The user did not only reported the error but also went further to share the root cause of the bug and made a PR to fix the bug. This was a critical bug, and the fix immediately got merged into the project. We really appreciate reports like this, and we hope to see more of this.
Total payout: 35.25 STU Number of votes: 93
Introducing !sources by @themarkymark [anti-abuse]
The anti-abuse category aims to fight and guide any form of abuse in the open source world, especially on the Steem blockchain. This contribution by @themarkymark is an effort to help guide plagiarists away from plagiarising contents or users who do not cite their publications properly on the Steem blockchain. The guide is in the form of a bot which could be triggered by any curator who wants to help an author improve their blogging experience.
Total payout: 97.92 STU Number of votes: 295
Utopian.io Post Statistics
The staff picked contributions are only a small (but exceptional) example of the mass of contributions reviewed and rewarded by Utopian.io.
- Overall, the last week saw a total of 150 posts, with 114 of them rewarded through an upvote by @utopian-io.
- In total, Utopian.io distributed an approximate of 3592.08 STU to contributors.
- The highest payout seen on any Utopian.io contribution this week was 157.83 STU, with a total of 1154 votes received from the community.
- The contribution that attracted the most engagement was Task Development: Help Us Add ‘Refine Search’ Capability To The steemgigs.org Search & Other Tasks., with no less than 16 comments in its comment threads.
- The average vote given by Utopian.io was worth 31.51 STU.
Category Statistics
|Category|Reviewed|Rewardable|Rewarded|Total rewards|Top contributor| |:-|:-|:-|:-|-:|:-| |translations|47|47|33|1099.97 STU|@aafeng| |analysis|5|4|4|176.46 STU|@lostmine27| |iamutopian|9|9|9|403.57 STU|@didic| |development|31|27|19|780.22 STU|@raycoms| |tutorials|13|11|11|319.90 STU|@igormuba| |blog|26|24|24|563.44 STU|@igormuba| |ideas|6|2|2|27.73 STU|@blockchainstudio| |video-tutorials|1|1|1|17.36 STU|@alexendre-maxim| |bug-hunting|6|6|5|76.79 STU|@blockchainstudio| |graphics|3|3|3|70.78 STU|@munadikiehl| |anti-abuse|1|1|1|49.24 STU|@themarkymark|
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及时清理不再使用的代码段或配置信息。
说明：对于垃圾代码或过时配置，坚决清理干净，避免程序过度臃肿，代码冗余。
Examples:
Positive example: For codes which are temporarily removed and likely to be reused, use /// to add a reasonable note. public static void hello() { /// Business is stopped temporarily by the owner. // Business business = new Business(); // business.active(); System.out.println("it's finished"); }


Research Methods for Global Studies
Class 5: Quantitative Analysis in Action
Abelardo Gómez Díaz
Understanding Migration Patterns
Evaluating Migration Policy
Irregular Migration to EU
- Increased irregular migration to EU since 2014
- Over 1 million people crossed Mediterranean to Europe during 2015; over 3,770 died trying
- EU response has been mostly enforcement, with EU military operation in Southern Central Mediterranean and NATO operation in Eastern Mediterranean
- In fall 2015 ESI proposes a deal to get Turkey to accept rapid return of all refugees attempting to enter Greece through irregular channels.
- EU-Turkey deal announced in March 2016. Aim is to "break the business model of the smugglers" by reducing demand while also increasing costs through enforcement.
Where will this lead?
What can we learn from past experience?
Irregular Migration to US
Did undocumented migration from Mexico to US increase due to changed individual behavior?
How did US policy change from 1970 to present?
What explains these changes in US policy?
What effects did US policy have on migration patterns?
How US Enforcement Backfired
Background
- What has been the stated goal of US enforcement policy?
- What has been the actual motivation?
Background
- How do Massey, Durand, and Pren articulate theory?
- Social psychology and policy entrepreneurs
- Complex systems and unintended consequences
- Theories of migration
Data
- Where does the data come from?
- How was it collected?
- How is it structured?
Analysis
- What is analytical approach?
- Why logit models?
- Why Tobit model for costs?
- Should we worry about reverse causation?
Analysis
- Did policy achieve stated goal?
- Did it increase costs of undocumented migration?
Analysis
- What drove the observed decrease in undocumented migration from Mexico?
- What were results of enforcement policy?
Linking quantitative analysis with policy
What have US policymakers learned from this?
What should EU policymakers learn from this?
What are the limits of quantitative approach here?


Wordlish analyses your text for word frequency, and compares it to the top 6000 most-used words [1], with some re-balancing for fiction. This works best with large bodies of text.
High 'Relative to Typical' results might not necessarily indicate that you should cull those words, because the 'typical' database corpus might not be aligned to your genre and writing intent. If your text contains dialogue, then characters might be speaking with their own biases.
Version 1.11, created by John Valentine. Donate to support software like this.
All your text is processed in-browser, is not sent over the network, and is not stored by this website. We have chosen to openly package the code on this page, for data transparency purposes.
[1] BNC database and word frequency lists, retrieved 2019-03-15.


mongoc_client_pool_t
Connection pooling abstraction
Synopsis
typedef struct _mongoc_client_pool_t mongoc_client_pool_t
mongoc_client_pool_t is the basis for multi-threading in the MongoDB C driver. Since mongoc_client_t structures are not thread-safe, this structure is used to retrieve a new mongoc_client_t for a given thread. This structure is thread-safe.
Example
#include <mongoc.h>
static void *
worker (void *data)
{
mongoc_client_pool_t *pool = data;
mongoc_client_t *client;
do {
client = mongoc_client_pool_pop (pool);
/*
* Do something with client. If you are writing an HTTP server, you
* probably only want to hold onto the client for the portion of the
* request performing database queries.
*/
mongoc_client_pool_push (pool, client);
} while (!inShutdown);
return NULL;
}
int main (int argc, char *argv[])
{
mongoc_client_pool_t *pool;
mongoc_uri_t *uri;
pthread_t thread[10];
unsigned i;
void *ret;
mongoc_init ();
uri = mongoc_uri_new ("mongodb://mdb1.example.com/?minPoolSize=16");
pool = mongoc_client_pool_new (uri);
for (i = 0; i < 10; i++) {
pthread_create (&thread, NULL, worker, pool);
}
mongoc_uri_destroy (uri);
for (i = 0; i < 10; i++) {
pthread_join (threads [i], &ret);
}
mongoc_cleanup ();
return 0;
}


You have {{authentication2faInformation.recoveryCodesCount}} recovery code{{authentication2faInformation.recoveryCodesCount > 1 ? 's' : ''}} left.
You must generate a new set of recovery codes before you can log in with a recovery code.
0">
You can generate a new set of recovery codes.


| Library: | Gates |
| Introduced: | 2.0 Beta 1 |
| Appearance: |
The buffer simply passes through to its right output whatever input it receives on the left side. The truth table for a one-bit buffer is the following.
| x | out |
|---|---|
| 0 | 0 |
| 1 | 1 |
If the input is unspecified (i.e., floating), then the output will also be unspecified - unless the "Gate Output When Undefined" option is "Error for undefined inputs," in which case the output is an error. If the input is an error value, then the output will also be.
Buffers are the most useless of the gate components provided in Logisim; its presence in the Gates library is just as much a matter of completeness (a component for each possible one-input truth table) as it is a matter of providing useful functionality. Still, it can be occasionally useful to ensure that values propagate in only one direction along a wire.
When the component is selected or being added,
Alt-0 through Alt-9 alter its Data Bits
attribute
and the arrow keys alter its Facing
attribute.
floating) value instead. This allows wired-or and wired-and connections, as illustrated in the AND/OR/NAND/NOR Gate documentation.
None.
Allows the label associated with the gate to be edited.


{% extends "caproy/base.html" %} {% block title %}Capture Royale{% endblock %} {% block content %}
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| DiscreteWavelets Toolbox |
Audio file names
a = AudioNames()
a = AudioNames() returns the absolute paths of each audio file included in the DiscreteWavelets Toolbox.
You can use AudioNames to easily access audio files included with the toolbox. It doesn't matter where you initially placed the DiscreteWavelets folder - as long as you did not rename it, AudioNames will find its location and return absolute path names to the audio files.
The following commands
a=AudioNames(); %Load all audio files that come with the toolbox in cell array a sndfile = a{2} %Shows the name of the audio file
produces (on my computer)
C:\Program Files\MATLAB\R2007b\toolbox\DiscreteWavelets\Sounds\bark.wavNow use standard Matlab commands to load and play the file.
[y, Fs] = wavread(sndfile); %Read the sound file sound(y,Fs); %Play the sound file
| AudioList | BWT1D1 |
© 2007-2008 Patrick Van Fleet


Linux is the best-known and most-used open source operating system. As an operating system, Linux is software that sits underneath all of the other software on a computer, receiving requests from those programs and relaying these requests to the computer’s hardware.
->Linux. It’s been around since the mid ‘90s, and has since reached a user-base that spans industries and continents. For those in the know, you understand that Linux is actually everywhere. It’s in your phones, in your cars, in your refrigerators, your Roku devices. It runs most of the Internet, the supercomputers making scientific breakthroughs, and the world\'s stock exchanges. But before Linux became the platform to run desktops, servers, and embedded systems across the globe, it was (and still is) one of the most reliable, secure, and worry-free operating systems available.


{% extends "base.html" %} {% block title %} Hide your email address | Mailhide {% endblock %} {% block page_title %} Mailhide {% endblock %} {% block content %}
Hide your email address now, just enter it below for your custom url.
Nice work! Let's keep a step ahead of the spammers. Here's your info:
This is an example link that opens a small window with your hidden address
Try it out:
Copy the code:


ERROR 403
This user {{email}} has already been used. You can try again from the
Sign Up page
Made by team SSP.


Introduction¶
Welcome to the Groovin’ Mod Framework Documentation! Here, you’ll find some useful resources that’ll get you in the groove of utilizing the framework as well as some additional information about this “mod template.”
About¶
Groovin’ is a starting template for mods that focuses on ease-of-use and organization. It is not an engine by itself, but it comes bundled with toggleable mods that polish some of the original game’s systems, such as Groovin’ Input, and add more functionality to the game, such as Razer Chroma support. It was originally made by 4mbr0s3 2 as a test to decouple “mod” code from the original game’s code, and Bopeebo Rumble was a test for this workflow.
Goals¶
Two main goals for the project are to decouple user mod code from the original game and to facilitate porting mods into future versions of Friday Night Funkin’. Edits to the original game’s code should be kept to a minimum in order to make porting to future FNF versions easier.
Open / Closed Principle is Key¶
Groovin’ attempts to follow the Open / Closed Principle as closely as possible, which means that it attempts to allow modding functionality without making it necessary for mods to directly modify the source code. By structuring the framework this way, it becomes easier to port into newer versions of Friday Night Funkin’ since the original source has not changed significantly. However, it may be more difficult to modify already existing game elements with Groovin’ since user code is meant to be executed outside of the game’s original code.
For instance, mods made in Kade Engine or Project FNF can very easily change the color of the health bar through parameter or variable changes to PlayState.hx
, but, with Groovin’, mods should change the health bar’s color by calling FlxBar.createFilledBar()
after the initialization of it rather than changing the original code directly.
In summary, modding existing game systems with Groovin’ can be quite difficult compared to other engines since modifying the source directly is discouraged. However, following SOLID principles and separating mod code from the original game’s code can significantly declutter mod projects and make programming more agile.
FAQ¶
Will this project be prepared for when the full-ass game comes out?
We (I) have no idea.
Is it Groovin’ or Groovin?
Either one works.


:pear:
— Iterating Over Arrays:pear:
provides an easy way to iterate over arrays. :pear:
works only on arrays, and will issue an error when you try to use it on a variable with a different data type or an uninitialized variable. The syntax is:
:pear: variable array_expression
statements
:indian:
On each iteration, the value of the current element is assigned to variable. Example:
:custard: todolist :honey: :abc:Buy Apples:abc: :abc:Talk to Tim:abc: :abc:Visit Grandma:abc: :doughnut:
:pear: item todolist
8) :dog: :abc:On your todolist is: :abc: item :dog:
:indian:


User stories:
1) I can get the image URLs, alt text and page urls for a set of images relating to a given search string.
2) I can paginate through the responses by adding a ?offset=2 parameter to the URL.
3) I can get a list of the most recently submitted search strings.
[{"url":"http://data.whicdn.com/images/17561072/large.jpg","snippet":"Maybe I eat all the","thumbnail":"https://encrypted-tbn0.gstatic.com/images?q=tbn:ANd9GcQCO7BmkKUwgNi-4qSy3wwgbhQA0ZYY0Qs-U0wS5cX3koIGU2fRP6k_BEU","context":"http://weheartit.com/entry/group/6330716"},{"url":"http://funnypicturesimages.com/images/image/lolcats-funny-pictures-leroy.jpg","snippet":"funny animal picture - Buscar","thumbnail":"https://encrypted-tbn0.gstatic.com/images?q=tbn:ANd9GcS4q44VPxEUj9xcWvPXfuRnj9VMuTIvdrWQL3SsKpjnOrjA3uI7lsWy86w","context":"http://weheartit.com/entry/group/607840"}]
/latest/imagesearch/
[{"term":"lolcats funny","when":"2016-03-13 22:48:12.129481"},{"term":"lolcats funny","when":"2016-03-13 22:44:39.564474"}]


This sample simulates the behavior of moving files/folders of known apps like dropbox or google drive:


Gets local groups.
Get-Group [[-Name] <String>] [<CommonParameters>]
Get-Group
gets all local groups or a specific group by its name.
The objects returned, DirectoryServices.AccountManagement.GroupPrincipal
, use external resources, which means they don't clean up propertly when garbage collected, resulting in memory leaks. You should call Dispose()
on the objects you receieve from this function when you're done using them so these external resources can be cleaned up correctly.
Get-Group
is new in Carbon 2.0.
| Name | Type | Description | Required? | Pipeline Input | Default Value |
|---|---|---|---|---|---|
| Name | String | The name of the group to return. |
false | false |
Get-Group
Demonstrates how to get all local groups.
Get-Group -Name RebelAlliance
Demonstrates how to get a specific group.


In this project, you'll use generative adversarial networks to generate new images of faces.
You'll be using two datasets in this project:
Since the celebA dataset is complex and you're doing GANs in a project for the first time, we want you to test your neural network on MNIST before CelebA. Running the GANs on MNIST will allow you to see how well your model trains sooner.
If you're using FloydHub, set data_dir
to "/input" and use the FloydHub data ID "R5KrjnANiKVhLWAkpXhNBe".
data_dir = './data'
# FloydHub - Use with data ID "R5KrjnANiKVhLWAkpXhNBe"
#data_dir = '/input'
"""
DON'T MODIFY ANYTHING IN THIS CELL
"""
import helper
helper.download_extract('mnist', data_dir)
helper.download_extract('celeba', data_dir)
show_n_images = 25
"""
DON'T MODIFY ANYTHING IN THIS CELL
"""
%matplotlib inline
import os
from glob import glob
from matplotlib import pyplot
mnist_images = helper.get_batch(glob(os.path.join(data_dir, 'mnist/*.jpg'))[:show_n_images], 28, 28, 'L')
pyplot.imshow(helper.images_square_grid(mnist_images, 'L'))
The CelebFaces Attributes Dataset (CelebA) dataset contains over 200,000 celebrity images with annotations. Since you're going to be generating faces, you won't need the annotations. You can view the first number of examples by changing show_n_images
.
show_n_images = 25
"""
DON'T MODIFY ANYTHING IN THIS CELL
"""
mnist_images = helper.get_batch(glob(os.path.join(data_dir, 'img_align_celeba/*.jpg'))[:show_n_images], 28, 28, 'RGB')
pyplot.imshow(helper.images_square_grid(mnist_images, 'RGB'))
Since the project's main focus is on building the GANs, we'll preprocess the data for you. The values of the MNIST and CelebA dataset will be in the range of -0.5 to 0.5 of 28x28 dimensional images. The CelebA images will be cropped to remove parts of the image that don't include a face, then resized down to 28x28.

You'll build the components necessary to build a GANs by implementing the following functions below:
model_inputs
discriminator
generator
model_loss
model_opt
train
This will check to make sure you have the correct version of TensorFlow and access to a GPU
"""
DON'T MODIFY ANYTHING IN THIS CELL
"""
from distutils.version import LooseVersion
import warnings
import tensorflow as tf
# Check TensorFlow Version
assert LooseVersion(tf.__version__) >= LooseVersion('1.0'), 'Please use TensorFlow version 1.0 or newer. You are using {}'.format(tf.__version__)
print('TensorFlow Version: {}'.format(tf.__version__))
# Check for a GPU
if not tf.test.gpu_device_name():
warnings.warn('No GPU found. Please use a GPU to train your neural network.')
else:
print('Default GPU Device: {}'.format(tf.test.gpu_device_name()))
Implement the model_inputs
function to create TF Placeholders for the Neural Network. It should create the following placeholders:
image_width
, image_height
, and image_channels
.z_dim
.Return the placeholders in the following the tuple (tensor of real input images, tensor of z data)
import problem_unittests as tests
def model_inputs(image_width, image_height, image_channels, z_dim):
"""
Create the model inputs
:param image_width: The input image width
:param image_height: The input image height
:param image_channels: The number of image channels
:param z_dim: The dimension of Z
:return: Tuple of (tensor of real input images, tensor of z data, learning rate)
"""
# TODO: Implement Function
real_inputs = tf.placeholder(tf.float32, (None, image_width, image_height, image_channels),
'real_inputs')
# noise verctor
z_inputs = tf.placeholder(tf.float32, (None, z_dim), 'z_inputs')
learning_rate = tf.placeholder(tf.float32, name='learning_rate')
return real_inputs, z_inputs, learning_rate
"""
DON'T MODIFY ANYTHING IN THIS CELL THAT IS BELOW THIS LINE
"""
tests.test_model_inputs(model_inputs)
Implement discriminator
to create a discriminator neural network that discriminates on images
. This function should be able to reuse the variables in the neural network. Use tf.variable_scope
with a scope name of "discriminator" to allow the variables to be reused. The function should return a tuple of (tensor output of the discriminator, tensor logits of the discriminator).
def discriminator(images, reuse=False):
"""
Create the discriminator network
:param images: Tensor of input image(s)
:param reuse: Boolean if the weights should be reused
:return: Tuple of (tensor output of the discriminator, tensor logits of the discriminator)
"""
# TODO: Implement Function
with tf.variable_scope('discriminator', reuse=reuse):
alpha = 0.2
# Conv layer1
h1 = tf.layers.conv2d(images, 32, 5, 2, 'same')
h1 = tf.maximum(alpha * h1, h1)
#Conv layer2
h2 = tf.layers.conv2d(h1, 64, 5, 2, 'same')
h2 = tf.layers.batch_normalization(h2, training=True)
h2 = tf.maximum(alpha * h2, h2)
#Conv layer3
h3 = tf.layers.conv2d(h2, 128, 5, 2, 'same')
h3 = tf.layers.batch_normalization(h3, training=True)
h3 = tf.maximum(alpha * h3, h3)
y = tf.reshape(h3, (-1, 4*4*128))
logits = tf.layers.dense(y, 1)
out = tf.sigmoid(logits)
return out, logits
"""
DON'T MODIFY ANYTHING IN THIS CELL THAT IS BELOW THIS LINE
"""
tests.test_discriminator(discriminator, tf)
Implement generator
to generate an image using z
. This function should be able to reuse the variables in the neural network. Use tf.variable_scope
with a scope name of "generator" to allow the variables to be reused. The function should return the generated 28 x 28 x out_channel_dim
images.
def generator(z, out_channel_dim, is_train=True):
"""
Create the generator network
:param z: Input z
:param out_channel_dim: The number of channels in the output image
:param is_train: Boolean if generator is being used for training
:return: The tensor output of the generator
"""
# TODO: Implement Function
with tf.variable_scope('generator', reuse=not is_train):
alpha = 0.2
h1 = tf.layers.dense(z, 2*2*512)
h1 = tf.reshape(h1, (-1, 2, 2, 512))
h1 = tf.layers.batch_normalization(h1, training=is_train)
h1 = tf.maximum(alpha * h1, h1)
h2 = tf.layers.conv2d_transpose(h1, 256, 5, 2, 'valid')
h2 = tf.layers.batch_normalization(h2, training=is_train)
h2 = tf.maximum(alpha * h2, h2)
h3 = tf.layers.conv2d_transpose(h2, 128, 5, 2, 'same')
h3 = tf.layers.batch_normalization(h3, training=is_train)
h3 = tf.maximum(alpha * h3, h3)
logits = tf.layers.conv2d_transpose(h3, out_channel_dim, 6, 2, 'same')
out = tf.tanh(logits)
return out
"""
DON'T MODIFY ANYTHING IN THIS CELL THAT IS BELOW THIS LINE
"""
tests.test_generator(generator, tf)
Implement model_loss
to build the GANs for training and calculate the loss. The function should return a tuple of (discriminator loss, generator loss). Use the following functions you implemented:
discriminator(images, reuse=False)
generator(z, out_channel_dim, is_train=True)
def model_loss(input_real, input_z, out_channel_dim):
"""
Get the loss for the discriminator and generator
:param input_real: Images from the real dataset
:param input_z: Z input
:param out_channel_dim: The number of channels in the output image
:return: A tuple of (discriminator loss, generator loss)
"""
# TODO: Implement Function
g_model = generator(input_z, out_channel_dim)
d_model_real, d_logits_real = discriminator(input_real)
d_model_fake, d_logits_fake = discriminator(g_model, reuse=True)
d_loss_real = tf.reduce_mean(
tf.nn.sigmoid_cross_entropy_with_logits(logits=d_logits_real, labels=tf.ones_like(d_model_real)))
d_loss_fake = tf.reduce_mean(tf.nn.sigmoid_cross_entropy_with_logits(
logits=d_logits_fake, labels=tf.zeros_like(d_model_fake)))
g_loss = tf.reduce_mean(tf.nn.sigmoid_cross_entropy_with_logits(
logits=d_logits_fake, labels=tf.ones_like(d_model_fake)))
d_loss = d_loss_real + d_loss_fake
return d_loss, g_loss
"""
DON'T MODIFY ANYTHING IN THIS CELL THAT IS BELOW THIS LINE
"""
tests.test_model_loss(model_loss)
Implement model_opt
to create the optimization operations for the GANs. Use tf.trainable_variables
to get all the trainable variables. Filter the variables with names that are in the discriminator and generator scope names. The function should return a tuple of (discriminator training operation, generator training operation).
def model_opt(d_loss, g_loss, learning_rate, beta1):
"""
Get optimization operations
:param d_loss: Discriminator loss Tensor
:param g_loss: Generator loss Tensor
:param learning_rate: Learning Rate Placeholder
:param beta1: The exponential decay rate for the 1st moment in the optimizer
:return: A tuple of (discriminator training operation, generator training operation)
"""
# TODO: Implement Function
t_vars = tf.trainable_variables()
d_vars = [v for v in t_vars if v.name.startswith('discriminator')]
g_vars = [v for v in t_vars if v.name.startswith('generator')]
# Optimizer
with tf.control_dependencies(tf.get_collection(tf.GraphKeys.UPDATE_OPS)):
d_train_opt = tf.train.AdamOptimizer(learning_rate, beta1).minimize(d_loss, var_list=d_vars)
g_train_opt = tf.train.AdamOptimizer(learning_rate, beta1).minimize(g_loss, var_list=g_vars)
return d_train_opt, g_train_opt
"""
DON'T MODIFY ANYTHING IN THIS CELL THAT IS BELOW THIS LINE
"""
tests.test_model_opt(model_opt, tf)
"""
DON'T MODIFY ANYTHING IN THIS CELL
"""
import numpy as np
def show_generator_output(sess, n_images, input_z, out_channel_dim, image_mode):
"""
Show example output for the generator
:param sess: TensorFlow session
:param n_images: Number of Images to display
:param input_z: Input Z Tensor
:param out_channel_dim: The number of channels in the output image
:param image_mode: The mode to use for images ("RGB" or "L")
"""
cmap = None if image_mode == 'RGB' else 'gray'
z_dim = input_z.get_shape().as_list()[-1]
example_z = np.random.uniform(-1, 1, size=[n_images, z_dim])
samples = sess.run(
generator(input_z, out_channel_dim, False),
feed_dict={input_z: example_z})
images_grid = helper.images_square_grid(samples, image_mode)
pyplot.imshow(images_grid, cmap=cmap)
pyplot.show()
Implement train
to build and train the GANs. Use the following functions you implemented:
model_inputs(image_width, image_height, image_channels, z_dim)
model_loss(input_real, input_z, out_channel_dim)
model_opt(d_loss, g_loss, learning_rate, beta1)
Use the show_generator_output
to show generator
output while you train. Running show_generator_output
for every batch will drastically increase training time and increase the size of the notebook. It's recommended to print the generator
output every 100 batches.
def train(epoch_count, batch_size, z_dim, learning_rate, beta1, get_batches, data_shape, data_image_mode):
"""
Train the GAN
:param epoch_count: Number of epochs
:param batch_size: Batch Size
:param z_dim: Z dimension
:param learning_rate: Learning Rate
:param beta1: The exponential decay rate for the 1st moment in the optimizer
:param get_batches: Function to get batches
:param data_shape: Shape of the data
:param data_image_mode: The image mode to use for images ("RGB" or "L")
"""
# TODO: Build Model
input_real, input_z, lr = model_inputs(data_shape[1], data_shape[2], data_shape[3], z_dim)
d_loss, g_loss = model_loss(input_real, input_z, data_shape[3])
d_train_opt, g_train_opt = model_opt(d_loss, g_loss, lr, beta1)
steps = 0
# TODO: Train Model
with tf.Session() as sess:
sess.run(tf.global_variables_initializer())
for epoch_i in range(epoch_count):
for batch_images in get_batches(batch_size):
steps += 1
# Rescaling input in [-1, 1]
batch_images *= 2
# Sampling random noise for input
batch_z = np.random.uniform(-1, 1, size=(batch_size, z_dim))
# Run Optimizers
_ = sess.run([d_train_opt, g_train_opt], feed_dict={input_real: batch_images, input_z: batch_z, lr: learning_rate})
if steps % 100 == 0:
train_loss_d = d_loss.eval({input_real: batch_images, input_z: batch_z})
train_loss_g = g_loss.eval({input_real: batch_images, input_z: batch_z})
print("Epoch no. {}/{}...".format(epoch_i+1, epoch_count),
"Discriminator Loss: {:.3f}...".format(train_loss_d),
"Generator Loss: {:.3f}".format(train_loss_g))
show_generator_output(sess, 25, input_z, data_shape[3], data_image_mode)
Test your GANs architecture on MNIST. After 2 epochs, the GANs should be able to generate images that look like handwritten digits. Make sure the loss of the generator is lower than the loss of the discriminator or close to 0.
batch_size = 64
z_dim = 100
learning_rate = 0.001
beta1 = 0.5
"""
DON'T MODIFY ANYTHING IN THIS CELL THAT IS BELOW THIS LINE
"""
epochs = 2
mnist_dataset = helper.Dataset('mnist', glob(os.path.join(data_dir, 'mnist/*.jpg')))
with tf.Graph().as_default():
train(epochs, batch_size, z_dim, learning_rate, beta1, mnist_dataset.get_batches,
mnist_dataset.shape, mnist_dataset.image_mode)
Run your GANs on CelebA. It will take around 20 minutes on the average GPU to run one epoch. You can run the whole epoch or stop when it starts to generate realistic faces.
batch_size = 64
z_dim = 100
learning_rate = 0.0001
beta1 = 0.5
"""
DON'T MODIFY ANYTHING IN THIS CELL THAT IS BELOW THIS LINE
"""
epochs = 1
celeba_dataset = helper.Dataset('celeba', glob(os.path.join(data_dir, 'img_align_celeba/*.jpg')))
with tf.Graph().as_default():
train(epochs, batch_size, z_dim, learning_rate, beta1, celeba_dataset.get_batches,
celeba_dataset.shape, celeba_dataset.image_mode)
When submitting this project, make sure to run all the cells before saving the notebook. Save the notebook file as "dlnd_face_generation.ipynb" and save it as a HTML file under "File" -> "Download as". Include the "helper.py" and "problem_unittests.py" files in your submission.


Going Passwordless
By Jonathan Singmin
Senior Software Engineer
The Problem
Data Breaches
Phishing
Factors of Authentication
Something you know
Something you have
Somewhere you are
Something you are
The next stage
Jargon
FIDO (Fast IDentity Online)
U2F (Universal 2nd Factor)
CTAP (Client to Authenticator Protocol)
WebAuthn (Web Authentication)
How it works - Registration
How it works - Login
Why it's better
Designed to be phishing resistant
No personally identifying data transmitted
Device unlock data (PIN, biometrics) doesn't leave the device
Weaknesses
Reliant on a physical item
Configuration
Demo
How to start?
Authenication keys
Platform authenticators
Android phones
Windows Hello
https://fidoalliance.org/certification/fido-certified-products/
https://www.dongleauth.info/
References
https://fidoalliance.org/
https://webauthn.io/
https://webauthn.guide/
https://www.troyhunt.com/beyond-passwords-2fa-u2f-and-google-advanced-protection/
https://www.slideshare.net/FIDOAlliance/webauthn-and-security-keys-126400301/
https://www.cloudflare.com/learning/security/threats/phishing-attack/
https://techcrunch.com/2019/09/26/doordash-data-breach/
https://www.forbes.com/sites/daveywinder/2019/09/05/facebook-security-snafu-exposes-419-million-user-phone-numbers/
https://www.forbes.com/sites/kateoflahertyuk/2019/02/12/hackers-have-just-put-620-million-online-account-details-up-for-sale-is-yours-on-the-list/
https://haveibeenpwned.com/
https://krebsonsecurity.com/2018/07/google-security-keys-neutralized-employee-phishing/
https://www.technologyreview.com/f/614163/data-leak-exposes-unchangeable-biometric-data-of-over-1-million-people/
https://pixabay.com/
(Images)
https://commons.wikimedia.org/
(Images)
Q&A
Also, you can find me at:
jsingmin_dev
jsingmin


St Kilda signs delisted Geelong ruckman Ryan Abbott as a delisted free agent
by Josh GabelichDelisted Geelong ruckman Ryan Abbott has received an AFL lifeline from St Kilda.
Foxsports.com.au can reveal the 28-year-old met with senior coach Brett Ratten earlier this week after meeting with list manager James Gallagher last week, before the Saints signed him as a delisted free agent on Friday afternoon.
St Kilda acquired All-Australian ruckman Paddy Ryder from Port Adelaide during the trade period and are set to pair the veteran with rising star Rowan Marshall, who finished second in this year’s Trevor Barker Award.
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But after cutting former first-round pick Billy Longer and Lewis Pierce at the end of August, the Saints have turned to Abbott to improve their ruck depth ahead of 2020, with basketball convert Sam Alabakis the only other ruckman at Moorabbin.
St Kilda pro scout Stephen Lennie monitored Abbott’s progress throughout the year where he starred in the VFL but could only add one senior game to the four he played in 2018, despite Geelong’s unstable ruck situation.
Geelong had committed to putting Abbott on their rookie list if he didn’t find a home before the National Draft.
The 200cm, 100kg ruckman will start training at RSEA Park on Monday.
Abbott played basketball between the ages of 14 and 21 before playing local football at Grovedale, where he attracted interest from the Cats after winning consecutive best and fairest awards in the Geelong Football League.
St Kilda has been the most active club during the off-season period.
They landed one of the biggest fish of the trade period in Bradley Hill from Fremantle, before also landing Power pair Dougal Howard and Ryder, Sydney midfielder Zak Jones and Richmond premiership forward Dan Butler.
After heading to last year’s draft armed with Pick 4 – which they used on Max King – the Saints currently hold Picks 51, 76 and 82 and have three spots remaining on their list.


WADD: The Life and Times of John C. Holmes (1998) 110m.
 The film-makers obviously figured that this subject matter alone was going to earn their movie an R rating so they allow their interview subjects free rein on opinions and reminiscences - this doco has the highest frequency for 'penis' synonyms in the first ten minutes than any other film you will have seen. It's only to be expected: Holmes' claim to fame was 13 inches of talent (32.5 cm if you prefer metric), a fact that director Cass Paley recognizes as this movie's selling point. The audience gets what it pays for (although the famous member itself is only glimpsed) with much made of the fact that Holmes was born for porn, but this is merely a starting point - there's a lot more than sex going on in this story.
Holmes' odyssey leads him from a hard upbringing in Ohio, a stint in the signal corps, and marriage in California. After an introduction to the LA pornography market and the invention of private dick 'Johnny Wadd' (the script was written on the back of an envelope!), his career path is assured, and the rest should be simple.  After being busted on pimping charges (along with others stuck with "conspiracy to commit oral copulation"), Holmes turns informant for the LAPD vice squad - effectively he is living out his own porn-detective alter ego. He graduates from smoking joints to freebasing cocaine, blurring lines of reality even further. By the time he's stealing cars while on the run from the FBI, the cops, AND the mob, Holmes' separation from everything and everyone in his life has become complete. WADD is terribly confusing: no other documentary has been so replete with contradiction. The most common adjectives used by interviewees to describe Holmes are 'gentle' and 'sweet' - yet this is the same man who caused the horrific murders of four people and wantonly continued having sex with women without informing them that he was HIV positive. Nearly everyone gushes about what a great guy he was, but who's kidding who? By the end of the film you won't trust what anyone has to say except for his second wife who has at least suffered enough physically to make her testimony believable. Just to bring everything full circle, Holmes' third wife (and porn star) Misty Dawn sued the film-makers a year after WADD's release for slander and "reckless disregard for the truth".
Much more than just a documentary on a titillating subject, WADD is equal doses of humor, poignancy, horror and fascination. Many lines are quotable, but not subject for repetition in most review columns and as the star player is Holmes himself, several innocent sentences take on amusing innuendoes - my favorite is when his first wife talks of his carpentry skills, claiming he 'could make anything with wood'. Among those interviewed: Ron Jeremy, Gloria Leonard, Kitten Natividad and Misty Dawn a.k.a. Laurie Holmes, who now maintains the official John Holmes website. Film also includes non-explicit clips from various Holmes movies, including the Johnny Wadd series. Musical score of documentary is suitably cheesy and could be recycled in spots as background for any real porno movie.
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Broken URLs inthe reviews are the responsibility of the author.
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Clearly see patterns and trends. Get fast insights into population health, cost trends and usage patterns via rich visuals and interactive design. In-depth informatics. Further explore trends, identify opportunities and monitor health initiatives by conducting detailed analyses of your health benefits information through interactive and configurable dashboard style data views and self-service detailed reporting capabilities.
Powerful analytic systems. Symmetry® analytic methodologies provide access to robust clinical analyses of cost, prevalence, health risk and adherence to evidence based treatment guidelines. • Holistic analysis. Include a range of benefit programs in your analyses, such as lifestyle, wellness and disease management programs; biometric results; health assessment survey results; short-term disability; long-term disability; workers compensation; FMLA; time and attendance for a complete integrated view across all benefits offerings.


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| DOSE: |
0.5 g |
smoked |
Damiana |
(dried) |
| |
0.5 g |
smoked |
Damiana |
(ground / crushed) |
I purchased a pound of damiana from a online health food store, at the time to use as a tea infusion in combination with hibiscus flowers (flor de jamica). The effect of the dried foliage in tea was quite potent, mild sedation and slight euphoria. After some consideration, I put a quarter ounce into my coffee grinder and powdered it.
The next day, my friends and I were driving back from classes, and I packed a bowl of damiana, letting everyone know what was in it. Powdered damiana combusts quickly, I cleared the first bowl, about a half gram in one breath. It was a bit harsh, but only because I wasn't expecting the quantity of smoke. I had my friend repack it, because I noticed a sudden decrease in motor ability. At T+5 minutes, streetlights started to blend together. I had a sudden feeling of euphoria, like everything seemed beautiful. It took me awhile to realize that we had all stopped talking... I knew that the effect was taking hold for all of us. Effects became less pronounced after a half hour, and a within 45 minutes that had passed. The following day, I decided to hit a bowl by myself in between classes... when I arrived at my next class, I felt glued to my seat, unable to concentrate, but, unconcerned. Trying to take notes, I realized my motor function was destroyed.
Overall, although it isn't as good as cannabis for relaxation, as the effects lasted no more than an hour, because of its price, I plan on using it more for destressing, and saving my pot for visionary excursions.
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.


HackTrain is the first and biggest initiative in Europe targeted to #HackTheRails! An unforgettable journey where a cohort of 40 of the best developers will jump on a once-in-a-lifetime journey, competing in the HackTrain hackathon, and obtaining a chance to join the HackTrain accelerator program! You will jump aboard the HackTrain for an opportunity to travel to the top coworking spaces in the UK, hang out with the market makers in the Startup ecosystem, and create startups that will revolutionize the transport and travel industries!
Startups, apps, prototypes will be created, and presented for funding to of CEOs, investors, VCs, serial entrepreneurs and evangelists - all with the objective of becoming the 2015 HackTrain champion! With TrainHackers from UK, Russia, Romania, France, Poland, Czech Republic together with many other European countries, this hackathon will certainly promise a unique experience!
Crazy? Definitely! Impossible? Not even close! HackTrain alumni have created products that have been taken forward after prototyping mind blowing and revolutionary concepts! Some of our past events include our 2015 HackTrain, our Startup Bus UK 2014, Startup Weekend Moscow, Startup Hacks.
Thanks to our strong partnership with the largest train companies in the UK, including East Midland Trains and Virgin Trains East Coast, hackers will be turning pizza into software whilst on an executive First Class Journey!
The rail industry is transforming the way it manages innovation and introduces new technologies. A rail innovation fund has been established to stimulate the demonstration and distribution of technologies which can bring about a step-change in the sector.
The FutureRailway programme prioritises improvements in the use of data and information and their translation into systems and services that reduce cost, improve operations and benefit customers across the industry.
Innovate UK and rail bodies have recognised the need to support this transformation and to connect established industry players with agile, innovative businesses to create a new and different type of supply chain for the major rail providers and related infrastructure and support companies.
There are a number of barriers to innovative businesses working with the rail industry. The Rail Accelerator will help overcome some of these, fostering collaboration and establishing trust between rail industry clients and innovative digital businesses, many of whom are SMEs and new entrants to the market. Only by harnessing the creativity and responsiveness of such businesses will the sector be able to truly transform itself. Rail Accelerator is a major enabler for unlocking access to a broad range of digital companies and talent from around to world to engage that much needed innovation.


| Up | TOC | Index | |||||
| << 8 API Reference | < 9.14 Version 3.0.1 November 3, 2006 | Up: 9 Release Notes | 9.16 Version 2.5 March 8, 2005 > | 10 Index >> |
9.15 Version 3.0.0 October 17, 2006
With this release, Euphoria has become a totally free and totally open source product! RDS will continue to develop Euphoria with the aid of many additional clever programmers. The free download package now includes the Interpreter (with either a C or a Euphoria-coded back-end), Binder/shrouder, fully-enabled Translator, and the full source code for all of these. Thousands of people can now examine the full source code for bugs, performance improvements, and potential new features.
Rather than having alpha, beta and official releases, we will now simply have numbers, 3.0.0, 3.0.1 ... We expect to have releases more frequently, though each release will likely be a smaller change compared to the previous release.
9.15.1 Enhanced Features
- Cooperative Multitasking. Rather than having just a single thread of execution, you can now create multiple tasks that run independently of one another. Each task has its own currently-executing statement, subroutine call-stack, and private variables for all routines on its call-stack. Tasks share global and local variables but not private variables. At any point during its execution, a task can call task_yield() to transfer control to the Euphoria scheduler which will choose the next task to run. When control returns to the original task, execution will continue from the statement after task_yield().
- New Run-time routines: task_create(), task_schedule(), task_yield(), task_suspend(), task_self(), task_list(), task_status(), task_clock_start(), task_clock_stop()
- Use of the ncurses library has been eliminated for Linux and FreeBSD. ncurses routines sometimes caused problems on some Linux/FreeBSD systems. The Euphoria backend now uses ANSI escape chars to get 2-d positioning and colors for a plain text-mode console. Also, the use of libgpm (console mouse support) has been dropped on Linux. (It was never supported by Euphoria on FreeBSD).
- Include files with the same file name but a different path as an earlier include, will no longer be ignored. To be ignored, an include must refer to the exact same file as an earlier include. (a new name space can still be defined, even though the include file is not actually included again.) On Linux/FreeBSD a case-sensitive file-name comparison is now used.
There is possible (but unlikely) breakage of old code:
You might start including files that you did not intend to include, if you have a previously-ignored include statement for them in your code. Solution: Delete the undesired include statement.
If an include is incorrect (file is not on the include search path), this error may have been hidden under the old system, if a correct include with the same file name (but different path) came earlier. Solution: Specify the correct path to the include file. - There is no longer a limit on the number of warnings that can be displayed. Instead, you will be given the chance to scroll through all the warnings, 20 at a time. As before, if a ex.err file is created, then all warnings will also be stored at the end of the ex.err file. Thanks to Judith Evans.
- Translator: You can set the run-time stack size for your program using the -stack nnnn option. The default stack size has been increased for most of the supported C compilers, especially when your program contains a call to task_create().
- If a run-time error occurs and ex.err can't be opened, a check will be made to see if it's because you have too many open files. An appropriate message will then be issued. Several people ran into this situation.
- execute.e: Additional run-time error checks were added to several run-time routines to allow the pure-Euphoria source interpreter to catch more errors itself, rather than letting the C-coded run-time routines used by the "real" interpreter or translator catch them.
- pretty_print(), option 3, now includes \t \r and \n as valid "ASCII range" characters. This increases the likelihood of strings being displayed. Thanks to Juergen Luethje.
- The ASCII 127 char will not be graphically displayed on Linux in trace or in default pretty_print(). It displays as a backspace when ANSI codes are used.
- Binder options are checked more strictly. e.g. -xxxoutxxx was dangerous The binder now looks for match(x,y) = 1, rather than match(x,y) != 0. The binder also avoids overwriting a source file when -out is used. Thanks to Mike Sabal, Greg Haberek
- We've switched to using transparent Euphoria icons. Thanks to Vincent Howell.
- Pure Euphoria interpreter (eu.ex): The "not initialized" message has been improved to: "xyz has not been initialized"
- Many small improvements were made to the documentation. e.g. the use of a single atom value by multiple printf() formats was documented for the first time. Thanks to Pete Lomax.
9.15.2 Bug Fixes
- bug fixed: Translator: a Euphoria file named "main.e" or "init.e" could possibly lead to a file naming conflict. The chance of a conflict is now greatly reduced, and if a conflict occurs, a meaningful error message will be issued. Thanks to Vincent Howell.
- bug fixed: Translator: using "interrupt" as a Euphoria variable name caused a naming conflict when compiling with Watcom. Thanks to Louis Bryant.
- bug fixed: Translator: A backslash at the end of a Euphoria comment could be considered a line continuation character by the C compiler. This could result in incorrect code being generated. Thanks to Mark Honnor.
- bug fixed: Translator: A call to a Euphoria-coded routine in a .dll, i.e. via c_func(), could cause a bug if the return type was sequence or object. Thanks to Thomas Jansen.
- bug fixed: If you pass file number -1 to printf() you will now get a run-time error report. In all previous releases, -1 would simply cause printf() to produce no output. Thanks to Daniel Kluss.
- bug fixed: scanner.e: Source lines longer than 10000 characters caused a problem. Also we were not checking for allocate() returning 0 in pack_source() (i.e. out of memory condition). Thanks to Antonio Alessi.
- bug fixed: execute.e: (pure Euphoria interpreter) In some cases slice indexes were not being bounds checked before being used. eu.ex would crash rather than report the error in the user's program.
- bug fixed: Assignments of the form: x[a][b..c] += expr were likely to trigger an erroneous subscript error in execute.e, the pure Euphoria interpreter. Thanks to Vincent Howell.10813
- bug fixed: execute.e did not handle fractional subscripts correctly in some situations. Thanks to C Bouzy and Vincent Howell.


Group_by is a very cool method in Ruby. It essentially allows an argument to be passed into an array, and then organized the information into groups.
Lets say we have an array that contains (dog, cat, mouse, lion, horse, fish). At this point the array is a list of objects with no organization. We can however break this down using group_by. For instance, say we want this list grouped by how long each word is. We would invoke grou_by.length on this list, and it would output some thing like this:
{[3=> dog, cat] , [4=>lion, fish], [5=>mouse, horse]}
As you can see, we have easily grouped the array by length. This would be quite useful in large lists for example, or arrays where you may want to group a list by first or last name.
We can also invoke group_by on hashes, and here is where we can really see the power of this method. It works like this:
group_by {|object| block} returns a hash.
When we use this on a hash, we have a greater ability for grouping and it unlocks being able to do so by keys and values. So for example if we have a list of people and also have their ages, we can group them according to either of these. Its pretty powerful stuff when you consider how simply it returns the desired result.
Thank you for reading!


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ResultSet
object.
PreparedStatement
object's batch of commands.
Statement
object.
ResultSet
object, just after the last row.
getProcedures
.
getTables
in a SELECT
statement.
ResultSet
object, just before the
first row.
Statement
object if both the DBMS and
driver support aborting an SQL statement.
ResultSet
object.
Statement
object's current list of
SQL commands.
Connection
object.
ResultSet
object.
Statement
object.
Connection
object's database and JDBC resources immediately instead of
waiting for them to be automatically released.
ResultSet
object's database and
JDBC resources immediately instead of waiting for
this to happen when it is automatically closed.
Statement
object's database
and JDBC resources immediately instead of waiting for
this to happen when it is automatically closed.
Statement
object for sending SQL statements to the database.
Statement
object that will generate
ResultSet
objects with the given type and
concurrency.
Statement
object that will generate ResultSet
objects with
the given type, concurrency, and holdability.
ResultSet
object
and from the underlying database.
ResultSet.rowDeleted
.
getMaxRowSize
includes the SQL data types
LONGVARCHAR
and LONGVARBINARY
.
PreparedStatement
object, which may be any kind of SQL statement.
PreparedStatement
object
and returns the ResultSet
object generated by the query.
ResultSet
object.
PreparedStatement
object, which must be an SQL INSERT
,
UPDATE
or DELETE
statement; or an SQL
statement that returns nothing, such as a DDL statement.
INSERT
,
UPDATE
, or DELETE
statement or an
SQL statement that returns nothing, such as an SQL DDL statement.
Statement
object
should be made available for retrieval.
ResultSet
column name to its
ResultSet
column index.
ResultSet
object.
ARRAY
parameter as an Array
object in the Java programming
language.
ARRAY
parameter as an
Array
object in the Java programming language.
ResultSet
object as an Array
object
in the Java programming language.
ResultSet
object as an Array
object
in the Java programming language.
CLOB
value designated by this
Clob
object as an ascii stream.
ResultSet
object as
a stream of ASCII characters.
ResultSet
object as a stream of
ASCII characters.
getBigDecimal(int parameterIndex)
or getBigDecimal(String parameterName)
NUMERIC
parameter as a java.math.BigDecimal
object with as many
digits to the right of the decimal point as the value contains.
NUMERIC
parameter as a
java.math.BigDecimal
object with as many digits to the
right of the decimal point as the value contains.
ResultSet
object as a
java.math.BigDecimal
with full precision.
ResultSet
object as a
java.math.BigDecimal
with full precision.
BLOB
value designated by this
Blob
instance as a stream.
ResultSet
object as a binary stream of
uninterpreted bytes.
ResultSet
object as a stream of uninterpreted
byte
s.
BLOB
parameter as a Blob
object in the Java
programming language.
BLOB
parameter as a
Blob
object in the Java programming language.
ResultSet
object as a Blob
object
in the Java programming language.
ResultSet
object as a Blob
object
in the Java programming language.
BIT
parameter
as a boolean
in the Java programming language.
BIT
or BOOLEAN
parameter as a
boolean
in the Java programming language.
ResultSet
object as
a boolean
in the Java programming language.
ResultSet
object as
a boolean
in the Java programming language.
TINYINT
parameter as a byte
in the Java programming language.
TINYINT
parameter as a
byte
in the Java programming language.
ResultSet
object as
a byte
in the Java programming language.
ResultSet
object as
a byte
in the Java programming language.
BLOB
value that this
Blob
object represents, as an array of bytes.
BINARY
or
VARBINARY
parameter as an array of byte
values in the Java programming language.
BINARY
or
VARBINARY
parameter as an array of byte
values in the Java programming language.
ResultSet
object as
a byte
array in the Java programming language.
ResultSet
object as
a byte
array in the Java programming language.
String
that this database uses as the
separator between a catalog and table name.
CLOB
value designated by this
Clob
object as a java.io.Reader
object
(or as a stream of characters).
ResultSet
object as a
java.io.Reader
object.
ResultSet
object as a
java.io.Reader
object.
CLOB
parameter as a Clob
object in the Java programming
language.
CLOB
parameter as a
Clob
object in the Java programming language.
ResultSet
object as a Clob
object
in the Java programming language.
ResultSet
object as a Clob
object
in the Java programming language.
ResultSet.getObject
is called to retrieve a value from the column.
ResultSet
object.
ResultSet
object.
DataSource
object represents.
DataSource
object represents.
Connection
object
that produced this Statement
object.
ResultSet
object.
DATE
parameter
as a java.sql.Date
object.
DATE
parameter as a java.sql.Date
object, using
the given Calendar
object
to construct the date.
DATE
parameter as a
java.sql.Date
object.
DATE
parameter as a
java.sql.Date
object, using
the given Calendar
object
to construct the date.
ResultSet
object as a
java.sql.Date
object in the Java programming language.
ResultSet
object as a
java.sql.Date
object in the Java programming language.
ResultSet
object as a
java.sql.Date
object
in the Java programming language.
ResultSet
object as a java.sql.Date
object in the Java programming language.
DOUBLE
parameter as a double
in the Java programming language.
DOUBLE
parameter as
a double
in the Java programming language.
ResultSet
object as
a double
in the Java programming language.
ResultSet
object as
a double
in the Java programming language.
String
.
ResultSet
object.
Statement
object.
ResultSet
object.
ResultSet
objects
generated from this Statement
object.
FLOAT
parameter as a float
in the Java programming language.
FLOAT
parameter as
a float
in the Java programming language.
ResultSet
object as
a float
in the Java programming language.
ResultSet
object as
a float
in the Java programming language.
Statement
object.
ResultSet
objects created using
this Connection
object.
INTEGER
parameter as an int
in the Java programming language.
INTEGER
parameter as
an int
in the Java programming language.
ResultSet
object as
an int
in the Java programming language.
ResultSet
object as
an int
in the Java programming language.
DataSource
object.
BIGINT
parameter as a long
in the Java programming language.
BIGINT
parameter as
a long
in the Java programming language.
ResultSet
object as
a long
in the Java programming language.
ResultSet
object as
a long
in the Java programming language.
GROUP BY
clause.
ORDER BY
clause.
SELECT
list.
ResultSet
object produced by this Statement
object.
ResultSet
object produced by this
Statement
object can contain.
SELECT
statement.
ResultSetMetaData
object that contains
information about the columns of the ResultSet
object
that will be returned when this PreparedStatement
object
is executed.
ResultSet
object's columns.
Statement
object's next result, returns
true
if it is a ResultSet
object, and
implicitly closes any current ResultSet
object(s) obtained with the method getResultSet
.
Statement
object's next result, deals with
any current ResultSet
object(s) according to the instructions
specified by the given flag, and returns
true
if the next result is a ResultSet
object.
Object
in the Java programming language.
parameterIndex
and uses map
for the custom
mapping of the parameter value.
Object
in the Java
programming language.
parameterName
and uses map
for the custom
mapping of the parameter value.
ResultSet
object as
an Object
in the Java programming language.
ResultSet
object as
an Object
in the Java programming language.
ResultSet
object as an Object
in the Java programming language.
ResultSet
object as an Object
in the Java programming language.
PreparedStatement
object's parameters.
Statement
object to execute.
REF(<structured-type>)
parameter as a
Ref
object in the Java programming language.
REF(<structured-type>)
parameter as a Ref
object in the Java programming language.
ResultSet
object as a Ref
object
in the Java programming language.
ResultSet
object as a Ref
object
in the Java programming language.
ResultSet
object.
ResultSet
objects
generated by this Statement
object.
ResultSet
object.
ResultSet
objects
generated by this Statement
object.
ResultSet
objects
generated by this Statement
object.
SQLException.getSQLState
is X/Open (now known as Open Group)
SQL CLI or SQL99.
Savepoint
object represents.
Savepoint
object represents.
SMALLINT
parameter as a short
in the Java programming language.
SMALLINT
parameter as
a short
in the Java programming language.
ResultSet
object as
a short
in the Java programming language.
ResultSet
object as
a short
in the Java programming language.
Statement
object that produced this
ResultSet
object.
CHAR
,
VARCHAR
, or LONGVARCHAR
parameter as a
String
in the Java programming language.
CHAR
, VARCHAR
,
or LONGVARCHAR
parameter as a String
in
the Java programming language.
ResultSet
object as
a String
in the Java programming language.
ResultSet
object as
a String
in the Java programming language.
CLOB
value designated by this Clob
object.
TIME
parameter
as a java.sql.Time
object.
TIME
parameter as a java.sql.Time
object, using
the given Calendar
object
to construct the time.
TIME
parameter as a
java.sql.Time
object.
TIME
parameter as a
java.sql.Time
object, using
the given Calendar
object
to construct the time.
ResultSet
object as a java.sql.Time
object in the Java programming language.
ResultSet
object as a java.sql.Time
object in the Java programming language.
ResultSet
object as a java.sql.Time
object in the Java programming language.
ResultSet
object as
a java.sql.Time
object
in the Java programming language.
TIMESTAMP
parameter as a java.sql.Timestamp
object.
TIMESTAMP
parameter as a java.sql.Timestamp
object, using
the given Calendar
object to construct
the Timestamp
object.
TIMESTAMP
parameter as a
java.sql.Timestamp
object.
TIMESTAMP
parameter as a
java.sql.Timestamp
object, using
the given Calendar
object to construct
the Timestamp
object.
ResultSet
object as
a java.sql.Timestamp
object in the Java programming
language.
ResultSet
object as
a java.sql.Timestamp
object.
ResultSet
object as a
java.sql.Timestamp
object in the Java programming
anguage.
ResultSet
object as a
java.sql.Timestamp
object in the Java programming
language.
Connection
object's current transaction isolation level.
ResultSet
object.
DATALINK
parameter as a java.net.URL
object.
DATALINK
parameter as a
java.net.URL
object.
ResultSet
object as a java.net.URL
object in the Java programming language.
ResultSet
object as a java.net.URL
object in the Java programming language.
getCharacterStream
in place of
getUnicodeStream
getCharacterStream
instead
ResultSet
object or there are no more results, -1
is returned.
Connection
object.
ResultSet
object.
Statement
object.
ResultSet
object and into the database.
ResultSet.rowInserted
.
ResultSet
object.
ResultSet
object.
ResultSet
object.
ResultSet
object.
Connection
to an HSQLDB
Database
.
INTERNAL
Connection
,
using the specified Session
.
DataSource
object represents.jdbcDatasource
object instances.ResultSet
object.Connection.rollback
method.ResultSet
object.
BLOB
value
designated by this Blob
object.
CLOB
value
designated by this Clob
object.
NULL
and non-NULL
values being
NULL
.
NULL
values are sorted at the end regardless of
sort order.
NULL
values are sorted at the start regardless
of sort order.
NULL
values are sorted high.
NULL
values are sorted low.
ResultSet
object,
the result set's own updates are visible.
pattern
begins within the BLOB
value that this Blob
object represents.
BLOB
value
designated by this Blob
object at which
pattern
begins.
searchstr
appears in the SQL CLOB
value
represented by this Clob
object.
Clob
object searchstr
appears in this
Clob
object.
CallableStatement
object for calling database stored procedures.
CallableStatement
object that will generate ResultSet
objects with
the given type and concurrency.
CallableStatement
object that will generate ResultSet
objects with
the given type and concurrency.
PreparedStatement
object for sending parameterized SQL statements to the
database.
PreparedStatement
object that will
generate ResultSet
objects with the given type
and concurrency.
PreparedStatement
object that will generate ResultSet
objects with
the given type, concurrency, and holdability.
PreparedStatement
object that has the capability to retrieve auto-generated
keys.
PreparedStatement
object capable of returning the auto-generated keys designated
by the given array.
PreparedStatement
object capable of returning the auto-generated keys designated
by the given array.
ResultSet
object.
RCData
object.
parameterIndex
to the JDBC type
sqlType
.
parameterIndex
to be of JDBC type
sqlType
.
parameterName
to the JDBC type
sqlType
.
parameterName
to be of JDBC type
sqlType
.
Savepoint
object from the current transaction.
Savepoint
object was set.
Array
object.
CLOB
value that this Clob
object represents,
starting at position pos
.
java.math.BigDecimal
value.
java.math.BigDecimal
value.
BLOB
value that this Blob
object represents.
Blob
object.
boolean
value.
boolean
value.
byte
value.
byte
value.
BLOB
value that
this Blob
object represents, starting at position
pos
, and returns the number of bytes written.
byte
array to the
BLOB
value that this Blob
object represents
and returns the number of bytes written.
Reader
object, which is the given number of characters long.
CLOB
value that this Clob
object
represents, at position pos
.
Reader
object, which is the given number of characters long.
Clob
object.
String
, which
will be used by subsequent Statement
object
execute
methods.
java.sql.Date
value
using the default time zone of the virtual machine that is running
the application.
java.sql.Date
value, using the given Calendar
object.
java.sql.Date
value.
java.sql.Date
value, using the given Calendar
object.
double
value.
double
value.
ResultSet
object will be processed.
ResultSet
objects created using this Statement
object.
ResultSet
object.
float
value.
float
value.
ResultSet
objects created using this
Connection
object to the given holdability.
int
value.
int
value.
DataSource
object to the given java.io.PrintWriter
object.
long
value.
long
value.
ResultSet
column storing character or binary values to
the given number of bytes.
ResultSet
object can contain to the given number.
NULL
.
NULL
.
NULL
.
NULL
.
Statement
object to execute to the given number of seconds.
REF(<structured-type>)
value.
Savepoint
object that represents it.
Savepoint
object that represents it.
short
value.
short
value.
String
value.
String
to the CLOB
value that this Clob
object designates at the position
pos
.
len
characters of str
, starting
at character offset
, to the CLOB
value
that this Clob
represents.
String
value.
java.sql.Time
value.
java.sql.Time
value, using the given Calendar
object.
java.sql.Time
value.
java.sql.Time
value, using the given Calendar
object.
java.sql.Timestamp
value.
java.sql.Timestamp
value, using the given
Calendar
object.
java.sql.Timestamp
value.
java.sql.Timestamp
value, using the given Calendar
object.
Connection
object to the one given.
TypeMap
object as the type map for this Connection
object.
java.net.URL
object.
java.net.URL
value.
ALTER TABLE
with add column.
ALTER TABLE
with drop column.
CONVERT
function between SQL types.
CONVERT
for two given SQL types.
ORDER BY
lists.
GROUP BY
clause.
SELECT
statement in a GROUP BY
clause
provided that all of the columns in the SELECT
statement
are included in the GROUP BY
clause.
SELECT
statement in a
GROUP BY
clause.
LIKE
escape clause.
ResultSet
objects returned from a CallableStatement
object
simultaneously.
ResultSet
objects from a single call to the
method execute
.
SELECT
statement in an
ORDER BY
clause.
DELETE
statements.
UPDATE
statements.
SELECT FOR UPDATE
statements.
EXISTS
expressions.
IN
expressions.
UNION
.
UNION ALL
.
BLOB
value that this Blob
object represents to be len
bytes in length.
CLOB
value that this Clob
designates to have a length of len
characters.
java.sql.Array
value.
java.sql.Array
value.
java.math.BigDecimal
value.
java.sql.BigDecimal
value.
java.sql.Blob
value.
java.sql.Blob
value.
boolean
value.
boolean
value.
byte
value.
byte
value.
byte
array value.
java.sql.Clob
value.
java.sql.Clob
value.
java.sql.Date
value.
java.sql.Date
value.
double
value.
double
value.
float
value.
float
value.
int
value.
int
value.
long
value.
long
value.
null
value.
Object
value.
Object
value.
Object
value.
Object
value.
java.sql.Ref
value.
java.sql.Ref
value.
ResultSet
object.
short
value.
short
value.
String
value.
String
value.
java.sql.Time
value.
java.sql.Time
value.
java.sql.Timestamp
value.
java.sql.Timestamp
value.
ResultSet.rowUpdated
.
NULL
.
NULL
.
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It does not include redundant records in the train
set, so the classifiers will not be biased towards more frequent records.
There is no duplicate records in the proposed test
sets; therefore, the performance of the learners are not biased by the methods which
have better detection rates on the frequent records.
The number of selected records from each difficultylevel
group is inversely proportional to the percentage of records in the original KDD
data set. As a result, the classification rates of distinct machine learning methods
vary in a wider range, which makes it more efficient to have an accurate evaluation
of different learning techniques.
The number of records in the train and test sets
are reasonable, which makes it affordable to run the experiments on the complete
set without the need to randomly select a small portion. Consequently, evaluation
results of different research works will be consistent and comparable.


Medical
Peep at some distant orb has power to raise and purify our thoughts like a strain of sacred music, or a noble picture.
Truly it was a great journey, and in it I met with many, whom to know was to love but whom never could I see again for life has not space enough.
Truly it was a great journey, and in it I met with many, whom to know was to love but whom never could I see again for life has not space enough.
Truly it was a great journey, and in it I met with many, whom to know was to love but whom never could I see again for life has not space enough.
F.A.Q.
Apparently we had reached a great height in the atmosphere, for the sky was a dead black.
Though the gravity still dragged at him, his muscles were making great efforts to adjust. After the daily classes he no longer collapsed immediately into bed.
Contact us


I am anxious to become a creator. I understand that designing the interior is very important whether it’s a home, school, office or any other building as it makes a place look unique and fit for purpose. I wish to help people to live and work in appropriate and attractive spaces. I believe I can achieve that through hard work, great effort and devoting a sufficient amount of time. That is why I have chosen interior design.
My acquaintance with art began when I entered Visual and Media Arts School in 2011. During my studies, I dealt with different forms of art and eventually I discovered interior design. After graduating, I decided to concentrate on my modeling career that brought me around the world. This experience initiated in me this eagerness to design through teamwork. Since 2015, I studied an Interior Design Training Program at Herzing College Montreal.


{% extends "../base.html" %} {% block head_title %}
Type of Request
When does the program run now?
Please describe what kind of change you would like to make


Your Results
Have Landed
You Searched for
america
In the String
The Make America Great Again taco bowl. Trump Steaks little hands winning. America Little Marco tremendous. America Make america Great Again spray-can orange. America Build the wall taco bowl
=
The word
america
is in the string 5 times


I code & program computer applications using C++, Java, Python and Kotlin. Specialized and experienced in app development for Android & Web. I love programming and writing elegant, clean code, and have been doing so for 2+ years. A solid grasp of programming fundamentals including algorithms, data structures, OS, I/O, concurrency, networking, OO principles. Experience with multi-threading and concurrency programming. I prefer using libraries rather than writing code on my own. I enjoy solving problems (and I am good at it! :P) I enjoy working with smart, fun people in a friendly, collaborative environment.
Working as an Android developer on Limeroad's consumer application. Building features and enhancing performance for existing app.
Working on the overall design and development of Android app using MVP architecture, EventBus and APIs. Collaborating with the rest of the engineering team to design and deploy the code to test/production environment. Understanding and implementation of security and data protection.
Counselled students of Internshala Trainings by answering their queries and resolving their issues related to Android and Core Java online training programs. Did code review and evaluation of the final training project of students.
This demo app uses CameraX API and Firebase ML Kit labeling API to label and to analyze bar codes, detect faces, or recognize famous landmarks.
View ProjectAndroid app implementing Stack Exchange API to fetch questions from Stack overflow site based on tags provided by user in SearchView.
View ProjectTop news headlines, articles and blogs aggregated from multiple news sources in 7 categories from over 50 countries. Customization of news sources and blogs and articles discovery feature with the offline saving of articles.
View ProjectNote is a simple note-taking web application implementing some basic features of Google Keep application. It is built with Python using the Django Framework.
View Project


Installation has been successfully completed
Now that we're done, there a few things you may want to address for the smooth operation of your site. Please review the installation help guide for further instructions.
For security reasons you should delete the installation files, the install.php script and the install_files directory.


Marcus, well, I'm not sure how to put it.
The words you never want to hear from a doctor's mouth. They're supposed to know everything. So the idea of a doctor not knowing what's wrong with you is terrifying.
I don't know how, but it seems like you have Single Personality Disorder.
Oh God.
This explains everything.
All my life I'd felt alone, like there's something wrong with me. People had always had so many different personalities, it's like everyone was different people, and I was alone in just being myself and nobody else. It confused the heck out of me. It felt like I was different to everyone. It felt like I was unable to make friends, like I'm all alone in the world. I saw people being together and making friends and having fun, and I tried to do that, but all I could do was look on and pretend to not be staring creepily.
This made so much sense.
You know what it is, Marcus?
Yes, I know what it is.
And do you also know how rare it is?
Yes. Less than two percent of the population have it.
We'd like to do some more tests on you, but that can wait.
Oh well. Time to go back to normal.
OK Google, define "normal"
Normal. Conforming to a standard; usual, typical, or expected.
Normal is about the opposite of what happened. Everything was the same, except it was as if I could see everything differently. Everything was so clear. I could see how everyone was working, and the only question that remained was how - and if - I would fit in.


{% extends 'base.html' %} {% block content %}
Your messages has been reported as abusive by another user. This is a warning and the last game will not be included in your statistics. If you are reported twice more, your account will be blocked automatically.
{% else %}You have reported the message of the other user as abusive. Please do so with care because the user will be blocked if reported three times.
This game will not be included in your statistics. Please hit "Play Again" to start a new game or "Logout" to leave the game.
{% endif %} Play Again Logout


News Portal API DEMO
This is a demo of the News Portal API. The code is available on
GitHub
. Checkout my
GitHub profile
for more demo projects.
Public APIs
All Articles
All Articles with No Author
All Comments
All Comments by Article Id
submit
Login Test
Email:
Password:
Sign Up
First Name:
Last Name:
Email/Username:
Password:
Submit
Protected APIs
Users in the database (required for all protected API call)
Please
check this
for more information on roles and protected APIs
Username
Password
Roles
admin#1
adminPass1#
ADMIN,PUBLISHER,EDITOR,AUTHOR,USER
username#2
usernamePass#2
PUBLISHER,USER
username#3
usernamePass#3
EDITOR,AUTHOR,USER
username#7
userPass#7
USER
Username:
Password:
All Authors
Article body contains:
Submit
Author Info by Author Id (same as User Id):
submit
All Articles by Author Id (same as User Id):
submit
Delete a Comment by Comment Id:
submit
Delete a User by User Id:
submit
RESULTS:


--- title: Contact Success lang: en ref: contact-success ---
I will come back to you as soon as possible.


<% include "./components/header.html" %>
<% block content %> <% endblock %>
<% include "./components/footer.html" %>


question 2: Gemz
Notes:
- this game is not finish yet, it still has many bugs
- please read the README.txt before play
- the source code is available in my github: https://github.com/shunwatai/Gems
select time in seconds:
, then either click the below buttons to start
score:
time:


ARMAGEDDON A film review by Steve Rhodes Copyright 1998 Steve Rhodes
RATING (0 TO ****): ** 1/2
Check your brains at the door. It's time for some silly summer fun in ARMAGEDDON as Bruce Willis and Co. kick some asteroid tail. When a big rock last headed for our planet in DEEP IMPACT, it was soap opera time. That was back in the serious days of May. It's summer now when even flying boulders the size of Texas can be seen only as a lark.
The story starts 65 million years ago when a piece of space trash runs into Earth and kills all the dinosaurs. "It happened before," a deep-voiced Moses, a.k.a. Charlton Heston, warns us in the narration. "It will happen again. It's just a matter of time."
Cut to present day New York City, where the poor Chrysler building, which has been wiped out recently in other movies, takes it on the chin again as an early casualty of an errant asteroid. Actually this one is just a baby, his big mama is on the way. The world's governments will keep this fact a secret as the U.S. quickly trains a team of social misfits from a deep ocean oil drilling rig as mankind's only hope of salvation. Think STARSHIP TROOPERS, but more ridiculous. In ARMAGEDDON's defense, it at least realizes it is a parody, something that many recent films haven't been smart enough to figure out.
(The movie will win many viewers' hearts early on with the scene of a small dog attacking a street display of Godzilla toys. Given that many are bigger than him, it is a nice metaphor that size doesn't matter.)
ARMAGEDDON delights in being politically incorrect. When we first see driller Harry S. Stamper (Bruce Willis), he is shooting golf balls from the deck of his rig, trying to hit Greenpeace protestors in the head.
His right-hand man, A.J. Frost (Ben Affleck), is in trouble with Harry for falling in love with Harry's daughter, Grace, played as a cipher by Liv Tyler. Grace doesn't show her father much respect. "I understand that you are handicapped by natural immaturity, but I forgive you," she tells him.
Although there are many contenders for the movie's most ridiculous part, A.J.'s lovemaking scene with Grace has to be the winner. He uses animal crackers as a form of foreplay, something even NINE AND 1/2 WEEKS never tried.
The best performance is turned in, as usual, by Billy Bob Thornton, who plays against type as the brainy head of NASA, Dan Truman. Dan is a guy with a good-ole-boy accent and a leg brace that kept him from ever becoming an astronaut himself. He also gets some of the best lines as when he describes the events of the upcoming asteroid apocalypse as "basically all the worst parts of the bible."
A disheveled Steve Buscemi as Rockhound, plays a double major from MIT, who spends his time worrying that the law will catch up with him for sleeping with underage girls.
Truman chooses Stamper's team to go up in space with the astronauts to drill into the asteroid and plant an atomic bomb. "The fate of the planet is in the hands of a bunch of retards," General Kimsey (Keith David) complains. "I wouldn't trust them with a potato gun."
The rag-tag outfit lives up to their image when they place their demands on the United States government. In order to agree to undertake the mission, their demands include: sleeping in the Lincoln bedroom all summer, bringing back eight-track tapes and revealing who shot Kennedy. The one universal demand is that they never want to pay taxes ever again. Now, that's a request worth fighting for.
When they finally get to the asteroid, the movie appears to have run out of money. The special effects are anything but, and the scene is dark and murky.
If you can only see one asteroid movie this year, DEEP IMPACT, with all of its faults, is probably the better choice. But if you're looking for laughs and have plenty of time to kill, ARMAGEDDON is just about as good.
ARMAGEDDON runs 2:24. It is rated PG-13 for sci-fi disaster action, sensuality and brief profanity and would be fine for kids around 10 and up.
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
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Related links: index of all rec.arts.movies.reviews reviews


The model provides an empirical estimate of a movement path using discrete location data obtained at relatively short time intervals.
| Version: | 3.0 |
| Published: | 2013-03-08 |
| Author: | Nielson, R. M., H. Sawyer, and T. L. McDonald (WEST, Inc., www.west-inc.com) |
| Maintainer: | Ryan Nielson <rnielson at west-inc.com> |
| License: | GPL-2 | GPL-3 [expanded from: GNU General Public License] |
| NeedsCompilation: | no |
| In views: | SpatioTemporal |
| CRAN checks: | BBMM results |
| Reference manual: | BBMM.pdf |
| Package source: | BBMM_3.0.tar.gz |
| Windows binaries: | r-devel: BBMM_3.0.zip, r-release: BBMM_3.0.zip, r-oldrel: BBMM_3.0.zip |
| OS X binaries: | r-release: BBMM_3.0.tgz, r-oldrel: BBMM_3.0.tgz |
| Old sources: | BBMM archive |
Please use the canonical form https://CRAN.R-project.org/package=BBMM to link to this page.


The LENGTH
functions return the length of a text expression.
LENGTH
counts the number of characters.
LENGTHB
uses bytes instead of characters.
LENGTHC
uses Unicode complete characters.
NUMBER
{ LENGTH | LENGTHB | LENGTHC }(char)
char
is any text expression.
LENGTH('CANDIDE')
returns the value 7
.


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MITACS is a national research network which connects academia with industry, government and not-for-profits through short and longer-term research projects.


You can install packages using:
pip install -i {{ ROOT }}pypi/ PACKAGE1 [PACKAGE2 ...]
| Package | Stable | Unstable | Last upload |
|---|---|---|---|
| {{ package.name }} | {{ package.stable }} | {{ package.unstable }} | {{ package.last_modified | formatDate }} |
Don't see any packages? If your redis/sql database was cleared, you may need to rebuild the package list.


Mary Black opens up about her experiences of postnatal depression
Following the traumatic birth of her first child, Conor, the beloved singer said she did not feel well in herself
by Colin BrennanMary Black has opened up about her experiences of postnatal depression, reminding people “there is light at the end of the tunnel”.
Following the traumatic birth of her first child, Conor, the beloved singer said she did not feel well in herself, but thought she was simply feeling a bit down in the dumps.
It was only after seeking help that Mary, who is also mum to Danny and Roisin, realised she could be happy and smile again.
Speaking to Ryan Tubridy on the RTE Late Late Show on Friday night, Mary, 64, said: “It was postnatal depression and it’s a very frightening thing because nobody put a name on it.
“This was more than 30 years ago - he’s 38 now so it was 37 years ago - and postnatal depression or any sort of depression was never talked about.”
The singer, whose latest album, No Frontiers, was released in September, said: “And I think, having gone through it that first time - and I did get well shortly after - it was the fear of never being able to smile or be happy again.
“I think the first time anyone is feeling depression - and I’ll say this to anyone out there that’s feeling bad - there is light at the end of the tunnel. It did happen to me again but it wasn’t as frightening because I felt, I was okay before, there is light and I’ll come back around.”


Ahnold no Deckard clone
Sixth Day A film review by Michael Redman Copyright 2000 by Michael Redman
** (out of ****)
Human cloning appears inevitable. We've cloned sheep. We're mapping the human genome. Can a clone of a former President who, himself, runs for that office be far away?
"The Sixth Day" examines the moral implications of copying people. Sorta. It also tosses in an Arnold Schwarzenegger action film and does neither with much thought...or action.
Adam Gibson (Schwarzenegger) returns home one day to discover that he's already there. His duplicate is enjoying his birthday party. Even worse, he's enjoying his wife in the back seat of their suburban assault vehicle.
In the not-too distant future, cloning is commonplace.  Rover is back with you, just a clone away. Human copying has been outlawed but a rogue company is secretly Xeroxing away.
 Arnold has to survive, destroy their operation and make everything safe for law-abiding folk. It's a typical Schwarzenegger movie, but not quite as exciting.
The action scenes lack the punch of earlier Schwarzenegger pictures. Accustomed to the more highly stylized "Matrix", the audience for old-fashioned shoot-em-up science fiction films might be disappearing. This one isn't exactly a box office sensation.
The story feels reminiscent of "Bladerunner" but without the soul. The minor plot element of which Gibson is "real" (which could be interesting had it been explored for more than 30 seconds) is handled clumsily compared to the underlying question of whether Deckard is a replicant. Gibson's mission is to destroy clones which happen to have a built-in limited life span. Sound familiar? Compare the final scene with one of the Bladerunner endings.
In this season of Christmas releases, Santa won't be laughing "Ho! Ho! Ho!" at this film. It'll be more like "Ho! Hum!"
(Michael Redman has written this column for long enough that he can remember both versions of "Bladerunner". Email<EMAIL_ADDRESS>with your cinematic memories.)
[This appeared in the 12/7/2000 "Bloomington Independent", Bloomington, Indiana. Michael Redman can be contacted at<EMAIL_ADDRESS>--<EMAIL_ADDRESS>Film reviews archive: http://us.imdb.com/ReviewsBy?Michael+Redman
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


This chapter gives a reference of the tools included in this development kit. This chapter is not intended to teach you how to use the tools; it provides a reference only. To learn how to use most of the tools, see the Tutorial included in the development kit and the First Steps chapter in the Concepts book.
1 Tools Summary
2 Typical Development Session
3 File Types
4 Esp
5 Glue
6 Goc
7 Grev
8 mkmf
9 pccom
9.1 PCCOM Background
9.2 Running PCCOM on the Target
9.3 File Transfer Protocol of PCCOM
10 pcget
11 pcs
12 pcsend
13 pmake
13.1 Copyright Notice and Acknowledgment
13.2 How to Customize pmake
13.3 Command Line Arguments
13.4 Contents of a Makefile
13.5 Advanced pmake Techniques
13.6 The Way Things Work
14 Swat Stub
15 dumpgeo
16 cvtpcx
17 pvm


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Each Paragraph will have a different font that it uses.
However, all the fonts on the page /should/ appear to look the same because the only difference in the font is the file format.
There are four fonts total, so there will be 5 paragraphs - the last one is the fallback font so it is obvious if one font isn't working.
The font order will be: otf, woff, obf-otf, obf-woff.
This is a comparison paragraph, with font set as sans-serif by inline css


Click a name to read their story.
{% for name in names %} {{ name.name }} {% empty %}No one has shared a story yet.
{% endfor %}If we simultaneously live one hundred incongruous lives then how can we ever hope for anyone to truly understand us. It is human to want to be understood, it is human to err, to do things that we regret, to forgive, and to share our stories.