swap
`Prev `__
S
`Next `__
--------------
**swap**: vt.
1. [techspeak] To move information from a fast-access memory to a
slow-access memory (swap out), or vice versa (swap in). Often refers
specifically to the use of disks as virtual memory. As pieces of data or
program are needed, they are swapped into `*core* <../C/core.html>`__
for processing; when they are no longer needed they may be swapped out
again.
2. The jargon use of these terms analogizes people's short-term memories
with core. Cramming for an exam might be spoken of as swapping in. If
you temporarily forget someone's name, but then remember it, your excuse
is that it was swapped out. To keep something swapped in means to keep
it fresh in your memory: “I reread the TECO manual every few months to
keep it swapped in.” If someone interrupts you just as you got a good
idea, you might say “Wait a moment while I swap this out”, implying that
a piece of paper is your extra-somatic memory and that if you don't swap
the idea out by writing it down it will get overwritten and lost as you
talk. Compare `*page in* <../P/page-in.html>`__, `*page
out* <../P/page-out.html>`__.
--------------
+-------------------------+----------------------------+-------------------------------+
| `Prev `__ | `Up <../S.html>`__ | `Next `__ |
+-------------------------+----------------------------+-------------------------------+
| swab | `Home <../index.html>`__ | swap space |
+-------------------------+----------------------------+-------------------------------+


WITNESS LIST
Appropriations - S/C on Article III Committee
February 14, 2019 - 7:30 AM
Texas School for the Blind and Visually Impaired
On:
Daugherty, William (Tx school for the blind)
MacLaurin, Andy (LBB)
Saxe, Avery (Legislative Budget Board)
Registering, but not testifying:
On:
Darden, Pamela (Texas School for the Blind and Visually Impaired)
Texas School for the Deaf
On:
Bergeron, Jon (Self)
Bugen, Claire (Texas School for the Deaf)
Denenberg, Gary (Self)
Saxe, Avery (Legislative Budget Board)
Wedel, Justin (TSD)
Registering, but not testifying:
On:
Loyola, LeAnn (TSD)
MacLaurin, Andy (LBB)
Texas State University System
On:
Evans, Kenneth (Lamar University)
Howard, Lonnie (Lamar Institute of Technology)
Hoyt, Dana (Sam Houston State University)
Johnson, Thomas (Lamar State College Orange)
Kibler, William (Sul Ross State University)
McCall, Brian (Texas State University System)
Reynard, Betty (Lamar State College Port Arthur)
Trauth, Denise (Texas state university)
University of Texas System
On:
Bailey, Guy (UTRGV)
Benson, Richard (University of Texas at Dallas)
Eighmy (pronounced Amy), Taylor (UTSA)
Eltife, Kevin (UT System)
Fenves, Greg (The University of Texas At Austin)
Karbhari, Vistasp (University of Texas at Arlington)
Milliken, James (University of Texas)
Natalicio, Diana (Univ of Texas at El Paso)
1
WITNESS LIST
On:
Tidwell, Michael (The University of Texas at Tyler)
Woodley, Sandra (UT Permian Basin)
2


Let us know how you enjoyed your meal
* How likely is that you would recommend our restaurant to a friend?


@INPROCEEDINGS{Sarkar20,
author={Sarkar, Subhadeep and Papon, Tarikul Islam and Staratzis, Dimitris and Athanassoulis, Manos},
booktitle = {Proceedings of the ACM SIGMOD International Conference on Management of Data},
title={Lethe: A Tunable Delete-Aware LSM Engine},
publisher = {Association for Computing Machinery},
address = {New York, NY, USA},
url = {https://doi.org/10.1145/3318464.3389757},
year={2020},
pages={893-908},
numpages = {16},
keywords={TTL-driven compaction, interweaved storage layout, KiWi, FADE, compaction policy, compaction trigger, out-of-place deletes, LSM-trees, lethe, delete persistence, delete key, sort key, delete persistence latency, delete persistence threshold, compaction},
doi={10.1145/3318464.3389757},
location = {Portland, OR, USA},
series = {SIGMOD '20},
isbn = {9781450367356},
month={June}
}


Genesis 14:10
And the vale of Siddim was full of slime pits; and the kings of Sodom and Gomorrah fled, and fell there; and they that remained fled to the mountain.


6.3. Kernel Approximation¶
This submodule contains functions that approximate the feature mappings that correspond to certain kernels, as they are used for example in support vector machines (see Support Vector Machines). The following feature functions perform non-linear transformations of the input, which can serve as a basis for linear classification or other algorithms.
The advantage of using approximate explicit feature maps compared to the kernel trick, which makes use of feature maps implicitly, is that explicit mappings can be better suited for online learning and can significantly reduce the cost of learning with very large datasets. Standard kernelized SVMs do not scale well to large datasets, but using an approximate kernel map it is possible to use much more efficient linear SVMs. In particularly the combination of kernel map approximations with SGDClassifier can make nonlinear learning on large datasets possible.
Since there has not been much empirical work using approximate embeddings, it is advisable to compare results against exact kernel methods when possible.
6.3.1. Radial Basis Function Kernel¶
The RBFSampler constructs an approximate mapping for the radial basis function kernel.
The mapping relies on a Monte Carlo approximation to the kernel values. The fit function performs the Monte Carlo sampling, whereas the transform method performs the mapping of the data. Because of the inherent randomness of the process, results may vary between different calls to the fit function.
The fit function takes two arguments: n_components, which is the target dimensionality of the feature transform, and gamma, the parameter of the RBF-kernel. A higher n_components will result in a better approximation of the kernel and will yield results more similar to those produced by a kernel SVM. Note that “fitting” the feature function does not actually depend on the data given to the fit function. Only the dimensionality of the data is used. Details on the method can be found in [RR2007].
6.3.2. Additive Chi Squared Kernel¶
The chi squared kernel is a kernel on histograms, often used in computer vision.
The chi squared kernel is given by
Since the kernel is additive, it is possible to treat all components separately for embedding. This makes it possible to sample the Fourier transform in regular intervals, instead of approximating using Monte Carlo sampling.
The class AdditiveChi2Kernel implements this component wise deterministic sampling. Each component is sampled n times, yielding 2n+1 dimensions per input dimension (the multiple of two stems from the real and complex part of the Fourier transform). In the literature, n is usually choosen to be 1 or 2, transforming the dataset to size n_samples x 5 * n_features (in the case of n=2).
The approximate feature map provided by AdditiveChi2Sampler can be combined with the approximate feature map provided by RBFSampler to yield an approximate feature map for the exponentiated chi squared kernel. See the [VZ2010] for details and [VVZ2010] for combination with the RBFSampler.
6.3.3. Skewed Chi Squared Kernel¶
The skewed chi squared kernel is given by:
It has properties that are similar to the exponentiated chi squared kernel often used in computer vision, but allows for a simple Monte Carlo approximation of the feature map.
The usage of the SkewedChi2Sampler is the same as the usage described above for the RBFSampler. The only difference is in the free parameter, that is called c. For a motivation for this mapping and the mathematical details see [LS2010].
6.3.4. Mathematical Details¶
Kernel methods like support vector machines or kernelized PCA rely on a property of reproducing kernel Hilbert spaces. For any positive definite kernel function k (a so called Mercer kernel), it is guaranteed that there exists a mapping into a Hilbert space , such that
Where denotes the inner product in the Hilbert space.
If an algorithm, such as a linear support vector machine or PCA, relies only on the scalar product of data points , one may use the value of , which corresponds to applying the algorithm to the mapped data points . The advantage of using k is that the mapping never has to be calculated explicitly, allowing for arbitrary large features (even infinite).
One drawback of kernel methods is, that it might be necessary to store many kernel values during optimization. If a kernelized classifier is applied to new data , needs to be computed to make predictions, possibly for many different in the training set.
The classes in this submodule allow to approximate the embedding , thereby working explicitly with the representations , which obviates the need to apply the kernel or store training examples.
References:
| [RR2007] | “Random features for large-scale kernel machines” Rahimi, A. and Recht, B. - Advances in neural information processing 2007, |
| [LS2010] | “Random Fourier approximations for skewed multiplicative histogram kernels” Random Fourier approximations for skewed multiplicative histogram kernels - Lecture Notes for Computer Sciencd (DAGM) |
| [VZ2010] | “Efficient additive kernels via explicit feature maps” Vedaldi, A. and Zisserman, A. - Computer Vision and Pattern Recognition 2010 |
| [VVZ2010] | “Generalized RBF feature maps for Efficient Detection” Vempati, S. and Vedaldi, A. and Zisserman, A. and Jawahar, CV - 2010 |


Images add much-needed context and visual flair to Android applications. Picasso allows for hassle-free image loading in your application—often in one line of code!
Picasso.get().load("https://i.imgur.com/DvpvklR.png").into(imageView);
Many common pitfalls of image loading on Android are handled automatically by Picasso:
ImageView
recycling and download cancelation in an adapter.Adapter re-use is automatically detected and the previous download canceled.
@Override public void getView(int position, View convertView, ViewGroup parent) { SquaredImageView view = (SquaredImageView) convertView; if (view == null) { view = new SquaredImageView(context); } String url = getItem(position); Picasso.get().load(url).into(view); }
Transform images to better fit into layouts and to reduce memory size.
Picasso.get() .load(url) .resize(50, 50) .centerCrop() .into(imageView)
You can also specify custom transformations for more advanced effects.
public class CropSquareTransformation implements Transformation { @Override public Bitmap transform(Bitmap source) { int size = Math.min(source.getWidth(), source.getHeight()); int x = (source.getWidth() - size) / 2; int y = (source.getHeight() - size) / 2; Bitmap result = Bitmap.createBitmap(source, x, y, size, size); if (result != source) { source.recycle(); } return result; } @Override public String key() { return "square()"; } }
Pass an instance of this class to the transform
method.
Picasso supports both download and error placeholders as optional features.
Picasso.get() .load(url) .placeholder(R.drawable.user_placeholder) .error(R.drawable.user_placeholder_error) .into(imageView);
A request will be retried three times before the error placeholder is shown.
Resources, assets, files, content providers are all supported as image sources.
Picasso.get().load(R.drawable.landing_screen).into(imageView1); Picasso.get().load("file:///android_asset/DvpvklR.png").into(imageView2); Picasso.get().load(new File(...)).into(imageView3);
For development you can enable the display of a colored ribbon which indicates the image source. Call setIndicatorsEnabled(true)
on the Picasso instance.
The source code to the Picasso, its samples, and this website is available on GitHub.
<dependency>
<groupId>com.squareup.picasso3</groupId>
<artifactId>picasso</artifactId>
<version>(insert latest version)</version>
</dependency>
implementation 'com.squareup.picasso:picasso:(insert latest version)'
If you would like to contribute code you can do so through GitHub by forking the repository and sending a pull request.
When submitting code, please make every effort to follow existing conventions and style in order to keep the code as readable as possible. Please also make sure your code compiles by running mvn clean verify
.
Before your code can be accepted into the project you must also sign the Individual Contributor License Agreement (CLA).
Copyright 2013 Square, Inc. Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with the License. You may obtain a copy of the License at http://www.apache.org/licenses/LICENSE-2.0 Unless required by applicable law or agreed to in writing, software distributed under the License is distributed on an "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the License for the specific language governing permissions and limitations under the License.


API Docs - Main Index
API documentation for the Mime Capturing Mock module for Node.js test driven development. Go to the overview page for an introduction or the examples page for some in depth examples.
API documentation for the Mime Capturing Mock module for Node.js test driven development. Go to the overview page for an introduction or the examples page for some in depth examples.


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I STILL KNOW WHAT YOU DID LAST SUMMER Reviewed by Jamie Peck
The filmmakers would have at least made sense with the shorter "I Still Know," the longer "I Still Know What You Did Two Summers Ago" or the appropriate "Stupid People Getting Hacked to Bits." That last suggestion is the preferable one since the characters in this film do things that are the polar opposite of smart. For example, if your roommate is plagued by terrible nightmares as a result of being stalked and nearly murdered not long ago, would you sneak into her room late at night and hide in the closet, even if it was just to locate and borrow a cute little dress?
Probably not, but that's precisely what college student Karla (pop diva Brandy) does to best friend Julie (Jennifer Love Hewitt), resulting in the first in a long line of phony frights. Julie, you'll recall, was one of the sole survivors at the end of 1997's surprise hit "I Know What You Did Last Summer," after a slasher with a grudge to bear - it's a _long_ story - began trying to pick off her, her buddies and various others in their coastal Carolina village. In this installment, the plot picks up as Karla wins a trip to the Bahamas, and Julie, yet racked by guilt, decides that maybe a tropical getaway will help ease her mind.
Yeah, right. Their island paradise has room, of course, for one more in the form of the still-alive killer (Muse Watson) from the first film. He sports the same Gorton's Fisherman get-up, a heavy hat and rain slicker that mask his identity, but why he's still trying to stay anonymous is a mystery this movie never solves ... though I suppose his hook-hand would look funny protruding from the sleeve of a leisure suit. In a sense, that's the movie's glaring flaw - everybody knows who the bad guy is, thus evaporating the level of paranoid tension nicely sustained by its prequel.
The murders and attempted murders in that film were vivid and scary, but Trey Callaway's derivative "I Still Know" screenplay makes the Fisherman just as dumb as his pretty potential victims. When Julie lays blissfully unaware in a tanning bed, giving him a perfect chance to wreak vengeance once and for all, what does he do?  Even prequel "Summer" lovers might balk at how little there is here beyond sporadically amusing absurdity and a few neat-o shots of blood flowing from toned teenage flesh.
The innovative gallows humor that scribe (and "Scream" wunderkind) Kevin Williamson injected into "I Know"'s unfolding story is sorely missed, replaced with the grating antics of a white Rastafarian cabana boy who smokes weed and tosses off slang like "yo"; you'll cheer - not shriek - when he ends up with a pair of hedgetrimmers firmly implanted in his chest. If "I Know What You Did Last Summer," however effective, was just the kind of movie that those subversive "Scream" flicks poked fun at, then the deadly "I Still Know What You Did Last Summer" deserves a full-blown roasting on "Mystery Science Theatre 3000."
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
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Related links: index of all rec.arts.movies.reviews reviews


Kevin Goenadibrata
00
Hello! My name is Kevin and I'm a software engineer with a passion in design. Scroll down to know more about me and what I do. Currently, I'm an engineer at Qualcomm. I'm working with the 5G sub-6 team to research on UE Positioning. I'd love to talk with you about anything.
Programmer + Designer
01
My whole life, it has been me trying to balance the things around me between logically ordered and creatively spread out. I have been doing graphic designs, logo designs, UI/UX explorations since the day I have my first laptop. On the other hand, I firmly believe in how technology will connect and accelerate the things we do daily.
What I do on the side
02
Here are the things I worked on in the past. More stuff are coming and will update more on this list.
Let's grab a virtual coffee and chat
03
You can grab my resume here. I'm reachable through kevingoenadibrata(at)gmail(dot)com or just send me a mail through the form below! Thanks for reading!


live_thumb demo
Pure MJPEG example (should have base64 disabled)
Works on all modern browsers (not IE)
Websocket demo (should have base64 enabled)
Works on all modern browsers, and IE >= 93>


[INFO] 2021-02-18 21:45:31,708 com.thegoate.json.utils.tolist.JSONArrayToList: Start Up:
***************************Starting Up***************************
* com.thegoate.json.utils.tolist.JSONArrayToList:jsonArray:(0) *
*****************************************************************
[DEBUG] 2021-02-18 21:45:31,717 com.thegoate.utils.fill.serialize.DeSerializer: Build Pojo:The data source was not specified, defaulting to default
[DEBUG] 2021-02-18 21:45:31,749 com.thegoate.utils.fill.serialize.Cast: Cast:Cast utility found, building object.
[DEBUG] 2021-02-18 21:45:31,749 com.thegoate.utils.fill.serialize.collections.CastList: Cast List:Couldn't just cast to an list, now trying to build it from the data.
[DEBUG] 2021-02-18 21:45:31,749 com.thegoate.utils.fill.serialize.collections.CastList: Cast list:building from data.
[DEBUG] 2021-02-18 21:45:31,752 com.thegoate.expect.ExpectEvaluator: :starting executor to evaluate expectations.
[DEBUG] 2021-02-18 21:45:31,752 com.thegoate.expect.Expectation: Expectation:evaluating expectations.

[DEBUG] 2021-02-18 21:45:31,768 com.thegoate.utils.fill.serialize.collections.CastList: Cast List:Couldn't just cast to an list, now trying to build it from the data.
[DEBUG] 2021-02-18 21:45:31,768 com.thegoate.utils.fill.serialize.collections.CastList: Cast list:building from data.
[DEBUG] 2021-02-18 21:45:31,769 com.thegoate.expect.ExpectEvaluator: :starting executor to evaluate expectations.
[DEBUG] 2021-02-18 21:45:31,770 com.thegoate.expect.Expectation: Expectation:evaluating expectations.

[DEBUG] 2021-02-18 21:45:31,779 com.thegoate.utils.fill.serialize.collections.CastList: Cast List:Couldn't just cast to an list, now trying to build it from the data.
[DEBUG] 2021-02-18 21:45:31,779 com.thegoate.utils.fill.serialize.collections.CastList: Cast list:building from data.
[DEBUG] 2021-02-18 21:45:31,779 com.thegoate.utils.fill.serialize.Cast: Cast:Cast utility found, building object.
[DEBUG] 2021-02-18 21:45:31,780 com.thegoate.utils.fill.serialize.Cast: Cast:Cast utility found, building object.
[DEBUG] 2021-02-18 21:45:31,780 com.thegoate.utils.fill.serialize.Cast: Cast:Cast utility found, building object.
[DEBUG] 2021-02-18 21:45:31,780 com.thegoate.expect.ExpectEvaluator: :starting executor to evaluate expectations.
[DEBUG] 2021-02-18 21:45:31,781 com.thegoate.expect.Expectation: Expectation:evaluating expectations.


 Together with the community at Assembly, you can polish it into a product, ship it, and grow a decentralized, community-owned business around it. Anyone will be able to jump in and help out, and all contributions you approve will be rewarded an ownership stake that translates to a portion of future profits.
Maybe you've built something awesome, but you don't know how to talk about it. Maybe the back-end needs work.  Find and collaborate with people who have the skills to turn your idle side project into a glowing success.
You start out as the only person on the core team, so you guide vision, quality, and execution. Where this product goes is up to you, but a vast community of talented people are eager to work with you to get there.
Building products collaboratively is fun and rewarding. But, in addition, when your product starts earning money, profits will be distributed to everyone who owns part of it. It's up to you how to build this business, but when you do, there's no ceiling to the earnings you can achieve.
If you have a side project that needs a bit more momentum, now's the time to get it going.
Assembly products live beyond the confines of traditional companies. There are no investors, shareholders, or even employees. Instead, a global community creates and owns products, together.
The entire process is a collaborative effort, including vision, development, design, and marketing. Anyone can make a contribution and all contributions are rewarded with an ownership stake assigned within each team.
Collaborators participate in the success of their products. Each product has App Coins, which are earned by contributing work. When that product earns money, everyone gets a share of the profits.
More than 4 million people use products built by the Assembly community.
What kind of side project is good for this?
Anything that might solve a problem for someone in the world other than you. Even if you don’t see it scaling to a massive customerbase, you might be able to help some people out and make some money from your hard work.
What will happen if I put my side project on Assembly?
You’ll have the chance to bring people along to work on it, and talented people from the Assembly community might be interested in working with you as well. If you or anyone else in the community figures out how to monetize your side project, the revenue will go to you and other contributors.
You will be the leader of the product, and over time you can add more people to the core team if you'd like. You can build it how you like and at the pace you like, and it's up to you when and how to monetize it.
What if my side project is only half-built?
That’s ok! Lots of products have gone from idea to launch on Assembly – it’s a perfect place to get development on your product moving.
How much does Assembly cost?
In most cases, Assembly helps cover hosting costs, and in others, costs that you spend on a product can be tracked and will be reimbursed when the product earns revenue. Assembly earns a 10% share of revenues once the product is profiable to cover the costs of using the platform.
For more about what it's like to build a product on Assembly, visit assembly.com/start


In this post we will learn how to monitor computers and services with Nagios. This will allow us to receive timely and actionable alerts about issues in our infrastructure.
- What is Nagios.
- Nagios: How it works.
- Description of the scenario we are working with in this post.
- Installing Nagios.
- Monitoring services and computers.
- At-a-glance overview of our devices and services.
- Testing notifications.
- Closing thoughts.
What is Nagios.
Nagios is an application that monitors computers, services, networks and infrastructure. It sends alerts in case of trouble, and it sends notifications when the issue is resolved.
Unlike other commercial alternatives like SolarWinds, Nagios is both free and Open Source and it also offers the option of purchasing a support plan.
Nagios: How it works.
Nagios can obtain information about the monitored resources in two different ways:
-
Using the Nagios Agent: After deploying the Agent to the computers you want to monitor, these agents collect the information and perform the checks by themselves before sending them to the Nagios server. -The main advantage of this method is the flexbility it offers, since we can define custom checks and write code to monitor any resource we can think of. The disadvantage would be that we have to push the definition of these custom checks to the clients.
-
Agentless : The Nagios server uses the facilities provided by the device that is being monitored (for example, VMI or SNMP).
- The main advantage of this mode is that it reduces the complexity of our deployment, and it allows us to centralize all the configuration in the Nagios server. The disadvantage would be that it does not allow for custom checks, so if the device does not provide a facility for monitoring a resource we can’t monitor it this way.
Nagios is able to use both modes at the same time, combining the results from agent checks and from agentless checks.
Monitored service states, and transition flow between states.
The state of a resource is determined through two components:
- The state of the service or resource: OK, WARNING, UP, DOWN...
- The type of state the resource is in: soft or hard.
To prevent false positives caused by temporary circumstances, Nagios will perform the check a number of times before considering a problem to be “happening”. This number of retries is defined by the max_check_attempts variable, and if the limit is reached Nagios will change the issue from soft to hard. This also works in reverse, before marking an issue as solved the check is repeated this same number of times.
Unless we specify otherwise, notifications are only set when a resource is hard down.
We can write our own handler for these events to perfom custom actions depending on the resource state. For example, if the web server is soft down and the check has been retried 3 times already, we can trigger the deployment of a secondary instance of the web server and add it to the load balancer in anticipation of the main web server going down.
An in-depth description of the states is available in the manual.
A resource is “flapping”. What does “flapping” mean?
When a resource is rapidly and repeatedly transitioning between OK and a state that means an issue is happening, the resource is tagged as flapping. This could indicate a deeper issue, or be caused by perfectly normal conditions, for example we know for sure that the database becomes unresponsive at a certain time of the day because of heavy load, and we know it does not affect regular operations.
In any case, flapping would generate many notifications about the same issue. In order to mitigate this situation, we should increase max_check_attempts to a value that allows these false positives to fall under the threshold and be careful to not increase too much that issues go unreported.
Nagios contains logic that tries to address flapping, but given the nature of the problem it might not be enough to eliminate the problem in our specific environment.
Description of the scenario we are working with in this post.
We have three virtual machines in the same network, all three using Debian 8 (Jessie).
- nagiosHost: <IP_ADDRESS>, will function as the Nagios server. It will also host a MongoDB instance, and an SSH server.
- servidorLamp: <IP_ADDRESS>, will have a LAMP stack installed.
- escritorioUsuario: <IP_ADDRESS>, will be a desktop for the end-user to use.
This scenario can be deployed automatically through the use of this Vagrantfile, including all services and configuration.
Installing Nagios.
nrpe-server is the name of the Agent software that is installed in the monitored machines, and will send status reports back to the Nagios server as well as executing remote checks. As we have explained at the beginning, these checks can be customized by the administrator, and nagios-plugins is a package that contains many useful pre-defined checks. Later on we’ll explain how to install additional components that will enable us to monitor a MongoDB database and how to create our own custom checks to, for example, check for the existence of zombie processes.
To be able to run checks on-demand, we have to make the following change on /etc/nagios3/nagios.cfg
We must also change the owner and mode of these two directories, so the nagios service is able to write temporary files to them. If we were to not do this, we would get error messages along the lines of Could not stat() command file ‘/var/lib/nagios3/rw/nagios.cmd’.
We will implement these changes at the package manager level, to preserve them in case of updates.
We are also going to create a new user called ‘nagiosadmin’ with the password ‘nagios’ to be able to access the web panel. Then, we restart the service so all our changes go into effect.
Monitoring services and computers.
Services exist inside of devices, logically speaking. We are going to install the monitoring agent in nagiosHost, and the process is exactly the same to monitor the other two devices on our network: servidorLamp and escritorioUsuario.
Installing the monitoring agent.
We enable remote custom commands.
And we whitelist the server.
Adding devices to the monitoring list
conf.d is a folder that is consumed in its entirety to build the runtime configuration. We can split the settings however we see fit, following the criteria that fits our infrastructure best.
These steps are to be perfomed on nagiosHost.
/etc/nagios3/conf.d/nodes.cfg contains the list and addresses of the computers we are going to monitor. In our specific scenario, these would be its contents.
Devices belong to groups, and monitoring policies can be applied to groups. We are going to store these definitions in /etc/nagios3/conf.d/hostgroups_nagios2.cfg.
Defining services to monitor
/etc/nagios3/conf.d/services_nagios2.cfg contains the definitions of the services we wish to monitor across groups of devices.
/etc/nagios3/conf.d/nagiosHost.cfg
This file will contain the services we wish to monitor on nagiosHost: number of currently logged-in users, number of processes running and cpu load over time.
/etc/nagios3/conf.d/escritorioUsuario.cfg
Likewise for escritorioUsuario: this will contain the relevant definitions to check for zombie processes.
Since this is a custom check, we need to explicitly define it.
Adding custom service checks.
Custom service checks are defined in two parts: A mandatory definition in the Nagios server, and an optional second definition in the monitored device.
In the Nagios server, we have to define the custom command name that will be run through on the server itself.
In the monitored device, the definition of the custom command we are going to run inside the monitorized device itself.
If we need to gather information about the state of the monitored device that can only be collected by running code on the device, then the secondary definition becomes necessary.
For example, in our scenario we are going to check for zombie processes and if a MongoDB server is available. To gather information about the list of processes on the monitored machine, we have to run code on the machine itself. To ascertain whether a MongoDB server is up and accepting connections, we can do that from the outside by trying to connect to the MongoDB server like any other client would.
Checking for zombie processes.
Nagios server
/etc/nagios3/commands.cfg
Monitored device.
/etc/nagios/nrpe_local.cfg
Installing additional plugins to monitor other services.
To be able to monitor the state of the MongoDB database on nagiosHost, we are going to install nagios-plugin-mongodb. The process is very similar to adding a custom check: the only explicit difference is that we don’t have a check_mongodb command already available in the PATH, thus we have to install it first.
Installing nagios-plugin-mongodb
Since the plugin is coded in Python, the install process is very simple. We are going to clone the repository on the Nagios server, install the requirements and then the python MongoDB connector.
We add the relevant service definition to the configuration. Since we may add additional MongoDB servers in the future, it makes sense to define it as a service that applies to a group of hosts.
/etc/nagios3/conf.d/services_nagios2.cfg
commands.cfg
The syntax of check_mongodb.py is explained in the documentation, and each plugin we install may have a different syntax.
Setting up email notifications
Nagios has the ability to send notifications emails to contact groups, which obviously contain contacts. Let’s create a contact called root that will belong to the contact group admins.
/etc/nagios3/conf.d/contacts_nagios2.cfg will contain the list of contacts. It also contains the name of the commands used to send the notifications, which we’ll define later.
And /etc/nagios3/conf.d/contact_groups_nagios2.cfg will contain the list of groups, along with their memberships.
Now, we need to add to each service the groups that we’d like to be notified in case of issues using the contact_groups variable. For the SSH service, it would look like this.
Customizing the email contents and the sending methods.
In this post we will use _sendemail, to be able to send the emails through the use of GMail’s SMTP servers.
We have to adapt the email-sending syntax on commands.cfg.
You could further customize the command line to include other channels of communications. We could add SMS notifications through Twilio or messages through Slack, for example.
Variables $USER4 and $USER5 will contain our GMail username and password, used to authenticate against the SMTP server.
/etc/nagios3/resource.cfg
WARNING: These credentials are stored in plaintext. Besides using proper file permissions, it is recommended we use service credentials generated explicitly and uniquely for Nagios. In GMail’s case, we can enable 2-Factor authentication and generate an app password.
At-a-glance overview of our devices and services.
We can get a bird’s-eye view of our infrastructure through the use of the map view in the web interface.
If we click on any of the devices, we get a quick view of the services’ health.
Testing notifications.
Device offline.
What happens if escritorioUsuario is offline? The expected behaviour is that Nagios will retry the connection a number of times, and then notify us that we have a problem if the device is still not responding.
After a number of retries, Nagios marks the device as officially offline and proceeds to send an email notification.
After the machines comes back online, Nagios detects that the problem has been solved and notifies us.
Zombie process.
To generate a zombie process, we execute the following line on the terminal of escritorioUsuario.
MongoDB server availability.
If we were to stop the MongoDB service to simulate a failure state, we can see that Nagios detects that new connections are not being established and sends an email notification about the matter.
Closing thoughts.
It is of vital importance that we are aware of issues in our infrastructure before the customers are.
Nagios allows us to condense down all the information about the state of our deployment into an easily glanceable dashboard, and the time investment required to set it up is worth the peace of mind of knowing our infrastructure is healthy and if that were to change we would be the first ones to know.


ID
Photo
User Name
Title
Likes Count
Comment Count
Country
Action
{{row.id}}
{{row.first_name}} {{row.last_name}}
{{row.title}}
{{row.likes_count}}
{{row.comment_count}}
{{row.country}}


ChampionRequest
open class ChampionRequest
A class responsible for the querying and fetching of Champion
’s.
-
Looks up the
Champion
struct
for the specified identifier.Parameters:
- id: the champion identifier
Returns
A
Champion
struct, for the specified champion.Declaration
Swift
public static func getChampion(usingID id: Int) -> Champion
Parameters
id
the champion identifier
Return Value
A
Champion
struct, for the specified champion. -
Looks up the
Champion
struct
for the specified name.Parameters:
- championName: the champion name
Returns
A
Champion
struct, for the specified champion.Declaration
Swift
public static func getChampion(usingName championName: String) -> Champion
Parameters
championName
the champion name
Return Value
A
Champion
struct, for the specified champion. -
For all previously obtained champions, fetch the image from the dragon endpoint.
- Parameters:
- handler: the completion handler to be executed once complete.
Declaration
Swift
public static func getChampionImages(withCompletionHandler handler: @escaping () -> Void)
Parameters
handler
the completion handler to be executed once complete.
- Parameters:
-
Fetches the full list of champions from the static API endpoint.
- Parameters:
- shouldFetchImages: whether or not to automatically fetch the champion images. Defaults to
false
. - handler: the completion handler to be executed once complete.
- shouldFetchImages: whether or not to automatically fetch the champion images. Defaults to
Declaration
Swift
public static func getChampionList(withImages shouldFetchImages:Bool = false, withCompletionHandler handler: @escaping () -> Void)
Parameters
shouldFetchImages
whether or not to automatically fetch the champion images. Defaults to
false
.handler
the completion handler to be executed once complete.
- Parameters:


id
Order Number
Order Key
Status
Total
Total Tax
Customer First Name
Customer Last Name
Total Line Items
Product id
Mode of Payment
Paid Or Not
Processing...


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'), cmap='gray')
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), "input_real")
z_inputs = tf.placeholder(tf.float32, (None, z_dim), "input_z")
learning_rate = tf.placeholder(tf.float32, name="lr")
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)
"""
#For batch normalization
alpha = 0.1
keep_prob = 0.9
# TODO: Implement Function
with tf.variable_scope('discriminator', reuse=reuse):
x1 = tf.layers.conv2d(images, 64, 5, strides=2, padding='same')
x1 = tf.maximum(alpha * x1, x1)
#Deeper
x2 = tf.layers.conv2d(x1, 128, 5, strides=2, padding='same')
x2 = tf.layers.batch_normalization(x2, training=True)
x2 = tf.maximum(alpha * x2, x2)
x2 = tf.nn.dropout(x2, keep_prob=keep_prob)
x3 = tf.layers.conv2d(x2, 256, 5, strides=2, padding='same')
x3 = tf.layers.batch_normalization(x3, training=True)
x3 = tf.maximum(alpha * x3, x3)
x3 = tf.nn.dropout(x3, keep_prob=keep_prob)
flat = tf.reshape(x3, (-1, 4*4*256))
logits = tf.layers.dense(flat, 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
alpha = 0.1
with tf.variable_scope('generator', reuse=not is_train):
g1 = tf.layers.dense(z, 7*7*512)
g1 = tf.reshape(g1, (-1, 7, 7, 512))
g1 = tf.layers.batch_normalization(g1, training=is_train)
g1 = tf.maximum(alpha * g1, g1)
g2 = tf.layers.conv2d_transpose(g1, 256, 5, strides=2, padding='same')
g2 = tf.layers.batch_normalization(g2, training=is_train)
g2 = tf.maximum(alpha * g2, g2)
g3 = tf.layers.conv2d_transpose(g2, 128, 5, strides=2, padding='same')
g3 = tf.layers.batch_normalization(g3, training=is_train)
g3 = tf.maximum(alpha * g3, g3)
logits = tf.layers.conv2d_transpose(g3, out_channel_dim, 3, strides=1, padding='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
smooth = 0.1
g_output = generator(input_z, out_channel_dim)
disc_output_real, disc_logits_real = discriminator(input_real)
disc_output_fake, disc_logits_fake = discriminator(g_output, reuse=True)
disc_loss_real = tf.reduce_mean(tf.nn.sigmoid_cross_entropy_with_logits
(logits=disc_logits_real,
labels=tf.ones_like(disc_output_real) * (1 - smooth)))
disc_loss_fake = tf.reduce_mean(tf.nn.sigmoid_cross_entropy_with_logits(logits=disc_logits_fake,
labels=tf.zeros_like(disc_output_fake)))
generator_loss = tf.reduce_mean(tf.nn.sigmoid_cross_entropy_with_logits
(logits=disc_logits_fake, labels=tf.ones_like(disc_output_fake)))
discrim_loss = disc_loss_real + disc_loss_fake
return discrim_loss, generator_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
train_vars = tf.trainable_variables()
disc_vars = [var for var in train_vars if var.name.startswith('discriminator')]
gen_vars = [var for var in train_vars if var.name.startswith('generator')]
update_ops = tf.get_collection(tf.GraphKeys.UPDATE_OPS)
with tf.control_dependencies(update_ops):
gen_train_optimizer = tf.train.AdamOptimizer(learning_rate=learning_rate, beta1=beta1).minimize(g_loss, var_list=gen_vars)
disc_train_optimizer = tf.train.AdamOptimizer(learning_rate=learning_rate, beta1=beta1).minimize(d_loss, var_list=disc_vars)
return disc_train_optimizer, gen_train_optimizer
"""
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
_, image_width, image_height, image_channels = data_shape
input_real, input_z, lr = model_inputs(image_width, image_height, image_channels, z_dim)
discim_loss, generator_loss = model_loss(input_real, input_z, image_channels)
discrim_optimizer, generator_optimizer = model_opt(discim_loss, generator_loss, lr, beta1)
saver = tf.train.Saver()
losses = []
steps = 0
total_steps = epoch_count * batch_size
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):
# TODO: Train Model
steps += 1
batch_images *= 2
batch_z = np.random.uniform(-1, 1, size=(batch_size, z_dim))
_ = sess.run(discrim_optimizer, feed_dict={input_real: batch_images, input_z: batch_z, lr:learning_rate})
_ = sess.run(generator_optimizer, feed_dict={input_real: batch_images, input_z: batch_z, lr:learning_rate})
if steps == 1:
print('initial:')
show_generator_output(sess, 16, input_z, image_channels, data_image_mode)
if steps % 10 == 0:
train_loss_disc = discim_loss.eval({input_z: batch_z, input_real: batch_images})
train_loss_gen = generator_loss.eval({input_z: batch_z})
print("Epoch {}/{}.. ".format(epoch_i + 1, epoch_count), "Generator loss: {:.4f}. ".format(train_loss_gen),
"Dicrim loss: {:.4f}.".format(train_loss_disc))
losses.append((train_loss_disc, train_loss_gen))
if steps % 100 == 0:
show_generator_output(sess, 16, input_z, image_channels, data_image_mode)
saver.save(sess, './generator.ckpt')
return losses
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 = 128
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 = 0.0005
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.


lesson 3.1 introduction to HTML-understanding HTML and how is webpages created
Lesson 3.1 Eddie programming lesson
Lesson 3.1 : introduction to HTML-understanding HTML and how is webpages created
- introduction to HTML
- html elements and their definition
After my last lesson and some online research I learn a lot about HTML, CSS and JavaScript. For now we will talk about HTML and as we go along I will add in CSS and JavaScript. Ok so HTML basically stand for hyper text markup language, it is simply the building block for webpages, after it’s written the computer will translate it into what and how we want it to be for the user/client to see. For a more detailed explanation you can look at the screenshot below.
￼
And another picture of what a HTML document look like.
Another picture below to show you how the computer interpret it.
If you notice, inside a HTML document there are a lot of this bracket <> with character or wording inside, we call it HTML tag , don’t worry we will get to what they each mean as we go along the way. As most ppl will know h1 to h6 elements stands for the heading with h1 being the most important to h6 being the least. the p elements actually stands for the paragraph and as it is stated above, only those which is in the body elements will be shown when the browser interpret the html script.
￼
If you notice, for every opening tag, there is a closing tag, it is important to remember to add in the closing tag, even though sometimes when you did not put in a closing tag, the computer will still display it correctly but it is best to not rely on this as there are times when error will still occur, so do make it a habit.
HTML tag (when you put tag ,always remember to put opening tag and closing tag)
Computers nowadays are more clever or less strict, an example would be from what i learn from our last lesson on heading, last time if we want the correct heading we have to put an opening tag and closing tag of h1 then only will the computer understand and give us what we want of the heading, but now computer are more advanced, for example if we want our heading to be h6, let’s say we put in h6 in front of h1 , it will understand and give us a heading of h6, but note that it’s only applicable when we put it in the opening tag and NOT the closing tag, i tried to do it and it’s not able to run it. On another note, it’s best to put it the same instead of what we just tried as it would be confusing for other programmers to see and be seems as lazy. there are other more tag and I will post a few screenshot of it as a reference
￼ Below is some of the tag reference and their descriptions commonly use in HTML documents.
￼
And these are some of the attributes and descriptions use in HTML too, attributes provide additional information for HTML documents.
For now we will focus on other things, later on I will add in attributes and explain them as we add them in. Anyway, i will try out some simple stuff that I mention and I will add in more of the stuff that I learn as we go on step by step and try to keep it easier to understand.
￼
ok now that you know what does a heading look like, lets add in some paragraph.
after my last lesson and bit of research it’s actually not that hard to learn so long as you understand how it works, for now this will be it, I will add in color and font for my next minute.


Accepts a file:
URI and returns a regular file path suitable for use with the
fs
module functions.
Install with npm
:
$ npm install file-uri-to-path
var uri2path = require('file-uri-to-path');
uri2path('file://localhost/c|/WINDOWS/clock.avi');
// "c:\\WINDOWS\\clock.avi"
uri2path('file:///c|/WINDOWS/clock.avi');
// "c:\\WINDOWS\\clock.avi"
uri2path('file://localhost/c:/WINDOWS/clock.avi');
// "c:\\WINDOWS\\clock.avi"
uri2path('file://hostname/path/to/the%20file.txt');
// "\\\\hostname\\path\\to\\the file.txt"
uri2path('file:///c:/path/to/the%20file.txt');
// "c:\\path\\to\\the file.txt"
(The MIT License)
Copyright (c) 2014 Nathan Rajlich<EMAIL_ADDRESS>Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the 'Software'), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions:
The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software.
THE SOFTWARE IS PROVIDED 'AS IS', WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.


Eagle rush helps Fleetwood to play-off win at Nedbank Challenge
Englishman Tommy Fleetwood carded three eagles in a scintillating final round 65 to claim a play-off victory over Swede Marcus Kinhult at the Nedbank Golf Challenge on Sunday.
SUN CITY, South Africa –: Englishman Tommy Fleetwood carded three eagles in a scintillating final round 65 to claim a play-off victory over Swede Marcus Kinhult at the Nedbank Golf Challenge on Sunday.
Fleetwood started the day six shots behind overnight leader Zander Lombard but surged up the leaderboard and into a play-off, which he won on the first extra-hole as Kinhult was off target with his drive and could only card a bogey five.
Fleetwood rolled in a five-foot put in front of a packed gallery at the Gary Player Country Club to lift the trophy, having finished tied with Kinhult on 12 under-par for the tournament.
The world number 18, and highest ranked player in the field, claimed the US$2.5-million first prize and his first tournament win since the Abu Dhabi HSBC Championship in January 2018.
“I made a great up and down on one and without that the day could have been completely different. I was also really proud of how I played 17 and 18,” Fleetwood said.
“I was getting more and more nervous (as the round went on). Being a golfer these days you have the chance at a young age to set your family up for life … it’s just really cool when you win a tournament.”
All of Fleetwood’s eagles came on par-five holes, but as was the case all week he battled on the shorter holes and bogeys on 11th, 12th and 16th halted his victory charge, though he still carded comfortably the low round of the day.
Kinhult birdied his first three holes on Sunday and was much more measured in his play, with five birdies and a bogey on the par-three seventh as he secured a 68.
The top three on the overnight leaderboard all wilted in their challenge on Sunday, as Belgian Thomas Detry (74) tied for third, Louis Oosthuizen (75) finished tied sixth, and Zander Lombard (77) tied for eighth.
Race to Dubai leader Bernd Wiesberger was in a tie for third after carding 70 on Sunday for a total of eight under-par.
(Reporting by Nick Said, editing by Pritha Sarkar)


{% extends 'book/base.html'%} {%block body%} {% load static %}
Welcome to Biblio!!
These are the 20 most recently added books! Here you can request to borrow a book by clicking 'Request' button so that the request email will be automatically sent out.
There is no book in a library


By Claire Robinson
Receive money in any currency with no feesThe world is getting smaller and we’re becoming more mobile. So why should you be forced to only receive money in a single …
Take your financial life online. Your Easybank account will be a one-stop-shop for spending, saving, budgeting, investing, and much more.
Why choose Easybank?
We leverage Open Banking to turn your bank account into your financial hub. Control your finances like never before.
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Our modern web and mobile applications allow you to keep track of your finances wherever you are in the world.
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See exactly where your money goes each month. Receive notifications when you’re close to hitting your limits.
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Manage your savings, investments, pension, and much more from one account. Tracking your money has never been easier.
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Receive money in any currency with no feesThe world is getting smaller and we’re becoming more mobile. So why should you be forced to only receive money in a single …
Treat yourself without worrying about money
Our simple budgeting feature allows you to separate out your spending and set realistic limits each month. That means you …
 This is why we don’t charge any fees on purchases while you’re abroad. We’ll even show you …
By Claire Robinson
Our invite-only Beta accounts are now live!After a lot of hard work by the whole team, we’re excited to launch our closed beta. It’s easy to request an invite through the site.


[Erowid Note: 40 mgs of 2C-E is considered a very high dose, see 2C-E Dose Chart. Without further detailed information about how the measurements were derived, it is reasonable to assume that this dose is either misinformed or overstated.]
It was during the summer of 06, I was 18 and very what I thought was VERY experienced in psychedelics, until that night.
My background in psychedelics is pretty extensive. I had taken the sacrament of mushrooms soo many times that I couldn't ever count. Too many journeys, and so much knowledge gained that to ever put words to them would be an injustice to the whole thing. The same with LSD. I had found a vial and basically disappeared for quite sometime but that was a couple years ago. I liked to trip by myself and have been since the beginning. I'd say about 99% of my trips were alone or in the company of sober people who really didnt know if I was tripping or not and didnt care if I was.
Then I met my buddy who we will call D. D and I had known each other as we used to live in the same neighborhood. We didnt ever really hang out but I got him to smoke weed i think for like one of his first times. Then, we both lost track of each other. Eventually he got an apartment and we started hanging out all the time. Been through a lot of the same she mentally and spiritually. There was a dank bond between us and we always chilled.
Well I moved to the other side of town and didnt see him very much.  It was pretty shitty to say the least but it saved my life. Any who, I ended up randomly getting a bag from him and we hung out ever since that day. I started tripping with him for the first time that I've ever tripped with another person. The rest was history. We had many journeys together since that fateful night.
I was reading about 2ce and a bunch of other research chemicals at the time and D just so happened to pick up 2ce and some 5MEO-DMT. My parents were out of town up at their condo in a vacation spot. I decided host a tripping party. It was a great idea.
We dose about 40 mgs at 11:11 pm and i am tripping at around 11:45. Everything is very colorful, shifting and moving. There's and odd 4th dimension to tripping on 2ce, and lots of tracers. From what I gather, 2ce (becuz it a lot since this night) is a light-based trip, meaning the hallucinations are more intense depending on how much light your eyes take in and if ur sitting in the dark or in a daytime setting. I prefer the dark with a lot of lights like glowsticks or just walking around at night near town. We stayed in tonight and kept the setting controllable.
11:45- I feel my consciousness changing and I feel heavy.  He got a little dose and was the tester. I went next. We loaded it on some foil, about 35mgs premeasured, and D lit under it. I used 3/4 of a plastic bottle to catch the smoke and rip that hit like a rock. I had no idea what I was in for.
Within seconds all the smoke was in my lungs and I held it in for quite sometime. Before I could blow the smoke out I coughed out 'OMG!  The room started shaking.  All the pieces fell, and everything went black. A light kind of like the light of an equalizer visualising music in the shape of a line, in the color of blue, started shaking in the tone of a B flat, which i made to be the hum of earth, but that happens to be 12 lower than the human ear can hear. This geeked me out.
I was tripping so hard! Then sound started resonating and getting louder and louder and louder, I was suddenly shot off like out of a cannon. I was flying through outer space and different worlds with ridiculously amazing colors and patterns in the shape of sacred geometry. I come to a bunch of galaxies which fractal/zoom out to a million galaxies in encased in one large circle. I had become the creator of the universe. I was able to see through his eyes.
I saw my life and death and the truth/purpose/meaning of life and death. It blew my mind. No one person should be able to see and experience these things. Its just not possible. That freaked me out a lot. It was all so intense and fast that I dont remember any of it except that I was shown it.  I ran upstairs only to find out it feels like I am floating through limbo and a different dimension, tripping so hard, to go puke in my sink. It felt very good.
 In general, mad sack trippage. I tried to convince my buddy D that he was and wouldnt ever be prepared for such a hit, and that maybe he shouldnt do it because it was so scary/enlightening. Of course, this made him want to do it more, him being like me. He loved it and had the same ideas i had about it. I played guitar during his trip which he said made it awesome and influenced his whole trip. We tripped until around 8:30 or 9 in the morning. Everyone went to bed and then we awoke at about 4 to discuss the trip.
All in all, it was the most defining moment of my life. It was so scary but eventually it enveloped/encompassed my whole life once I realized how awesome it was. I am obsessed forever with the power and the glory.
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.


Registers a JavaScript background task for the Time Zone Change system event. The background task runs whenever the Time Zone changes.
Unregistered
Progress:


to the shipcloud developer portal where you - the developer - will hopefully get all the information you
need to get started with integrating shipcloud into your own service, shop, app or other crazy idea.
If there's anything missing in this portal, you've found a typo, bug or something isn't clear, the developer
portal is build as a public repository on github. Feel free to fork it, change things, make a pull request or
even run your own local version of it.


Connecting to game...
"I'm going to pick the third-most obvious one" - Andreas
"I have an obscure hint: how much do you know about Polynesian agricultural societies?" - Ben
"Your hint is 'numan'?! What does that even mean?" - Sandra
"Two clues left? Only a real chicken would pass" - Michael


-
Internal APIs with Fargate
A walk through on building an internal API using Fargate -
Halloween horror with AWS Savings Plans
A story about how purchasing savings plans can go badly wrong -
Welcome to my blog
What I plan on blogging about
- •
- 1
- •


A-Pizza-Pie-Ya
Size:
Personal
Medium
Large
Extra Large
Crust:
Plain
Garlic Butter
Cheese Stuffed
Spicy
House Special
Sauce:
Marinara
White
Barbeque
No sauce
Cheese:
Regular Cheese
No Cheese
Extra Cheese
Meats:
Pepperoni
Sausage
Canadian Bacon
Ground Beef
Anchovy
Chicken
Veggies:
Tomatoes
Onions
Olives
Green Peppers
Mushrooms
Pineapple
Spinach
Jalepeno
Place Order
Clear Order


DEPOSIT
balance
$23.00
Recharge Amount
Yuan
Please select a recharge method
Paypal
Online Banking
The Line Remittance
Select Bank


Absolute period (from S to E)
Relative period (last N days)
From: To:
Last
days;
Accuracy:
meters
Refresh


Results of the statistical tests comparing the observed data and synthetic data generated by the Long Ashton Research Station Weather Generator (LARS-WG) with the numbers of tests revealing significantly different results at the 5% significance level.
a: indicates seasonal wet/dry series distributions tested by the Kolmogorov–Smirnov (K–S) test. b: indicates daily precipitation distributions tested by the Kolmogorov–Smirnov (K–S) test. c: indicates monthly mean of precipitation tested by the t-test. d: indicates monthly variances of precipitation tested by the F-test. e: indicates daily minimum temperature distributions tested by the Kolmogorov–Smirnov (K–S) test. f: indicates monthly mean of daily minimum temperature tested by the t-test. g: indicates daily maximum temperature distributions tested by the Kolmogorov–Smirnov (K–S) test. h: indicates monthly mean of daily maximum temperature tested by the t-test.


Fancy search input
Vanilla.js implementation - because vanilla is the best
Start typing and use omnibox by hitting
Tab
key.
Home
Check source on


The KDC will validate the authentication if it can decrypt the timestamp with the long-term user key (for RC4, the NTLM hash of the user password)
It uses TGT representing the user in the domain, for a specified period


Send more kitteh on routers!
CDN / IO by Fastly
DMCA
Welcome to Cats on routers!
Puuurouse your choice of cats... on.... routers...
Previous
Next
Want more Cats?
https://imgur.com/search?q=cats


The Gift of Giving
Pia and I have been together for over 6 years now. During that time, we have accumulated basically every household item you could need. Our apartment can't hold anymore stuff. But if you would like to congratulate us with more than words, in lieu of a registry, we will be accepting cold hard cash. Just click the amount you would like to give below, fill out the form, and click submit. Be sure to leave your name so that we can send you a thank you note later.


∘ Human Interest Stories About The Naval Undersea Warfare Center ∘
1910's History
Home
About
1980's History
To play this video clip, your browser needs to support HTML5.


Dragon Knight
Shriekwing
Huntsman Altimor
Sun King's Salvation
Artificer Xy'mox
Council of Blood
Hungering Destroyer
Lady Inerva Darkvein
Sludgefist
Stone Legion Generals
Sire Denathrius


[gecode-users] Max not bound consistent?
Jean-Noël Monette
jean-noel.monette at it.uu.se
Mon Apr 16 11:00:19 CEST 2012
Hello,
The "bound consistency" max constraint does not seem to enforce bound
consistency. Indeed, with x = {1, 1, [1..2]}, and y = 2, the constraint
"max(home, x,y,ICL_BND)" should enforce x[2] = 2, but does not modify
the domains (after a call to status()). Is it the expected behavior
(because of the cost to check this case or any other reason), or a bug?
Thank you for your answer,
Jean-Noël Monette
More information about the users
mailing list


The system’s architecture is a traditional
NLG pipeline, adapted from (Reiter and Dale, 1997). It is
designed with three distinct and well-defined modules.
The text planner module receives the input CMML expression and filters
out the information that will be included in the text. The file is read line by
line and a list of the expression’s tokens is produced. This token list
is passed on to the sentence planner.
The sentence planner’s job is to organize
the overall structure of the intended sentence. This module takes the list of tokens
as input and arranges them into an Abstract Syntax Tree (AST). The root of each sub-tree is the operator,
the child nodes are its operands. The completed AST is handed over to
the linguistic realiser.
The linguistic realiser module will take
the output from the sentence planner and generate a grammatically correct and
complete sentence using isiZulu templates.
The
received AST is depth-first traversed, fetching a template via the name of the
operator and filling it in for each sub-tree.
To use the templates, the realiser opens a text file where the data for each template is stored and loads the file line-by-line into template objects. These objects store all the information needed to create and change a template’s grammar depending on how its verb is used (as a primary, secondary or an adjoining verb).
created with
Website Builder Software .


All routines in the Rand unit are exported qualified (and thus must be prefaced with "Rand.").
| Real | Returns a random real number. | |
| Int | Returns a random integer. | |
| Reset | Sets the seed in the default sequence to a default value. | |
| Set | Sets the seed in the default sequence to a specified value. | |
| Next | Returns a random real number from a sequence. | |
| Seed | Sets a seed in a sequence. |


--- layout: post title: Successful Entrepreneur in AZ date: 2012-02-17 12:31:50.000000000 -06:00 type: post published: true status: publish categories: - Ruby on Rails tags: [] meta: _edit_last: '15714693' publicize_results: a:1:{s:7:"twitter";a:1:{i:199393780;a:2:{s:7:"user_id";s:11:"broberts_az";s:7:"post_id";s:18:"170591305745969152";}}} _wpas_done_twitter: '1' author: login: broberts65 email<EMAIL_ADDRESS>display_name: Bob Roberts first_name: '' last_name: '' ---
Just wanted to do a quick link for an article about a local AZ man and his success story in raising $1.5 million for his tech startup written by a friend of mine. You can read it here Entrepreneurship Series: Interview with Paul Kenjora or here NOW THAT’S CALLED BOOTSTRAPPING: WHY ONE ENTREPRENEUR STOPPED PURSUING INVESTORS


ACT OF REPARATION TO THE IMMACULATE HEART OF MARY
O Most Holy Virgin, and Our Mother, we listen with grief to the complaints of your
Immaculate Heart surrounded with the thorns placed therein at every moment by the
blasphemies and ingratitude of ungrateful humanity. We are moved by the ardent desire
of loving you as Our Mother and of promising a true devotion to Your Immaculate Heart.
We therefore kneel before You to manifest the sorrow we feel for the grievances that people
cause You, and to atone by our prayers and sacrifices for the offenses with which they return
your love. Obtain for them and for us the pardon of so many sins.
Hasten the conversion of sinners that they may love Jesus Christ and cease to offend the Lord,
already so much offended. Turn you eyes of mercy toward us, that we may love God with all our
heart on earth and enjoy Him forever in Heaven.
|


Finnish minister, 34, to become youngest PM
Sanna Marin will become the world’s youngest sitting prime minister, according to Finland’s biggest newspaper.
A 34-year-old transport minister is set to become Finland’s youngest prime minister ever and its third female government leader.
Finland’s ruling Social Democratic Party council voted 32-29 to name Sanna Marin over rival Antti Lindtman to take over the government’s top post from incumbent Antti Rinne.
Having emerged as Finland’s largest party in the April election, the Social Democrats can appoint one of their own to the post of prime minister in the Nordic nation of 5.5 million.
Ms Marin has been the party’s vice chairwoman, a lawmaker since 2015 and served until this week as the minister for transport and communications.
According to Finland’s biggest newspaper Helsingin Sanomat and the Ilta-Sanomat tabloid, Ms Marin will become the world’s youngest sitting prime minister.
Finland currently holds the European Union’s rotating presidency until the end of the year.
Politicians are likely to approve the appointment of Ms Marin and her new government quickly so she can represent Finland at the December 12-13 EU leaders’ summit in Brussels.
Mr Rinne stepped down on Tuesday after a key coalition partner, the Centre Party, withdrew its support, citing lack of trust.
The Centre Party also criticised Mr Rinne’s leadership skills prior to a two-week strike by the country’s state-owned postal service Posti in November that spread to other industries, including the national flag carrier Finnair.
Mr Rinne’s resignation prompted the formal resignation of a coalition of the Social Democrats and the Centre Party and three junior partners: the Greens, the Left Alliance and the Swedish People’s Party of Finland.
The Social Democrats and the four other coalition parties said they are committed to the government programme agreed upon after the April election and will continue in Ms Marin’s new government.
The new government will still have a comfortable majority of 117 seats at the 200-seat Eduskunta (parliament).
The Social Democrats said they are seeking to have Mr Rinne, a former trade union leader, become the parliament’s vice speaker.
He also plans to stay on as the Social Democrats’ chairman until a party congress next summer.


|
SmartLock
1.0.0a
|
Public Member Functions | |
| UserDto | createUser (CreateUserDto userData) |
| Used to create a User. More... | |
| UserDto | getUser (Long id) |
| Searches a user by his Id and returns it. More... | |
| Long | getMyID () |
| Gives the Id for the user who requested this. More... | |
| List< UserWithoutLocksDto > | getAllUsersThatCanAccessToThisLock (Long lockId, Long userId) throws NotFoundException |
| For a specific Lock returns all the users who have permission to access it. More... | |
| void | leaveFromThisLock (Long lockId, Long userId) throws NotFoundException |
| Removes the User that requested it from a Lock. More... | |
| List< LockDto > | getAllLocksThisUserCanAccess (Long userId) |
| Get's all the Locks added to the library of the given user, identified by his Id. More... | |
| UserDto com.smartlock.server.user.service.UserService.createUser | ( | CreateUserDto | userData | ) |
Used to create a User.
| userData | DTO containing the data for the user to be created. UserDTO containing the info of the successfully created user. |
Implemented in com.smartlock.server.user.service.UserServiceImpl.
| List<LockDto> com.smartlock.server.user.service.UserService.getAllLocksThisUserCanAccess | ( | Long | userId | ) |
Get's all the Locks added to the library of the given user, identified by his Id.
| userId | the user's Id |
Implemented in com.smartlock.server.user.service.UserServiceImpl.
| List<UserWithoutLocksDto> com.smartlock.server.user.service.UserService.getAllUsersThatCanAccessToThisLock | ( | Long | lockId, |
| Long | userId | ||
| ) | throws NotFoundException |
For a specific Lock returns all the users who have permission to access it.
Only the admin can ask for this information.
| lockId | the Id for the lock |
| userId | the user, presumably the lock owner, who requested the information. |
| NotFoundException | when the Lock does not exist. |
Implemented in com.smartlock.server.user.service.UserServiceImpl.
| Long com.smartlock.server.user.service.UserService.getMyID | ( | ) |
Gives the Id for the user who requested this.
Implemented in com.smartlock.server.user.service.UserServiceImpl.
| UserDto com.smartlock.server.user.service.UserService.getUser | ( | Long | id | ) |
Searches a user by his Id and returns it.
| id | corresponding to the user to be searched. UserDTO containing the info of the found user. |
Implemented in com.smartlock.server.user.service.UserServiceImpl.
| void com.smartlock.server.user.service.UserService.leaveFromThisLock | ( | Long | lockId, |
| Long | userId | ||
| ) | throws NotFoundException |
Removes the User that requested it from a Lock.
Can NOT be performed by the Lock owner.
| lockId | the Id of the Lock that the user wants to remove from his library. |
| userId | the Id for the user that performed the action. |
| NotFoundException | when the Lock does not exist. |
Implemented in com.smartlock.server.user.service.UserServiceImpl.


--- layout: default ---
There are installation packages available for Linux and Windows:
Both installers will configure the server to start automatically when your computer boots.
There is also a separate portable version that makes no changes to your system, and will not automatically boot the server:
This variant works on any operating system, so long as Java is installed. To run it,
extract the package contents and double-click on Server.jar
. If any firewall notices appear, click
Allow
.
If the mouse cursor disappears while using this version on Ubuntu, consider switching to the installer. It contains a script that fixes the problem during installation. Alternatively, you can fix it yourself using the method described in this thread.


Passionate about startups, internet and media -- and areas where these intersect.
I seek opportunities in startup environments or similar small teams, that will allow me to use my passion for the above in helping disruptive projects succeed. I have proven experience in handling ambiguous responsibilities, and delivering results.
Involved with multiple technologies, including storage, operating systems, and application design. Free and open source software developer, with significant contributions in multiple projects.
Proven track record in building and maintaining open and collaborative communities. Worked with global audiences, spoken at conferences and shows internationally.
Have handled projects, and managed small teams in building projects from prototype to production. Can easily handle discussions with various stakeholders, and ensure all the gears run smoothly.
Understand the media industry. Been in the trenches with film-making, and understand the challenges that the digital age brings to monetizing artistic works.
Joined the startup early, among the first few employees, which allowed me to implement multiple projects and roles.
Ownership in almost all parts of the project.
Maintain Full stack app all the way from a Coffeescript/Backbonejs powered frontend, to the Ruby on Rails server, to multiple services on the AWS cloud.
Joined the startup early, among the first few employees, which allowed me to implement multiple projects and roles.
NCP: The lead of the Nexenta Core Platform, the open source storage centric distribution by Nexenta. Oversaw development of OS, online community outreach.
Built NCP - debian packaging, bash scripting, and C.
Prototyping: Developed applications, tools and technologies from ground up for internal research and development.
Global Outreach: Spoke and represented the project at multiple conferences spanning DebConf (New York), OpenSolaris conferences (Mountainvew, Germany, France), and Foss.in (India).
Operations: Oversaw the Indian storage business. Worked on scouting new VARs, partners, and clients.
Web and IT: Maintained all web properties for the initial years including, corporate website, partner outreach and CRM. Implemented licensing technology and management for commercial product. (Joomla/Wordpress/elgg/php/python).
Noting a lack of good open source screenwriting options, I rebooted the Blyte screenwriter with it's original author, and renamed it Trelby. I implemented major UI modifications, import/export of the industry standard FDX format and HTML, binary installers for Windows/Ubuntu, undo/redo logic for the custom Text control, scene navigator, PDF watermarking, smooth scrolling, and multiple bugfixes. Currently also working on building a user and developer community around the project and taking on the incumbents.
Trelby is written in python using the wxWidgets multi-platform UI library. [website]
Ported Belenix operating system to boot via USB. Received local and international media attention. Later also integrated this into the upstream OpenSolaris project.
Served as the technical lead of the campus ambassador program for Sun Microsystems. Trained and evangelized open source technologies in OpenSolaris, including ZFS, Dtrace.
Built a wirelessly controlled robotic car with embedded spots technology. Presented in national conferences, and participated in robotic competition in BITS Pilani, Goa. Used Sun Spots technology.
Met then Sun CEO Jonathan Schwartz, and the Executive Leadership Team to consult and provide feedback on the education and campus outreach effort. Feedback was highly appreciated by the team and immediate manager.
A self-taught filmmaker. Conceived, wrote and directed multiple shorts and films. Featured at international film festivals.
IMDB profile: http://www.imdb.com/name/nm4890577/
Coming from a startup background, I prefer working in small teams. More flexibility and independence allows me to be more productive.
I want to build my career towards Working on web-based technologies and challenges.
Have experience with UI design from ground up, taking the user's usage pattern as the primary design motivation. An example design for a note-taking application.
Cryptography and meme-research are areas of considerable interest.
I have experience writing and designing comics!
I maintain a popular blog at gulecha.org.
My github account contains some of the other small utilities I've written.
Anil Gulecha — last update: Apr 2015


DEATH AND THE MAIDEN A film review by Ben Hoffman Copyright 1995 Ben Hoffman
There are three main characters in this extraordinary film that is based on the play by Ariel Dorfman. Far more important than the story that unfolds is a universal theme that the film explores so very well.
Unlike most films where bits and pieces that take place in one location are shot and later spliced to make the movie flow, Roman Polanski opted to film DEATH AND THE MAIDEN chronologically. Taking advantage of the fact that most of the movie takes place in one room, Polanski shot the film as the story would have really unfolded.
"Somewhere" in Latin America, at a lonely beach house, the gripping adventure begins on a stormy, dark night. Paulina Escobar (Sigorney Weaver), is at home when her husband, Gerardo (Stuart Wilson) is dropped off at their home. With them is a stranger, a Dr. Roberto Miranda, who has given her husband a lift when Gerardo's car broke down. He is invited into their home, thanked and given a drink to help him warm himself and dry up.
This unspecified Latin American country, long a dictatorship, had just recently been overthrown. Paulina's husband, an attorney, has been appointed to head a commission to find those who had worked on death squads for the dictatorship, and now to bring them to justice. As Dr. Miranda is exchanging small talk with the host and hostess, Paulina suddenly becomes aware that the doctor is the one who 15 years ago had raped her in jail, had applied live electrodes to various sensitive parts of her body as well as to other women prisoners.
Paulina gets Gerardo aside and tells him who Dr. Miranda is. He tells her it happened fifteen years ago and she cannot be sure. As the one appointed by the new government to find the culprits, he certainly does now want to engage in the same flimsy tactics the old regime used to inflict on their prisoners.
The cast is superb. Wilson as the very reasonable lawyer-husband who tries to reason but not help his wife without absolute proof; Ben Kingsley as the apparently shocked and bewildered man now bound hand and foot to a chair, is helpless. He says that at the time of the incidents described by Paulina, he was in Scotland studying at a university and nowhere near Latin America. Paulina, for her part, is ready to shoot him. She recognizes his features full well. She remembers the taste of the skin on his neck when she tried to bite him off ... but she cannot at this point convince her husband to help her.
The film is a nail-biter. The ending is even better. You will not want to miss this one. Polanski has proven once again, if proof were needed, that he can make a movie with the best of them.
4 bytes 4 Bytes = Absolutely must see. 3 Bytes = Too good to be missed. 2 Bytes = So so. 1 Byte = Save your money.
Ben Hoffman
.
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


my mm2 instance is using 100% CPU all the time
if i do sudo strace -f -p 68941 (68941 is the PID of mm2) i see mostly this messages
```
[pid 68949] futex(0x5581daa1faa8, FUTEX_WAIT_PRIVATE, 0, {tv_sec=0, tv_nsec=705617}) = -1 ETIMEDOUT (Connection timed out)
[pid 68949] futex(0x5581daa29ec0, FUTEX_WAKE_PRIVATE, 1) = 0
[pid 68949] recvfrom(154, 0x7ff2f0000e70, 8192, 0, NULL, NULL) = -1 EAGAIN (Resource temporarily unavailable)
[pid 68949] recvfrom(186, 0x7ff2f0003080, 8192, 0, NULL, NU...


Widgets test
link
Collectives I support
Backers/sponsors widget for apex
Events widget
Collectives widget for host brusselstogether


二宮
流行り
The HTML Mark Element (<\mark>) represents highlighted text, i.e., a run of text marked for reference purpose, due to its relevance in a particular context. For example it can be used in a page showing search results to highlight every instance of the searched-for word.
The HTML <\samp> element is an element intended to identify sample output from a computer program. It is usually displayed in the browser's default monotype font (such as Lucida Console).
The HTML Code Element (<\code>) represents a fragment of computer code. By default, it is displayed in the browser's default monospace font.


Saudi Arabia convicts 18 people of bribery and fraud - SPA
RIYADH (Reuters) - Saudi Arabia has convicted 18 people, including government officials and private sector employees, of bribery, fraud and abuse of office, state news agency SPA said on Tuesday, without identifying them.
The rulings followed an investigation by the public prosecutor, who presented “strong evidence” of corruption, SPA said. Punishments included jail sentences of up to 16 years and monetary fines totaling 4 million riyals ($1.07 million).
The new head of the kingdom’s anti-corruption commission pledged in August to go after graft by ordinary government employees, following a high-profile campaign two years ago that netted princes, ministers and top businessmen while unsettling some foreign investors.
The SPA report provided few details about the case in which 18 people were convicted, but said they included an executive-level government official who had received bribes from a businessman, abused his office and participated in fraud.
The businessman and employees of both men were also netted.
Crown Prince Mohammed bin Salman has defended the anti-corruption sweep he led in 2017, calling it “shock therapy”, as he tries to overhaul the Arab world’s largest economy and transform Saudi society.
Critics said it amounted to a power play and a shakedown of the political rivals of Saudi Arabia’s de facto ruler.


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nanocad
|
#include <Sys.h>
Public Attributes | |
| bool | valid |
| bool | visible |
| int | changes |
| bool | changed |
| Vertex * | vertex |
| unsigned int | vertex_cnt |
| Triangle * | triangle |
| unsigned int | triangle_cnt |
| bool Geom::changed |
| int Geom::changes |
| Triangle* Geom::triangle |
| unsigned int Geom::triangle_cnt |
| bool Geom::valid |
| Vertex* Geom::vertex |
| unsigned int Geom::vertex_cnt |
| bool Geom::visible |