Real Time Graphics Binary Options Charts - skproom.com

/r/reddevils 2020 Census Results

Thank you for taking part of the 2020 edition of /reddevils' census! We had 3,459 responses over the course of several days, and increase of .
Here are the results!
Age
With a year passing, it's understandable that our user base has also aged. What is interesting is that while last year 59.5% of the userbase indicated that they were 25 and younger, only 46.1% did so this year. Given that there was also a large increase in respondents for the "26-30" age group, it seems that we had a lot of 25 year old folks responding last year. Here is a chart showing the break out by age group and also an age distribution graph. I've included also a year-over-year comparison this year. These do not represent percent change but rather simple subtraction. For example, the 4.1% increase seen in the "26-30" age group comes from this year's "26-30" being 29.17% of this years census responses vs. only being 25.07% last year.
Conclusion? We're getting old folks.
Gender
As with every census we've run, /reddevils is overwhelmingly male. 96.2% of respondents indicated that they were male which translates to 3,328 out of the 3,459 responses. The number of ladies here increased greatly compared to last year with 72, up from 28 in 2019. 18 respondents declined to specify their gender while 41 responded with another gender.
Our resident Wookiees have increased in number to 3, up from 1 last year and in the 2012 census. 2 respondents responded as being Non-binary as well as 2 indicated that they were Olesexual. Each of the following received one response apiece: Coca Cola Can, Lockheed Martin F-35 Lightning II, Cube, Moderator, Divine Enlightened Energy Being, Two-Horned Rainbow Unicorn, Earthworm, Bisexual Leprechaun (who, surprisingly was not from Ireland but rather the Land Down Under), Absolute Chad, Anti-Virus, Attack Titan, Neymar, Ole-Wan Keaneobi, Parrot Lord, Frank Lampard, Optimus Prime, Potato, Slightly Under Ripe Kumquat, Gek (Geek?), Twin Engine Rafale Fighter Jet, Gender Is A Construct, Vulcan, Washing Machine, Wolfbrother, Juggernaut, Woolly Mammoth, Luke Shaw's Masculine Bottom, and Mail. There was also one respondent who deigned to use the "Other" option here to leave me a very rude message. Guess you can't please everyone.
Employment
Most of the reds are employed (75.3% across the Employed, Student Employed, and Self Employed categories), up from last years' 71.5%. Given the current state of the world, it is nice to see that most are still employed. Our student population has gone down, understadably, from 37.4% across the two student categories to 30.0%. A full breakdown of the year-over-year changes can be seen here. Our retirees increased in number from 1 last year to 11 this. Enjoy retirement sirs/madams.
Residence
As expected, the majority of /reddevils is UK or US based (25.85% and 25.93%, respectively). We have seen major changes this year, particularly in relation to Scandinavia, which saw the largest increase in percentage points year-over-year. I wonder what happened there.
If we're breaking it down by the regions I arbitrarily put into the census form, UK (England) is the clear winner for a second year running with 569 members reporting living in England and another 184 specifically saying they are in Manchester.
I received some feedback about covering large areas with a single region. This was largely driven by how few responses had come from these these regions historically. I'll include a few more next year but please do not expect me to list every one of the the 195 countries in the world. I've also received some feedback about not allowing any options for folks with family ties or had grown up in England/Manchester and had moved away. This will also be included in next years census.
Season TicketholdeMatches Attended
Overwhelmingly, most of us here are not season ticketholders (97.95%). We did see an increase in those who are, though it is fairly minor.
Most folks are unable to attend games as well. The number of fans who do go to many games (16+ per season) more than tripled from last year. You all are the real MVPs.
How long have you been following football/Manchester United?
Understandably, we don't have a whole lot of new fans. Interestingly enough though, we've had a large increase in folks who have started following football regularly in the last 1-3 years despite having followed United for longer than that. Putting on my tin foil hat, that at least makes me think we're more fun to watch these days.
How long have you been a subscriber to /reddevils and how do you usually access Reddit?
There are a lot of new-ish users with 63.6% reporting they have subscribed here for less than 3 years. We have a decent number of /reddevils veterans however, 154 users indicated that they had been subscribed for more than 8 years. It's good to see the old guard still around.
Unsurprisingly, Reddit apps are the most popular method to access Reddit by far. This is followed by Old Reddit users on Desktop, users of the Mobile Reddit website, and then New Reddit users coming in dead last. Long live old Reddit.
Favorite Current Player
The mood around this question was incredibly different than last year. Last year, many were vocal indicating that they had a hard time choosing due to our squad being shit. Victor Lindelof ended up being the by and large favorite with around a quarter of the votes, followed by Paul Pogba and Marcus Rashford.
This year, it appeared that there were no such issues. Only 1 response in the survey indicated that they couldn't choose because our squad was shit while the vast majority either selected a player or indicated that they loved them all. Prime Minister Doctor Sir Marcus Rashford overwhelmingly came in first place with an almost 300 vote lead over second placed Anthony Martial. Bruno Fernandes and Mason Greenwood were neck and neck for a while, eventually settling into third and fourth respectively.
Former crowd favorites Victor Lindelof and Paul Pogba fell down the rankings with Lindelof ending in 8th place and Pogba in 5th.
Favorite All Time Player
Wayne Rooney continued to the be the king of /reddevils amassing nearly double the votes of second placed Paul Scholes. Cristiano Ronaldo came in third after a very tight race with Scholes. Beckham came in fourth followed by fifth placed Cantona and sixth placed Giggsy.
Here is a year-over-year comparison purely on recorded responses. Most players received just about the same share of the votes as they did last year. The biggest changes came from Wayne Rooney (up) and David Beckham (down). The way the numbers land, it almost looks like Wazza was stealing votes from Becks! Ole Gunnar Solskjaer had more of the proverbial pie, again I wonder whats happened there.
My man Park Ji Sung came in 11th place, good to see that there are at least 58 Park lovers out there!
Now for a bit of fun. Someone asked in the Census thread how many of George Best's votes came from Northern Ireland. One user suggested it was all of them, the data on the other hand says otherwise. Only 10 of Best's 29 votes came from Northern Ireland. George Best tied for favorite player there with Wayne Rooney with Paul Scholes and Cristiano Ronaldo tying for 3rd place with 8 votes apiece.
I did this same exercise with a few other players. Here are the results:
  • While Scandinavians votes were joint-most for Ole Gunnar Solskjaer (tied with the UK), he was not the most popular player among respondents living in Scandinavia. He came in second behind Wayne Rooney.
  • Roy Keane both received the most votes from the Republic of Ireland and was also the most popular player among Irish respondents.
  • Eric Cantona was not voted heavily by the French. The British, on the other hand, love him with 82 of his 218 votes coming from the United Kingdom. The majority of Cantona voters are older, with 134/218 being over 30 years of age.
  • Park Ji Sung received the most votes from the US (21) followed by the UK (19) and Southeast Asia (4).
  • Among respondents from the United Kingdom, Wayne Rooney was the most popular followed by Scholes, Ronaldo, and Cantona.
  • Among respondents from the United States, South Asia, and Southeast Asia, Wayne Rooney was the most popular. Scholes and Ronaldo alternated in popularity in second and third place. Beckham placed fourth in all three regions.
Thank you all again for your participation. We'll run one next year and see how things have changed!
submitted by zSolaris to reddevils [link] [comments]

Retard Bot Update 2: What is there to show for six months of work?

Retard Bot Update 2: What is there to show for six months of work?
What is there to show? Not shit, that's why I made this pretty 4K desktop background instead:
4K
On the real: I've been developing this project like 6 months now, what's up? Where's that video update I promised, showing off the Bot Builder? Is an end in sight?
Yes sort of. I back-tested 6 months of data at over 21% on a net SPY-neutral, six month span of time (with similar results on a 16 year span) including 2 bear, 2 bull, 2 crab months. But that's not good enough to be sure / reliable. I had gotten so focused on keeping the project pretty and making a video update that I was putting off major, breaking changes that I needed to make. The best quant fund ever made, the Medallion fund, was once capable of roughly 60% per year consistently, but in Retard Bot's case 1.5% compounded weekly. "But I make 60% on one yolo" sure whatever, can you do it again every year, with 100% of your capital, where failure means losing everything? If you could, you'd be loading your Lambo onto your Yacht right now instead of reading this autistic shit.

The End Goal

1.5% compounded weekly average is $25K -> $57M in 10 years, securing a fairly comfortable retirement for your wife's boyfriend. It's a stupidly ambitious goal. My strategy to pull it off is actually pretty simple. If you look at charts for the best performing stocks over the past 10 years, you'll find that good companies move in the same general trajectory more often than they don't. This means the stock market moves with momentum. I developed a simple equation to conservatively predict good companies movements one week into the future by hand, and made 100%+ returns 3 weeks in a row. Doing the math took time, and I realized a computer could do much more complex math, on every stock, much more efficiently, so I developed a bot and it did 100% for 3 consecutive weeks, buying calls in a bull-market.
See the problem there? The returns were good but they were based on a biased model. The model would pick the most efficient plays on the market if it didn't take a severe downturn. But if it did, the strategy would stop working. I needed to extrapolate my strategy into a multi-model approach that could profit on momentum during all different types of market movement. And so I bought 16 years of option chain data and started studying the concept of momentum based quantitative analysis. As I spent more and more weeks thinking about it, I identified more aspects of the problem and more ways to solve it. But no matter how I might think to design algorithms to fundamentally achieve a quantitative approach, I knew that my arbitrary weights and variables and values and decisions could not possibly be the best ones.

Why Retard Bot Might Work

So I approached the problem from all angles, every conceivable way to glean reliably useful quantitative information about a stock's movement and combine it all into a single outcome of trade decisions, and every variable, every decision, every model was a fluid variable that machine learning, via the process of Evolution could randomly mutate until perfection. And in doing so, I had to fundamentally avoid any method of testing my results that could be based on a bias. For example, just because a strategy back-tests at 40% consistent yearly returns on the past 16 years of market movement doesn't mean it would do so for the next 16 years, since the market could completely end its bull-run and spend the next 16 years falling. Improbable, but for a strategy outcome that can be trusted to perform consistently, we have to assume nothing.
So that's how Retard Bot works. It assumes absolutely nothing about anything that can't be proven as a fundamental, statistical truth. It uses rigorous machine learning to develop fundamental concepts into reliable, fine tuned decision layers that make models which are controlled by a market-environment-aware Genius layer that allocates resources accordingly, and ultimately through a very complex 18 step process of iterative ML produces a top contender through the process of Evolution, avoiding all possible bias. And then it starts over and does it again, and again, continuing for eternity, recording improved models when it discovers them.

The Current Development Phase

Or... That's how it would work, in theory, if my program wasn't severely limited by the inadequate infrastructure I built it with. When I bought 16 years of data, 2TB compressed to its most efficient binary representation, I thought I could use a traditional database like MongoDB to store and load the option chains. It's way too slow. So here's where I've ended up this past week:
It was time to rip off the bandaid and rebuild some performance infrastructure (the database and decision stack) that was seriously holding me back from testing the project properly. Using MongoDB, which has to pack and unpack data up and down the 7 layer OSI model, it took an hour to test one model for one year. I need to test millions of models for 16 years, thousands of times over.
I knew how to do that, so instead of focusing on keeping things stable so I could show you guys some pretty graphs n shit, I broke down the beast and started rebuilding with a pure memory caching approach that will load the options chains thousands of times faster than MongoDB queries. And instead of running one model, one decision layer at a time on the CPU, the new GPU accelerated decision stack design will let me run hundreds of decision layers on millions of models in a handful of milliseconds. Many, many orders of magnitude better performance, and I can finally make the project as powerful as it was supposed to be.
I'm confident that with these upgrades, I'll be able to hit the goal of 60% consistent returns per year. I'll work this goddamn problem for a year if I have to. I have, in the process of trying to become an entrepreneur, planned project after project and given up half way through when it got too hard, or a partner quit, or someone else launched something better. I will not give up on this one, if it takes the rest of the year or five more.
But I don't think it'll come to that. Even with the 20% I've already achieved, if I can demonstrate that in live trading, that's already really good, so there's not really any risk of real failure at this point. But I will, regardless, finish developing the vision I have for Retard Bot and Bidrate Renaissance before I'm satisfied.

Tl;Dr

https://preview.redd.it/0plnnpkw5um51.png?width=3840&format=png&auto=webp&s=338edc893f4faadffabb5418772c9b250f488336
submitted by o_ohi to retard_bot [link] [comments]

Node.js Application Monitoring with Prometheus and Grafana

Hi guys, we published this article on our blog (here) some time ago and I thought it could be interesting for node to read is as well, since we got some good feedback on it!

What is application monitoring and why is it necessary?

Application monitoring is a method that uses software tools to gain insights into your software deployments. This can be achieved by simple health checks to see if the server is available to more advanced setups where a monitoring library is integrated into your server that sends data to a dedicated monitoring service. It can even involve the client side of your application, offering more detailed insights into the user experience.
For every developer, monitoring should be a crucial part of the daily work, because you need to know how the software behaves in production. You can let your testers work with your system and try to mock interactions or high loads, but these techniques will never be the same as the real production workload.

What is Prometheus and how does it work?

Prometheus is an open-source monitoring system that was created in 2012 by Soundcloud. In 2016, Prometheus became the second project (following Kubernetes) to be hosted by the Cloud Native Computing Foundation.
https://preview.redd.it/8kshgh0qpor51.png?width=1460&format=png&auto=webp&s=455c37b1b1b168d732e391a882598e165c42501a
The Prometheus server collects metrics from your servers and other monitoring targets by pulling their metric endpoints over HTTP at a predefined time interval. For ephemeral and batch jobs, for which metrics can't be scraped periodically due to their short-lived nature, Prometheus offers a Pushgateway. This is an intermediate server that monitoring targets can push their metrics before exiting. The data is retained there until the Prometheus server pulls it later.
The core data structure of Prometheus is the time series, which is essentially a list of timestamped values that are grouped by metric.
With PromQL (Prometheus Query Language), Prometheus provides a functional query language allowing for selection and aggregation of time series data in real-time. The result of a query can be viewed directly in the Prometheus web UI, or consumed by external systems such as Grafana via the HTTP API.

How to use prom-client to export metrics in Node.js for Prometheus?

prom-client is the most popular Prometheus client library for Node.js. It provides the building blocks to export metrics to Prometheus via the pull and push methods and supports all Prometheus metric types such as histogram, summaries, gauges and counters.

Setup sample Node.js project

Create a new directory and set up the Node.js project:
$ mkdir example-nodejs-app $ cd example-nodejs-app $ npm init -y 

Install prom-client

The prom-client npm module can be installed via:
$ npm install prom-client 

Exposing default metrics

Every Prometheus client library comes with predefined default metrics that are assumed to be good for all applications on the specific runtime. The prom-client library also follows this convention. The default metrics are useful for monitoring the usage of resources such as memory and CPU.
You can capture and expose the default metrics with following code snippet:
const http = require('http') const url = require('url') const client = require('prom-client') // Create a Registry which registers the metrics const register = new client.Registry() // Add a default label which is added to all metrics register.setDefaultLabels({ app: 'example-nodejs-app' }) // Enable the collection of default metrics client.collectDefaultMetrics({ register }) // Define the HTTP server const server = http.createServer(async (req, res) => { // Retrieve route from request object const route = url.parse(req.url).pathname if (route === '/metrics') { // Return all metrics the Prometheus exposition format res.setHeader('Content-Type', register.contentType) res.end(register.metrics()) } }) // Start the HTTP server which exposes the metrics on http://localhost:8080/metrics server.listen(8080) 

Exposing custom metrics

While default metrics are a good starting point, at some point, you’ll need to define custom metrics in order to stay on top of things.
Capturing and exposing a custom metric for HTTP request durations might look like this:
const http = require('http') const url = require('url') const client = require('prom-client') // Create a Registry which registers the metrics const register = new client.Registry() // Add a default label which is added to all metrics register.setDefaultLabels({ app: 'example-nodejs-app' }) // Enable the collection of default metrics client.collectDefaultMetrics({ register }) // Create a histogram metric const httpRequestDurationMicroseconds = new client.Histogram({ name: 'http_request_duration_seconds', help: 'Duration of HTTP requests in microseconds', labelNames: ['method', 'route', 'code'], buckets: [0.1, 0.3, 0.5, 0.7, 1, 3, 5, 7, 10] }) // Register the histogram register.registerMetric(httpRequestDurationMicroseconds) // Define the HTTP server const server = http.createServer(async (req, res) => { // Start the timer const end = httpRequestDurationMicroseconds.startTimer() // Retrieve route from request object const route = url.parse(req.url).pathname if (route === '/metrics') { // Return all metrics the Prometheus exposition format res.setHeader('Content-Type', register.contentType) res.end(register.metrics()) } // End timer and add labels end({ route, code: res.statusCode, method: req.method }) }) // Start the HTTP server which exposes the metrics on http://localhost:8080/metrics server.listen(8080) 
Copy the above code into a file called server.jsand start the Node.js HTTP server with following command:
$ node server.js 
You should now be able to access the metrics via http://localhost:8080/metrics.

How to scrape metrics from Prometheus

Prometheus is available as Docker image and can be configured via a YAML file.
Create a configuration file called prometheus.ymlwith following content:
global: scrape_interval: 5s scrape_configs: - job_name: "example-nodejs-app" static_configs: - targets: ["docker.for.mac.host.internal:8080"] 
The config file tells Prometheus to scrape all targets every 5 seconds. The targets are defined under scrape_configs. On Mac, you need to use docker.for.mac.host.internal as host, so that the Prometheus Docker container can scrape the metrics of the local Node.js HTTP server. On Windows, use docker.for.win.localhost and for Linux use localhost.
Use the docker run command to start the Prometheus Docker container and mount the configuration file (prometheus.yml):
$ docker run --rm -p 9090:9090 \ -v `pwd`/prometheus.yml:/etc/prometheus/prometheus.yml \ prom/prometheus:v2.20.1 
Windows users need to replace pwd with the path to their current working directory.
You should now be able to access the Prometheus Web UI on http://localhost:9090

What is Grafana and how does it work?

Grafana is a web application that allows you to visualize data sources via graphs or charts. It comes with a variety of chart types, allowing you to choose whatever fits your monitoring data needs. Multiple charts are grouped into dashboards in Grafana, so that multiple metrics can be viewed at once.
https://preview.redd.it/vt8jwu8vpor51.png?width=3584&format=png&auto=webp&s=4101843c84cfc6293debcdfc3bdbe70811dab2e9
The metrics displayed in the Grafana charts come from data sources. Prometheus is one of the supported data sources for Grafana, but it can also use other systems, like AWS CloudWatch, or Azure Monitor.
Grafana also allows you to define alerts that will be triggered if certain issues arise, meaning you’ll receive an email notification if something goes wrong. For a more advanced alerting setup checkout the Grafana integration for Opsgenie.

Starting Grafana

Grafana is also available as Docker container. Grafana datasources can be configured via a configuration file.
Create a configuration file called datasources.ymlwith the following content:
apiVersion: 1 datasources: - name: Prometheus type: prometheus access: proxy orgId: 1 url: http://docker.for.mac.host.internal:9090 basicAuth: false isDefault: true editable: true 
The configuration file specifies Prometheus as a datasource for Grafana. Please note that on Mac, we need to use docker.for.mac.host.internal as host, so that Grafana can access Prometheus. On Windows, use docker.for.win.localhost and for Linux use localhost.
Use the following command to start a Grafana Docker container and to mount the configuration file of the datasources (datasources.yml). We also pass some environment variables to disable the login form and to allow anonymous access to Grafana:
$ docker run --rm -p 3000:3000 \ -e GF_AUTH_DISABLE_LOGIN_FORM=true \ -e GF_AUTH_ANONYMOUS_ENABLED=true \ -e GF_AUTH_ANONYMOUS_ORG_ROLE=Admin \ -v `pwd`/datasources.yml:/etc/grafana/provisioning/datasources/datasources.yml \ grafana/grafana:7.1.5 
Windows users need to replace pwd with the path to their current working directory.
You should now be able to access the Grafana Web UI on http://localhost:3000

Configuring a Grafana Dashboard

Once the metrics are available in Prometheus, we want to view them in Grafana. This requires creating a dashboard and adding panels to that dashboard:
  1. Go to the Grafana UI at http://localhost:3000, click the + button on the left, and select Dashboard.
  2. In the new dashboard, click on the Add new panel button.
  3. In the Edit panel view, you can select a metric and configure a chart for it.
  4. The Metrics drop-down on the bottom left allows you to choose from the available metrics. Let’s use one of the default metrics for this example.
  5. Type process_resident_memory_bytesinto the Metricsinput and {{app}}into the Legendinput.
  6. On the right panel, enter Memory Usage for the Panel title.
  7. As the unit of the metric is in bytes we need to select bytes(Metric)for the left y-axis in the Axes section, so that the chart is easy to read for humans.
You should now see a chart showing the memory usage of the Node.js HTTP server.
Press Apply to save the panel. Back on the dashboard, click the small "save" symbol at the top right, a pop-up will appear allowing you to save your newly created dashboard for later use.

Setting up alerts in Grafana

Since nobody wants to sit in front of Grafana all day watching and waiting to see if things go wrong, Grafana allows you to define alerts. These alerts regularly check whether a metric adheres to a specific rule, for example, whether the errors per second have exceeded a specific value.
Alerts can be set up for every panel in your dashboards.
  1. Go into the Grafana dashboard we just created.
  2. Click on a panel title and select edit.
  3. Once in the edit view, select "Alerts" from the middle tabs, and press the Create Alertbutton.
  4. In the Conditions section specify 42000000 after IS ABOVE. This tells Grafana to trigger an alert when the Node.js HTTP server consumes more than 42 MB Memory.
  5. Save the alert by pressing the Apply button in the top right.

Sample code repository

We created a code repository that contains a collection of Docker containers with Prometheus, Grafana, and a Node.js sample application. It also contains a Grafana dashboard, which follows the RED monitoring methodology.
Clone the repository:
$ git clone https://github.com/coder-society/nodejs-application-monitoring-with-prometheus-and-grafana.git 
The JavaScript code of the Node.js app is located in the /example-nodejs-app directory. All containers can be started conveniently with docker-compose. Run the following command in the project root directory:
$ docker-compose up -d 
After executing the command, a Node.js app, Grafana, and Prometheus will be running in the background. The charts of the gathered metrics can be accessed and viewed via the Grafana UI at http://localhost:3000/d/1DYaynomMk/example-service-dashboard.
To generate traffic for the Node.js app, we will use the ApacheBench command line tool, which allows sending requests from the command line.
On MacOS, it comes pre-installed by default. On Debian-based Linux distributions, ApacheBench can be installed with the following command:
$ apt-get install apache2-utils 
For Windows, you can download the binaries from Apache Lounge as a ZIP archive. ApacheBench will be named ab.exe in that archive.
This CLI command will run ApacheBench so that it sends 10,000 requests to the /order endpoint of the Node.js app:
$ ab -m POST -n 10000 -c 100 http://localhost:8080/order 
Depending on your hardware, running this command may take some time.
After running the ab command, you can access the Grafana dashboard via http://localhost:3000/d/1DYaynomMk/example-service-dashboard.

Summary

Prometheus is a powerful open-source tool for self-hosted monitoring. It’s a good option for cases in which you don’t want to build from scratch but also don’t want to invest in a SaaS solution.
With a community-supported client library for Node.js and numerous client libraries for other languages, the monitoring of all your systems can be bundled into one place.
Its integration is straightforward, involving just a few lines of code. It can be done directly for long-running services or with help of a push server for short-lived jobs and FaaS-based implementations.
Grafana is also an open-source tool that integrates well with Prometheus. Among the many benefits it offers are flexible configuration, dashboards that allow you to visualize any relevant metric, and alerts to notify of any anomalous behavior.
These two tools combined offer a straightforward way to get insights into your systems. Prometheus offers huge flexibility in terms of metrics gathered and Grafana offers many different graphs to display these metrics. Prometheus and Grafana also integrate so well with each other that it’s surprising they’re not part of one product.
You should now have a good understanding of Prometheus and Grafana and how to make use of them to monitor your Node.js projects in order to gain more insights and confidence in your software deployments.
submitted by matthevva to node [link] [comments]

First Time Going Through Coding Interviews?

This post draws on my personal experiences and challenges over the past term at school, which I entered with hardly any knowledge of DSA (data structures and algorithms) and problem-solving strategies. As a self-taught programmer, I was a lot more familiar and comfortable with general programming, such as object-oriented programming, than with the problem-solving skills required in DSA questions.
This post reflects my journey throughout the term and the resources I turned to in order to quickly improve for my coding interview.
Here're some common questions and answers
What's the interview process like at a tech company?
Good question. It's actually pretty different from most other companies.

(What It's Like To Interview For A Coding Job

First time interviewing for a tech job? Not sure what to expect? This article is for you.

Here are the usual steps:

  1. First, you’ll do a non-technical phone screen.
  2. Then, you’ll do one or a few technical phone interviews.
  3. Finally, the last step is an onsite interview.
Some companies also throw in a take-home code test—sometimes before the technical phone interviews, sometimes after.
Let’s walk through each of these steps.

The non-technical phone screen

This first step is a quick call with a recruiter—usually just 10–20 minutes. It's very casual.
Don’t expect technical questions. The recruiter probably won’t be a programmer.
The main goal is to gather info about your job search. Stuff like:

  1. Your timeline. Do you need to sign an offer in the next week? Or are you trying to start your new job in three months?
  2. What’s most important to you in your next job. Great team? Flexible hours? Interesting technical challenges? Room to grow into a more senior role?
  3. What stuff you’re most interested in working on. Front end? Back end? Machine learning?
Be honest about all this stuff—that’ll make it easier for the recruiter to get you what you want.
One exception to that rule: If the recruiter asks you about your salary expectations on this call, best not to answer. Just say you’d rather talk about compensation after figuring out if you and the company are a good fit. This’ll put you in a better negotiating position later on.

The technical phone interview(s)

The next step is usually one or more hour-long technical phone interviews.
Your interviewer will call you on the phone or tell you to join them on Skype or Google Hangouts. Make sure you can take the interview in a quiet place with a great internet connection. Consider grabbing a set of headphones with a good microphone or a bluetooth earpiece. Always test your hardware beforehand!
The interviewer will want to watch you code in real time. Usually that means using a web-based code editor like Coderpad or collabedit. Run some practice problems in these tools ahead of time, to get used to them. Some companies will just ask you to share your screen through Google Hangouts or Skype.
Turn off notifications on your computer before you get started—especially if you’re sharing your screen!
Technical phone interviews usually have three parts:

  1. Beginning chitchat (5–10 minutes)
  2. Technical challenges (30–50 minutes)
  3. Your turn to ask questions (5–10 minutes)
The beginning chitchat is half just to help your relax, and half actually part of the interview. The interviewer might ask some open-ended questions like:

  1. Tell me about yourself.
  2. Tell me about something you’ve built that you’re particularly proud of.
  3. I see this project listed on your resume—tell me more about that.
You should be able to talk at length about the major projects listed on your resume. What went well? What didn’t? How would you do things differently now?
Then come the technical challenges—the real meet of the interview. You’ll spend most of the interview on this. You might get one long question, or several shorter ones.
What kind of questions can you expect? It depends.
Startups tend to ask questions aimed towards building or debugging code. (“Write a function that takes two rectangles and figures out if they overlap.”). They’ll care more about progress than perfection.
Larger companies will want to test your general know-how of data structures and algorithms (“Write a function that checks if a binary tree is ‘balanced’ in O(n)O(n) ↴ time.”). They’ll care more about how you solve and optimize a problem.
With these types of questions, the most important thing is to be communicating with your interviewer throughout. You'll want to "think out loud" as you work through the problem. For more info, check out our more detailed step-by-step tips for coding interviews.
If the role requires specific languages or frameworks, some companies will ask trivia-like questions (“In Python, what’s the ‘global interpreter lock’?”).
After the technical questions, your interviewer will open the floor for you to ask them questions. Take some time before the interview to comb through the company’s website. Think of a few specific questions about the company or the role. This can really make you stand out.
When you’re done, they should give you a timeframe on when you’ll hear about next steps. If all went well, you’ll either get asked to do another phone interview, or you’ll be invited to their offices for an onsite.

The onsite interview

An onsite interview happens in person, at the company’s office. If you’re not local, it’s common for companies to pay for a flight and hotel room for you.
The onsite usually consists of 2–6 individual, one-on-one technical interviews (usually in a small conference room). Each interview will be about an hour and have the same basic form as a phone screen—technical questions, bookended by some chitchat at the beginning and a chance for you to ask questions at the end.
The major difference between onsite technical interviews and phone interviews though: you’ll be coding on a whiteboard.
This is awkward at first. No autocomplete, no debugging tools, no delete button…ugh. The good news is, after some practice you get used to it. Before your onsite, practice writing code on a whiteboard (in a pinch, a pencil and paper are fine). Some tips:

  1. Start in the top-most left corner of the whiteboard. This gives you the most room. You’ll need more space than you think.
  2. Leave a blank line between each line as you write your code. Makes it much easier to add things in later.
  3. Take an extra second to decide on your variable names. Don’t rush this part. It might seem like a waste of time, but using more descriptive variable names ultimately saves you time because it makes you less likely to get confused as you write the rest of your code.
If a technical phone interview is a sprint, an onsite is a marathon. The day can get really long. Best to keep it open—don’t make other plans for the afternoon or evening.
When things go well, you’ wrap-up by chatting with the CEO or some other director. This is half an interview, half the company trying to impress you. They may invite you to get drinks with the team after hours.
All told, a long day of onsite interviews could look something like this:

If they let you go after just a couple interviews, it’s usually a sign that they’re going to pass on you. That’s okay—it happens!
There are are a lot of easy things you can do the day before and morning of your interview to put yourself in the best possible mindset. Check out our piece on what to do in the 24 hours before your onsite coding interview.

The take-home code test

Code tests aren’t ubiquitous, but they seem to be gaining in popularity. They’re far more common at startups, or places where your ability to deliver right away is more important than your ability to grow.
You’ll receive a description of an app or service, a rough time constraint for writing your code, and a deadline for when to turn it in. The deadline is usually negotiable.
Here's an example problem:
Write a basic “To-Do” app. Unit test the core functionality. As a bonus, add a “reminders” feature. Try to spend no more than 8 hours on it, and send in what you have by Friday with a small write-up.
Take a crack at the “bonus” features if they include any. At the very least, write up how you would implement it.
If they’re hiring for people with knowledge of a particular framework, they might tell you what tech to use. Otherwise, it’ll be up to you. Use what you’re most comfortable with. You want this code to show you at your best.
Some places will offer to pay you for your time. It's rare, but some places will even invite you to work with them in their office for a few days, as a "trial.")
Do I need to know this "big O" stuff?
Big O notation is the language we use for talking about the efficiency of data structures and algorithms.
Will it come up in your interviews? Well, it depends. There are different types of interviews.
There’s the classic algorithmic coding interview, sometimes called the “Google-style whiteboard interview.” It’s focused on data structures and algorithms (queues and stacks, binary search, etc).
That’s what our full course prepares you for. It's how the big players interview. Google, Facebook, Amazon, Microsoft, Oracle, LinkedIn, etc.
For startups and smaller shops, it’s a mixed bag. Most will ask at least a few algorithmic questions. But they might also include some role-specific stuff, like Java questions or SQL questions for a backend web engineer. They’ll be especially interested in your ability to ship code without much direction. You might end up doing a code test or pair-programming exercise instead of a whiteboarding session.
To make sure you study for the right stuff, you should ask your recruiter what to expect. Send an email with a question like, “Is this interview going to cover data structures and algorithms? Or will it be more focused around coding in X language.” They’ll be happy to tell you.
If you've never learned about data structures and algorithms, or you're feeling a little rusty, check out our Intuitive Guide to Data Structures and Algorithms.
Which programming language should I use?
Companies usually let you choose, in which case you should use your most comfortable language. If you know a bunch of languages, prefer one that lets you express more with fewer characters and fewer lines of code, like Python or Ruby. It keeps your whiteboard cleaner.
Try to stick with the same language for the whole interview, but sometimes you might want to switch languages for a question. E.g., processing a file line by line will be far easier in Python than in C++.
Sometimes, though, your interviewer will do this thing where they have a pet question that’s, for example, C-specific. If you list C on your resume, they’ll ask it.
So keep that in mind! If you’re not confident with a language, make that clear on your resume. Put your less-strong languages under a header like ‘Working Knowledge.’
What should I wear?
A good rule of thumb is to dress a tiny step above what people normally wear to the office. For most west coast tech companies, the standard digs are just jeans and a t-shirt. Ask your recruiter what the office is like if you’re worried about being too casual.
Should I send a thank-you note?
Thank-you notes are nice, but they aren’t really expected. Be casual if you send one. No need for a hand-calligraphed note on fancy stationery. Opt for a short email to your recruiter or the hiring manager. Thank them for helping you through the process, and ask them to relay your thanks to your interviewers.
1) Coding Interview Tips
How to get better at technical interviews without practicing
Chitchat like a pro.
Before diving into code, most interviewers like to chitchat about your background. They're looking for:

You should have at least one:

Nerd out about stuff. Show you're proud of what you've done, you're amped about what they're doing, and you have opinions about languages and workflows.
Communicate.
Once you get into the coding questions, communication is key. A candidate who needed some help along the way but communicated clearly can be even better than a candidate who breezed through the question.
Understand what kind of problem it is. There are two types of problems:

  1. Coding. The interviewer wants to see you write clean, efficient code for a problem.
  2. Chitchat. The interviewer just wants you to talk about something. These questions are often either (1) high-level system design ("How would you build a Twitter clone?") or (2) trivia ("What is hoisting in Javascript?"). Sometimes the trivia is a lead-in for a "real" question e.g., "How quickly can we sort a list of integers? Good, now suppose instead of integers we had . . ."
If you start writing code and the interviewer just wanted a quick chitchat answer before moving on to the "real" question, they'll get frustrated. Just ask, "Should we write code for this?"
Make it feel like you're on a team. The interviewer wants to know what it feels like to work through a problem with you, so make the interview feel collaborative. Use "we" instead of "I," as in, "If we did a breadth-first search we'd get an answer in O(n)O(n) time." If you get to choose between coding on paper and coding on a whiteboard, always choose the whiteboard. That way you'll be situated next to the interviewer, facing the problem (rather than across from her at a table).
Think out loud. Seriously. Say, "Let's try doing it this way—not sure yet if it'll work." If you're stuck, just say what you're thinking. Say what might work. Say what you thought could work and why it doesn't work. This also goes for trivial chitchat questions. When asked to explain Javascript closures, "It's something to do with scope and putting stuff in a function" will probably get you 90% credit.
Say you don't know. If you're touching on a fact (e.g., language-specific trivia, a hairy bit of runtime analysis), don't try to appear to know something you don't. Instead, say "I'm not sure, but I'd guess $thing, because...". The because can involve ruling out other options by showing they have nonsensical implications, or pulling examples from other languages or other problems.
Slow the eff down. Don't confidently blurt out an answer right away. If it's right you'll still have to explain it, and if it's wrong you'll seem reckless. You don't win anything for speed and you're more likely to annoy your interviewer by cutting her off or appearing to jump to conclusions.
Get unstuck.
Sometimes you'll get stuck. Relax. It doesn't mean you've failed. Keep in mind that the interviewer usually cares more about your ability to cleverly poke the problem from a few different angles than your ability to stumble into the correct answer. When hope seems lost, keep poking.
Draw pictures. Don't waste time trying to think in your head—think on the board. Draw a couple different test inputs. Draw how you would get the desired output by hand. Then think about translating your approach into code.
Solve a simpler version of the problem. Not sure how to find the 4th largest item in the set? Think about how to find the 1st largest item and see if you can adapt that approach.
Write a naive, inefficient solution and optimize it later. Use brute force. Do whatever it takes to get some kind of answer.
Think out loud more. Say what you know. Say what you thought might work and why it won't work. You might realize it actually does work, or a modified version does. Or you might get a hint.
Wait for a hint. Don't stare at your interviewer expectantly, but do take a brief second to "think"—your interviewer might have already decided to give you a hint and is just waiting to avoid interrupting.
Think about the bounds on space and runtime. If you're not sure if you can optimize your solution, think about it out loud. For example:

Get your thoughts down.
It's easy to trip over yourself. Focus on getting your thoughts down first and worry about the details at the end.
Call a helper function and keep moving. If you can't immediately think of how to implement some part of your algorithm, big or small, just skip over it. Write a call to a reasonably-named helper function, say "this will do X" and keep going. If the helper function is trivial, you might even get away with never implementing it.
Don't worry about syntax. Just breeze through it. Revert to English if you have to. Just say you'll get back to it.
Leave yourself plenty of room. You may need to add code or notes in between lines later. Start at the top of the board and leave a blank line between each line.
Save off-by-one checking for the end. Don't worry about whether your for loop should have "<<" or "<=<=." Write a checkmark to remind yourself to check it at the end. Just get the general algorithm down.
Use descriptive variable names. This will take time, but it will prevent you from losing track of what your code is doing. Use names_to_phone_numbers instead of nums. Imply the type in the name. Functions returning booleans should start with "is_*". Vars that hold a list should end with "s." Choose standards that make sense to you and stick with them.
Clean up when you're done.
Walk through your solution by hand, out loud, with an example input. Actually write down what values the variables hold as the program is running—you don't win any brownie points for doing it in your head. This'll help you find bugs and clear up confusion your interviewer might have about what you're doing.
Look for off-by-one errors. Should your for loop use a "<=<=" instead of a "<<"?
Test edge cases. These might include empty sets, single-item sets, or negative numbers. Bonus: mention unit tests!
Don't be boring. Some interviewers won't care about these cleanup steps. If you're unsure, say something like, "Then I'd usually check the code against some edge cases—should we do that next?"
Practice.
In the end, there's no substitute for running practice questions.
Actually write code with pen and paper. Be honest with yourself. It'll probably feel awkward at first. Good. You want to get over that awkwardness now so you're not fumbling when it's time for the real interview.

2) Tricks For Getting Unstuck During a Coding Interview
Getting stuck during a coding interview is rough.
If you weren’t in an interview, you might take a break or ask Google for help. But the clock is ticking, and you don’t have Google.
You just have an empty whiteboard, a smelly marker, and an interviewer who’s looking at you expectantly. And all you can think about is how stuck you are.
You need a lifeline for these moments—like a little box that says “In Case of Emergency, Break Glass.”
Inside that glass box? A list of tricks for getting unstuck. Here’s that list of tricks.
When you’re stuck on getting started
1) Write a sample input on the whiteboard and turn it into the correct output "by hand." Notice the process you use. Look for patterns, and think about how to implement your process in code.
Trying to reverse a string? Write “hello” on the board. Reverse it “by hand”—draw arrows from each character’s current position to its desired position.
Notice the pattern: it looks like we’re swapping pairs of characters, starting from the outside and moving in. Now we’re halfway to an algorithm.
2) Solve a simpler version of the problem. Remove or simplify one of the requirements of the problem. Once you have a solution, see if you can adapt that approach for the original question.
Trying to find the k-largest element in a set? Walk through finding the largest element, then the second largest, then the third largest. Generalizing from there to find the k-largest isn’t so bad.
3) Start with an inefficient solution. Even if it feels stupidly inefficient, it’s often helpful to start with something that’ll return the right answer. From there, you just have to optimize your solution. Explain to your interviewer that this is only your first idea, and that you suspect there are faster solutions.
Suppose you were given two lists of sorted numbers and asked to find the median of both lists combined. It’s messy, but you could simply:

  1. Concatenate the arrays together into a new array.
  2. Sort the new array.
  3. Return the value at the middle index.
Notice that you could’ve also arrived at this algorithm by using trick (2): Solve a simpler version of the problem. “How would I find the median of one sorted list of numbers? Just grab the item at the middle index. Now, can I adapt that approach for getting the median of two sorted lists?”
When you’re stuck on finding optimizations
1) Look for repeat work. If your current solution goes through the same data multiple times, you’re doing unnecessary repeat work. See if you can save time by looking through the data just once.
Say that inside one of your loops, there’s a brute-force operation to find an element in an array. You’re repeatedly looking through items that you don’t have to. Instead, you could convert the array to a lookup table to dramatically improve your runtime.
2) Look for hints in the specifics of the problem. Is the input array sorted? Is the binary tree balanced? Details like this can carry huge hints about the solution. If it didn’t matter, your interviewer wouldn’t have brought it up. It’s a strong sign that the best solution to the problem exploits it.
Suppose you’re asked to find the first occurrence of a number in a sorted array. The fact that the array is sorted is a strong hint—take advantage of that fact by using a binary search.

Sometimes interviewers leave the question deliberately vague because they want you to ask questions to unearth these important tidbits of context. So ask some questions at the beginning of the problem.
3) Throw some data structures at the problem. Can you save time by using the fast lookups of a hash table? Can you express the relationships between data points as a graph? Look at the requirements of the problem and ask yourself if there’s a data structure that has those properties.
4) Establish bounds on space and runtime. Think out loud about the parameters of the problem. Try to get a sense for how fast your algorithm could possibly be:

When All Else Fails
1) Make it clear where you are. State what you know, what you’re trying to do, and highlight the gap between the two. The clearer you are in expressing exactly where you’re stuck, the easier it is for your interviewer to help you.
2) Pay attention to your interviewer. If she asks a question about something you just said, there’s probably a hint buried in there. Don’t worry about losing your train of thought—drop what you’re doing and dig into her question.
Relax. You’re supposed to get stuck.
Interviewers choose hard problems on purpose. They want to see how you poke at a problem you don’t immediately know how to solve.
Seriously. If you don’t get stuck and just breeze through the problem, your interviewer’s evaluation might just say “Didn’t get a good read on candidate’s problem-solving process—maybe she’d already seen this interview question before?”
On the other hand, if you do get stuck, use one of these tricks to get unstuck, and communicate clearly with your interviewer throughout...that’s how you get an evaluation like, “Great problem-solving skills. Hire.”

3) Fixing Impostor Syndrome in Coding Interviews
“It's a fluke that I got this job interview...”
“I studied for weeks, but I’m still not prepared...”
“I’m not actually good at this. They’re going to see right through me...”
If any of these thoughts resonate with you, you're not alone. They are so common they have a name: impostor syndrome.
It’s that feeling like you’re on the verge of being exposed for what you really are—an impostor. A fraud.
Impostor syndrome is like kryptonite to coding interviews. It makes you give up and go silent.
You might stop asking clarifying questions because you’re afraid they’ll sound too basic. Or you might neglect to think out loud at the whiteboard, fearing you’ll say something wrong and sound incompetent.
You know you should speak up, but the fear of looking like an impostor makes that really, really hard.
Here’s the good news: you’re not an impostor. You just feel like an impostor because of some common cognitive biases about learning and knowledge.
Once you understand these cognitive biases—where they come from and how they work—you can slowly fix them. You can quiet your worries about being an impostor and keep those negative thoughts from affecting your interviews.

Everything you could know

Here’s how impostor syndrome works.
Software engineering is a massive field. There’s a huge universe of things you could know. Huge.
In comparison to the vast world of things you could know, the stuff you actually know is just a tiny sliver:
That’s the first problem. It feels like you don’t really know that much, because you only know a tiny sliver of all the stuff there is to know.

The expanding universe

It gets worse: counterintuitively, as you learn more, your sliver of knowledge feels like it's shrinking.
That's because you brush up against more and more things you don’t know yet. Whole disciplines like machine learning, theory of computation, and embedded systems. Things you can't just pick up in an afternoon. Heavy bodies of knowledge that take months to understand.
So the universe of things you could know seems to keep expanding faster and faster—much faster than your tiny sliver of knowledge is growing. It feels like you'll never be able to keep up.

What everyone else knows

Here's another common cognitive bias: we assume that because something is easy for us, it must be easy for everyone else. So when we look at our own skills, we assume they're not unique. But when we look at other people's skills, we notice the skills they have that we don't have.
The result? We think everyone’s knowledge is a superset of our own:
This makes us feel like everyone else is ahead of us. Like we're always a step behind.
But the truth is more like this:
There's a whole area of stuff you know that neither Aysha nor Bruno knows. An area you're probably blind to, because you're so focused on the stuff you don't know.

We’ve all had flashes of realizing this. For me, it was seeing the back end code wizard on my team—the one that always made me feel like an impostor—spend an hour trying to center an image on a webpage.

It's a problem of focus

Focusing on what you don't know causes you to underestimate what you do know. And that's what causes impostor syndrome.
By looking at the vast (and expanding) universe of things you could know, you feel like you hardly know anything.
And by looking at what Aysha and Bruno know that you don't know, you feel like you're a step behind.
And interviews make you really focus on what you don't know. You focus on what could go wrong. The knowledge gaps your interviewers might find. The questions you might not know how to answer.
But remember:
Just because Aysha and Bruno know some things you don't know, doesn't mean you don't also know things Aysha and Bruno don't know.
And more importantly, everyone's body of knowledge is just a teeny-tiny sliver of everything they could learn. We all have gaps in our knowledge. We all have interview questions we won't be able to answer.
You're not a step behind. You just have a lot of stuff you don't know yet. Just like everyone else.

4) The 24 Hours Before Your Interview

Feeling anxious? That’s normal. Your body is telling you you’re about to do something that matters.

The twenty-four hours before your onsite are about finding ways to maximize your performance. Ideally, you wanna be having one of those days, where elegant code flows effortlessly from your fingertips, and bugs dare not speak your name for fear you'll squash them.
You need to get your mind and body in The Zone™ before you interview, and we've got some simple suggestions to help.
5) Why You're Hitting Dead Ends In Whiteboard Interviews

The coding interview is like a maze

Listening vs. holding your train of thought

Finally! After a while of shooting in the dark and frantically fiddling with sample inputs on the whiteboard, you've came up with an algorithm for solving the coding question your interviewer gave you.
Whew. Such a relief to have a clear path forward. To not be flailing anymore.
Now you're cruising, getting ready to code up your solution.
When suddenly, your interviewer throws you a curve ball.
"What if we thought of the problem this way?"
You feel a tension we've all felt during the coding interview:
"Try to listen to what they're saying...but don't lose your train of thought...ugh, I can't do both!"
This is a make-or-break moment in the coding interview. And so many people get it wrong.
Most candidates end up only half understanding what their interviewer is saying. Because they're only half listening. Because they're desperately clinging to their train of thought.
And it's easy to see why. For many of us, completely losing track of what we're doing is one of our biggest coding interview fears. So we devote half of our mental energy to clinging to our train of thought.
To understand why that's so wrong, we need to understand the difference between what we see during the coding interview and what our interviewer sees.

The programming interview maze

Working on a coding interview question is like walking through a giant maze.
You don't know anything about the shape of the maze until you start wandering around it. You might know vaguely where the solution is, but you don't know how to get there.
As you wander through the maze, you might find a promising path (an approach, a way to break down the problem). You might follow that path for a bit.
Suddenly, your interviewer suggests a different path:
But from what you can see so far of the maze, your approach has already gotten you halfway there! Losing your place on your current path would mean a huge step backwards. Or so it seems.
That's why people hold onto their train of thought instead of listening to their interviewer. Because from what they can see, it looks like they're getting somewhere!
But here's the thing: your interviewer knows the whole maze. They've asked this question 100 times.

I'm not exaggerating: if you interview candidates for a year, you can easily end up asking the same question over 100 times.
So if your interviewer is suggesting a certain path, you can bet it leads to an answer.
And your seemingly great path? There's probably a dead end just ahead that you haven't seen yet:
Or it could just be a much longer route to a solution than you think it is. That actually happens pretty often—there's an answer there, but it's more complicated than you think.

Hitting a dead end is okay. Failing to listen is not.

Your interviewer probably won't fault you for going down the wrong path at first. They've seen really smart engineers do the same thing. They understand it's because you only have a partial view of the maze.
They might have let you go down the wrong path for a bit to see if you could keep your thinking organized without help. But now they want to rush you through the part where you discover the dead end and double back. Not because they don't believe you can manage it yourself. But because they want to make sure you have enough time to finish the question.
But here's something they will fault you for: failing to listen to them. Nobody wants to work with an engineer who doesn't listen.
So when you find yourself in that crucial coding interview moment, when you're torn between holding your train of thought and considering the idea your interviewer is suggesting...remember this:
Listening to your interviewer is the most important thing.
Take what they're saying and run with it. Think of the next steps that follow from what they're saying.
Even if it means completely leaving behind the path you were on. Trust the route your interviewer is pointing you down.
Because they can see the whole maze.
6) How To Get The Most Out Of Your Coding Interview Practice Sessions
When you start practicing for coding interviews, there’s a lot to cover. You’ll naturally wanna brush up on technical questions. But how you practice those questions will make a big difference in how well you’re prepared.
Here’re a few tips to make sure you get the most out of your practice sessions.
Track your weak spots
One of the hardest parts of practicing is knowing what to practice. Tracking what you struggle with helps answer that question.
So grab a fresh notebook. After each question, look back and ask yourself, “What did I get wrong about this problem at first?” Take the time to write down one or two things you got stuck on, and what helped you figure them out. Compare these notes to our tips for getting unstuck.
After each full practice session, read through your entire running list. Read it at the beginning of each practice session too. This’ll add a nice layer of rigor to your practice, so you’re really internalizing the lessons you’re learning.
Use an actual whiteboard
Coding on a whiteboard is awkward at first. You have to write out every single character, and you can’t easily insert or delete blocks of code.
Use your practice sessions to iron out that awkwardness. Run a few problems on a piece of paper or, if you can, a real whiteboard. A few helpful tips for handwriting code:

Set a timer
Get a feel for the time pressure of an actual interview. You should be able to finish a problem in 30–45 minutes, including debugging your code at the end.
If you’re just starting out and the timer adds too much stress, put this technique on the shelf. Add it in later as you start to get more comfortable with solving problems.
Think out loud
Like writing code on a whiteboard, this is an acquired skill. It feels awkward at first. But your interviewer will expect you to think out loud during the interview, so you gotta power through that awkwardness.
A good trick to get used to talking out loud: Grab a buddy. Another engineer would be great, but you can also do this with a non-technical friend.
Have your buddy sit in while you talk through a problem. Better yet—try loading up one of our questions on an iPad and giving that to your buddy to use as a script!
Set aside a specific time of day to practice.
Give yourself an hour each day to practice. Commit to practicing around the same time, like after you eat dinner. This helps you form a stickier habit of practicing.
Prefer small, daily doses of practice to doing big cram sessions every once in a while. Distributing your practice sessions helps you learn more with less time and effort in the long run.
part -2 will be upcoming in another post !
submitted by Cyberrockz to u/Cyberrockz [link] [comments]

Unpopular opinion: HL Math doesn't cover enough content

This might be a (very) unpopular opinion, but I don't think the IB Math course (particularly (Analysis) HL) covers enough content. I'm not saying that it's too easy (it's certainly not easy for most people), but rather I'm saying there are topics which are important to know which the course leaves out completely. I get that students have 5 (or more) other subjects along with TOK+EE, so of course it can't go too deep. It also has to cover a wide range of topics, which makes looking at rigorous mathematics difficult without putting too much in (which a student may not be able to handle).
I'm first going to break down the syllabus by topic and subtopic and comment on what I think should be kept, removed or added to it. Note that this applies both to the current HL syllabus (ending in 2020) as well as Analysis HL (which is more or less the same as the current HL). I'll be referring to the Analysis HL course in the breakdown, as it's the current course.
Here's a list of subtopics (not necessarily exhaustive) which are in the current syllabus:
Now here's what I would add to each topic. It's very likely that this isn't feasible to achieve in a course like this, but I'll talk about this later.
I realize this is quite a lot to add, and as mentioned it very likely isn't feasible to do. Rather than add this content to the existing course, it might be better to create a separate course entirely. This would essentially create another "Further Math", which seems a bit problematic. After all, there's a reason the original Further Math was removed: practically nobody took it. I'm guessing that the reason for this is because most schools didn't offer it, not because people couldn't do it or anything. I think regardless of the lack of popularity, (some form of) Further should still be an option to those who are willing and able to take it. Certainly if someone is passionate enough, they can learn it themselves.
Another issue with having the additional content in a separate course is there might not be so much in that course to call it one. Like the previous HL course, the original Further Math course had 6 topics; each of which studied a distinct area of math. I mentioned that the geometry topic doesn't need to add much more, but maybe one could add hyperbolic trig functions as a subtopic, or perhaps some non-Euclidean geometry (spherical, hyperbolic and projective).
If someone is willing to teach themselves the content, however, this begets some other problems. For example, there may be risks to self-teaching for the purpose of an exam; they might learn the material fine but find it difficult to write the papers (due to time issues or not being able to respond the right way for full marks) without sufficient practice. Also if few students are doing AA HL anyway, why the need for an additional course at all? Why can't they just teach themselves additional content as they please? I say if you're going to learn additional content, why not take an exam to assess your skills? Otherwise it might seem like a waste to learn it if you aren't going to do anything else with it. Having an additional course would also give structure to the additional content; there would be a syllabus specifying exactly what a student needs to know for the course and it would be tailored to students who have completed or are taking AA HL and would thus complement that course. That way, a student doesn't need to look for a bunch of undergraduate textbooks or anything; and none of these are likely to serve the student well enough.
Overall, I feel like the course lacks mathematical rigor. But maybe I'm getting ahead of myself. Feel free to share what you think. Do you think the AA HL course doesn't cover enough? If so, what would you add or change?
submitted by Liammcquay to IBO [link] [comments]

Nothing to see here! pls scroll to next post!

debug.cpp TesterHook.cpp entityidxarray.cpp graph.cpp graphnode.cpp modAI_Memory.cpp aAI_CommsInstructions.cpp aAI_EntityInterface.cpp cAI_Action.cpp cAI_AdminManager.cpp cAI_Agent.cpp cAI_CommsModule.cpp cAI_CommsPrefix.cpp cAI_CommsPrep.cpp cAI_EntityGame.cpp cAI_EntityPlayer.cpp cAI_TransitionData.cpp cAI_Variables.cpp modAI_Audio.cpp modAI_Communication.cpp modAI_Identifier.cpp modAI_Interaction.cpp modAI_Interface.cpp modAI_Senses.cpp modAI_Synchronisation.cpp aAI_PerformTask.cpp cAI_ActionManager.cpp cAI_AnimInterface.cpp cAI_LowLevelInterface.cpp cAI_PerformanceManager.cpp cAI_PerformancePhase.cpp cAI_PerformTaskAction.cpp cAI_PerformTaskAnim.cpp cAI_PerformTaskAudio.cpp cAI_SpeechInterface.cpp aAI_Controller.cpp aAI_ControllerCombat.cpp aAI_Coordinator.cpp aAI_EntityIDArray.cpp aAI_Objective.cpp cAI_ControllerBoundary.cpp cAI_ControllerCamp.cpp cAI_ControllerCombatBlind.cpp cAI_ControllerCombatCover.cpp cAI_ControllerCombatMelee.cpp cAI_ControllerCoverSeek.cpp cAI_ControllerFollow.cpp cAI_ControllerFollowThrough.cpp cAI_ControllerGoto.cpp cAI_ControllerGotoGunfire.cpp cAI_ControllerGuard.cpp cAI_ControllerHide.cpp cAI_ControllerIdle.cpp cAI_ControllerOrbit.cpp cAI_ControllerSearch.cpp cAI_ControllerStop.cpp cAI_CoordinateBoundary.cpp cAI_CoordinateGenericAction.cpp cAI_CoordinateGenericCombat.cpp cAI_CoordinateGuard.cpp cAI_CoordinateIdle.cpp cAI_CoordinateInvestigate.cpp cAI_CoordinateKillEnemy.cpp cAI_CoordinateSearch.cpp cAI_Goal.cpp cAI_GoalDefinition.cpp cAI_IdleActions.cpp cAI_ObjectiveBeBuddy.cpp cAI_ObjectiveHuntEnemy.cpp cAI_ObjectiveIdle.cpp cAI_ObjectiveScriptedAction.cpp cAI_Pack.cpp cAI_Subpack.cpp cAI_HearingSense.cpp cAI_SensesData.cpp cAI_SensingPhase.cpp cAI_VisionSense.cpp meleeTraits.cpp traits.cpp acts.cpp atomicActs.cpp combatUtil.cpp coverActs.cpp gunActBase.cpp meleeActs.cpp pedBodyAnimFSM.cpp pedTorsoAnimFSM.cpp compDriver.cpp weaponController.cpp formation.cpp motion.cpp navigation.cpp navPoint.cpp navTactics.cpp pointTracker.cpp squad.cpp pedSpace.cpp gunPerception.cpp itemPerception.cpp meleeCombatPerception.cpp pedRelationshipPerception.cpp selfPerception.cpp Senses.cpp Vision.cpp AnimBlendAssociation.cpp AnimBlendClumpData.cpp AnimBlendHierarchy.cpp AnimBlendNode.cpp AnimBlendSequence.cpp AnimHierarchy.cpp AnimManager.cpp Compressed.cpp EntityAnim.cpp App.cpp GameTime.cpp AmbientTransitionManager.cpp AudioAnim.cpp audiobloodfx.cpp AudioCollision.cpp audiolog.cpp audioman.cpp AudioMisc.cpp AudioScripted.cpp AudioTextMap.cpp CriAdxStream.cpp CriAixStream.cpp CriInterface.cpp dmaudio.cpp music.cpp SampleManagerChannelFunctions.cpp sampman.cpp ScriptedStream.cpp SpeechManager.cpp VolumeFader.cpp AgeSupport.cpp manager.cpp sfx.cpp system_wii.cpp BufferedSoundWii.cpp CRC.cpp SectorReadables.cpp ColAABox.cpp ColArch.cpp ColData.cpp ColFrustum.cpp ColLine.cpp Collision.cpp ColModelLine.cpp ColModelPoint.cpp ColModelSphere.cpp ColModelTri.cpp ColPrim.cpp ColSphere.cpp ColTri.cpp ContactInfo.cpp ColCylinder.cpp ColModelCylinder.cpp console.cpp skel.cpp wiiplatform.cpp CollectableEffect.cpp CreationManager.cpp Entity.cpp EntityManager.cpp OddEntity.cpp TypeData.cpp Character.cpp ped.cpp pedstates.cpp attackdirectiondata.cpp attackdirectionlookup.cpp pedcombatlookups.cpp pedspinecontrol.cpp pushporter.cpp Climb.cpp Crawl.cpp Crouch.cpp Detector.cpp Dive.cpp Jump.cpp JumpPredictor.cpp autoped.cpp Hunter.cpp Leader.cpp PedHead.cpp delayedHunterSpawn.cpp RsvGoreEffectForExecutions.cpp CameraData.cpp collectable.cpp conveyor.cpp door.cpp EntityLight.cpp Lift.cpp mover.cpp ShotEntity.cpp slidedoor.cpp switch.cpp Trigger.cpp Useable.cpp EntitySound.cpp EnvironmentalExecution.cpp Helicopter.cpp ShadowPlane.cpp FileHandler.cpp FileNames.cpp LoadSave.cpp eyelayerinset.cpp Frontend.cpp FrontendMenu.cpp GameInfo.cpp GameInventory.cpp GameMap.cpp randomuvanimator.cpp tvlayerinset.cpp confirmnewgamepage.cpp inventorystatussettings.cpp layeredbackground.cpp layeredpage.cpp pageeffects.cpp randomoverlay.cpp screenanim.cpp screeneffectsmanager.cpp startpage.cpp texanimator.cpp weaponslotcolours.cpp weaponswapper.cpp weaponswappersettings.cpp backgroundPicAnim.cpp bar.cpp confirmingameQuitPage.cpp ContextButtonDisplay.cpp controllerPage.cpp defaultSettingsPage.cpp ExecutionBox.cpp ExecutionFrame.cpp FlexText.cpp GoalFlexText.cpp hud.cpp hudItem.cpp ingameMainPage.cpp InventorySelector.cpp inventoryStatus.cpp item.cpp LevelNameFlexText.cpp LoadProgressScreen.cpp menu.cpp newGameBrightnessPage.cpp page.cpp radar.cpp saveGamesPage.cpp sceneselectionPage.cpp screen.cpp startLanguageSelectionPage.cpp textures.cpp cGEN_String.cpp cGEN_Timer.cpp gGEN_Globals.cpp gGEN_StandardFunctions.cpp modGEN_Housekeeping.cpp modGEN_Memory.cpp stats.cpp aGEN_Array.cpp cGEN_CharArray.cpp cDBG_DebugFile.cpp modDBG_LowLevelDebug.cpp aGEN_Memory.cpp modGEN_MemoryReporting.cpp rwcore.cpp TextUtils.cpp UniCodeUtils.cpp MhGlobalData.cpp MhLoadSave_Wii.cpp MhPeripherals_Wii.cpp Pad_Wii.cpp WiiLoadSave.cpp CheatHandler.cpp InputManager.cpp WiiAccelerometer.cpp WiiGesture.cpp ActionMapping.cpp KeyCode.cpp Inventory.cpp fx.cpp fxEmitter.cpp fxInfo.cpp fxInterp.cpp fxKeyGen.cpp fxList.cpp fxManager.cpp fxPrim.cpp fxSystem.cpp fxUtils.cpp MHtoFXinterface.cpp Maths.cpp Matrix.cpp Quaternion.cpp Vector.cpp MemManager.cpp PoolAllocationManager.cpp PoolAllocator.cpp CutsceneCamera.cpp EntityFadeController.cpp SimpleLinearAllocator.cpp Cylinder.cpp FrisbeeArm.cpp CriAfsPartition.cpp CriDataStream.cpp DataStreamManager.cpp Portal.cpp StreamedLevelSector.cpp StreamedLevelSectorCore.cpp StreamedLevelSectorManager.cpp StreamedAnimation.cpp StreamedAnimationManager.cpp TexturePool.cpp TexturePoolGroup.cpp TexturePoolManager.cpp AiHelpers.cpp EntityAttrReader.cpp EntityAttrWriter.cpp EntityTextureRenderer.cpp EnvironmentID.cpp PathSearch.cpp RsvDebuggingInfoForUseables.cpp RsvTvpChecker.cpp StringHashing.cpp OverlayMgr.cpp RwRGBA_Globals.cpp ScreenStringsOverlay.cpp TextOverlay.cpp Physics.cpp collisionFrame.cpp camglobals.cpp Crosshair.cpp ExecutionTutorial.cpp handicam.cpp ImpactDamageMap.cpp player.cpp playercam.cpp PLayerLimits.cpp playerstates.cpp WiiExecutionMap.cpp WiiQuickTimeMoment.cpp grenade.cpp responder.cpp Atomic.cpp Camera.cpp CharacterDamageManager.cpp CharacterDamageMap.cpp Clump.cpp ClumpDict.cpp clumplist.cpp collisionmaterial.cpp EntityShadow.cpp EntityShadowManager.cpp Frame.cpp Geometry.cpp Light.cpp lights.cpp material.cpp materiallist.cpp scene.cpp sceneData.cpp skin.cpp spline.cpp texdictionary.cpp texture.cpp tvp.cpp utils.cpp uvanimator.cpp World.cpp WorldSector.cpp CutScene.cpp CutScenePlayed.cpp EntityShadowFader.cpp MaterialMapper.cpp lit_environmentmap.cpp lit_singletexture.cpp lit_singletexture_uvanim.cpp lit_texreconfig.cpp unlit_32indtexture.cpp unlit_notexture.cpp unlit_singletexture.cpp entityData.cpp LoadedScript.cpp ScriptCaseFloat.cpp ScriptCaseGame.cpp ScriptCaseGame2.cpp ScriptCaseGame3.cpp ScriptCaseGameRsv.cpp ScriptCaseInternals.cpp ScriptCaseStandard.cpp ScriptCaseStrings.cpp ScriptLoader.cpp ScriptManager.cpp ScriptVM.cpp BreakingGlass.cpp clouds.cpp Decal.cpp dualtexture.cpp fogpatch.cpp FXMode.cpp LightFX.cpp ParticleEffect.cpp ParticleModel.cpp rats.cpp Renderbuffer.cpp rubbish.cpp SFXManager.cpp StreakEffect.cpp TrailEffect.cpp Weather.cpp jitter.cpp lipsync.cpp spotlight.cpp spotlightcone.cpp throwgraphic.cpp OverbrightEffect.cpp VideoScreenEffect.cpp Str.cpp Timer.cpp Shot.cpp Weapon.cpp WeaponManager.cpp colramp.cpp Gu.cpp GuProfiler.cpp main.cpp renderer.cpp rslengine.cpp shadermgr.cpp vectorASM.cpp volatilemem.cpp WiiGeometry.cpp WiiShader.cpp WorldCollision.cpp actor.c control.c displayObject.c dmabuffer.cpp fileCache.c geoPalette.c GQRSetup.c List.c normalTable.c SKNControl.c SKNMath.c string.c texPalette.c Tree.c HomeButtonMenu.cpp display.cpp binkfunctions.cpp binkplayer.cpp wiitextures.c adler32.c infblock.c infcodes.c inffast.c inflate.c inftrees.c infutil.c zutil.c binkwii.c binkread.c wiiax.c wiifile.c binkacd.c radcb.c expand.c popmal.c radmem.c fft.c dct.c bitplane.c ai.c arc.c AX.c AXAlloc.c AXAux.c AXCL.c AXOut.c AXSPB.c AXVPB.c AXProf.c AXComp.c DSPCode.c AXFXReverbHi.c AXFXReverbHiDpl2.c AXFXReverbHiExp.c AXFXReverbHiExpDpl2.c AXFXReverbStd.c AXFXReverbStdExp.c AXFXHooks.c PPCArch.c gki_buffer.c gki_time.c gki_ppc.c hcisu_h2.c uusb_ppc.c bta_dm_cfg.c bta_hh_cfg.c bta_sys_cfg.c bte_hcisu.c bte_init.c bte_logmsg.c bte_main.c btu_task1.c bd.c bta_sys_conn.c bta_sys_main.c ptim.c utl.c bta_dm_act.c bta_dm_api.c bta_dm_main.c bta_dm_pm.c bta_hh_act.c bta_hh_api.c bta_hh_main.c bta_hh_utils.c btm_acl.c btm_dev.c btm_devctl.c btm_discovery.c btm_inq.c btm_main.c btm_pm.c btm_sco.c btm_sec.c btu_hcif.c btu_init.c wbt_ext.c gap_api.c gap_conn.c gap_utils.c hcicmds.c hidd_api.c hidd_conn.c hidd_mgmt.c hidd_pm.c hidh_api.c hidh_conn.c l2c_api.c l2c_csm.c l2c_link.c l2c_main.c l2c_utils.c port_api.c port_rfc.c port_utils.c rfc_l2cap_if.c rfc_mx_fsm.c rfc_port_fsm.c rfc_port_if.c rfc_ts_frames.c rfc_utils.c sdp_api.c sdp_db.c sdp_discovery.c sdp_main.c sdp_server.c sdp_utils.c db.c dsp.c dsp_debug.c dsp_task.c dvdfs.c dvd.c dvdqueue.c dvderror.c dvdidutils.c dvdFatal.c dvd_broadway.c euart.c EXIBios.c EXIUart.c EXICommon.c fs.c GXInit.c GXFifo.c GXAttr.c GXMisc.c GXGeometry.c GXFrameBuf.c GXLight.c GXTexture.c GXBump.c GXTev.c GXPixel.c GXDisplayList.c GXTransform.c GXPerf.c HBMBase.cpp HBMAnmController.cpp HBMFrameController.cpp HBMGUIManager.cpp HBMController.cpp HBMRemoteSpk.cpp db_assert.cpp db_console.cpp db_DbgPrintBase.cpp db_directPrint.cpp db_mapFile.cpp lyt_animation.cpp lyt_arcResourceAccessor.cpp lyt_bounding.cpp lyt_common.cpp lyt_drawInfo.cpp lyt_group.cpp lyt_layout.cpp lyt_material.cpp lyt_pane.cpp lyt_picture.cpp lyt_resourceAccessor.cpp lyt_textBox.cpp lyt_window.cpp math_triangular.cpp snd_AnimSound.cpp snd_AxManager.cpp snd_AxVoice.cpp snd_Bank.cpp snd_BankFile.cpp snd_BasicSound.cpp snd_Channel.cpp snd_DisposeCallbackManager.cpp snd_DvdSoundArchive.cpp snd_EnvGenerator.cpp snd_ExternalSoundPlayer.cpp snd_FrameHeap.cpp snd_InstancePool.cpp snd_Lfo.cpp snd_MemorySoundArchive.cpp snd_MidiSeqPlayer.cpp snd_MidiSeqTrack.cpp snd_MmlParser.cpp snd_MmlSeqTrack.cpp snd_MmlSeqTrackAllocator.cpp snd_NandSoundArchive.cpp snd_PlayerHeap.cpp snd_RemoteSpeaker.cpp snd_RemoteSpeakerManager.cpp snd_SeqFile.cpp snd_SeqPlayer.cpp snd_SeqSound.cpp snd_SeqSoundHandle.cpp snd_SeqTrack.cpp snd_SoundArchive.cpp snd_SoundArchiveFile.cpp snd_SoundArchiveLoader.cpp snd_SoundArchivePlayer.cpp snd_SoundHandle.cpp snd_SoundHeap.cpp snd_SoundPlayer.cpp snd_SoundStartable.cpp snd_SoundSystem.cpp snd_SoundThread.cpp snd_StrmChannel.cpp snd_StrmFile.cpp snd_StrmPlayer.cpp snd_StrmSound.cpp snd_StrmSoundHandle.cpp snd_TaskManager.cpp snd_TaskThread.cpp snd_Util.cpp snd_WaveFile.cpp snd_WavePlayer.cpp snd_WaveSound.cpp snd_WaveSoundHandle.cpp snd_WsdFile.cpp snd_WsdPlayer.cpp snd_WsdTrack.cpp ut_binaryFileFormat.cpp ut_CharStrmReader.cpp ut_CharWriter.cpp ut_DvdFileStream.cpp ut_DvdLockedFileStream.cpp ut_FileStream.cpp ut_Font.cpp ut_IOStream.cpp ut_LinkList.cpp ut_list.cpp ut_ResFont.cpp ut_ResFontBase.cpp ut_TagProcessorBase.cpp ut_TextWriterBase.cpp ipcMain.c ipcclt.c memory.c ipcProfile.c KPAD.c mem_heapCommon.c mem_expHeap.c mem_frameHeap.c mem_unitHeap.c mem_allocator.c mem_list.c mix.c remote.c mtx.c mtxvec.c mtx44.c vec.c psmtx.c nand.c NANDOpenClose.c NANDCore.c NANDCheck.c OS.c OSAlarm.c OSAlloc.c OSArena.c OSAudioSystem.c OSCache.c OSContext.c OSError.c OSExec.c OSFatal.c OSFont.c OSInterrupt.c OSLink.c OSMessage.c OSMemory.c OSMutex.c OSReboot.c OSReset.c OSRtc.c OSSemaphore.c OSSync.c OSThread.c OSTime.c OSUtf.c OSIpc.c OSStateTM.c __start.c OSPlayRecord.c OSStateFlags.c OSNet.c OSNandbootInfo.c __ppc_eabi_init.cpp Pad.c scsystem.c scapi.c scapi_prdinfo.c seq.c SIBios.c SISamplingRate.c syn.c TPL.c usb.c vi.c i2c.c vi3in1.c wenc.c WPAD.c WPADHIDParser.c WPADEncrypt.c WPADMem.c debug_msg.c WUD.c WUDHidHost.c debug_msg.c DebuggerDriver.c exi2.c float.cpp alloc.c ansi_files.c ansi_fp.c arith.c buffer_io.c ctype.c direct_io.c errno.c file_io.c FILE_POS.C locale.c mbstring.c mem.c mem_funcs.c math_api.c misc_io.c printf.c qsort.c rand.c scanf.c signal.c string.c strtold.c strtoul.c wctype.c wstring.c wchar_io.c uart_console_io_gcn.c abort_exit_ppc_eabi.c math_sun.c extras.c e_atan2.c e_exp.c e_fmod.c e_log.c e_log10.c e_pow.c e_rem_pio2.c k_cos.c k_rem_pio2.c k_sin.c k_tan.c s_atan.c s_ceil.c s_copysign.c s_cos.c s_floor.c s_frexp.c s_ldexp.c s_sin.c s_tan.c w_atan2.c w_exp.c w_fmod.c w_log.c w_log10.c w_pow.c e_sqrt.c math_ppc.c w_sqrt.c __mem.c __va_arg.c global_destructor_chain.c NMWException.cp ptmf.c runtime.c __init_cpp_exceptions.cpp Gecko_ExceptionPPC.cp GCN_mem_alloc.c mainloop.c nubevent.c nubinit.c msg.c msgbuf.c serpoll.c usr_put.c dispatch.c msghndlr.c support.c mutex_TRK.c notify.c flush_cache.c mem_TRK.c string_TRK.c __exception.s targimpl.c targsupp.s mpc_7xx_603e.c mslsupp.c dolphin_trk.c main_TRK.c dolphin_trk_glue.c targcont.c target_options.c UDP_Stubs.c main.c CircleBuffer.c MWCriticalSection_gc.cpp HashKeyFunctions.cpp MemMan.cpp Random.cpp RelocatableChunk.cpp fmod_eventi.cpp fmod_eventsystemi.cpp fmod_sounddef.cpp fmod_eventcategoryi.cpp fmod_eventparameteri.cpp fmod_eventprojecti.cpp fmod_eventgroupi.cpp fmod_reverbdef.cpp fmod_channel_revolution.cpp fmod_os_misc.cpp fmod_os_output.cpp fmod_output_revolution.cpp fmod_sample_revolution.cpp fmod_dsp.cpp fmod_dspi.cpp fmod_codec_aiff.cpp fmod_codec_dsp.cpp fmod_codec_fsb.cpp fmod_codec_user.cpp fmod.cpp fmod_async.cpp fmod_channel.cpp fmod_channel_emulated.cpp fmod_channel_real.cpp fmod_channel_realmanual3d.cpp fmod_channel_stream.cpp fmod_channeli.cpp fmod_channelpool.cpp fmod_channelgroup.cpp fmod_channelgroupi.cpp fmod_codec.cpp fmod_debug.cpp fmod_file.cpp fmod_file_disk.cpp fmod_file_memory.cpp fmod_file_null.cpp fmod_file_user.cpp fmod_listener.cpp fmod_memory.cpp fmod_metadata.cpp fmod_output.cpp fmod_output_emulated.cpp fmod_output_polled.cpp fmod_plugin.cpp fmod_pluginfactory.cpp fmod_sound.cpp fmod_sound_sample.cpp fmod_sound_stream.cpp fmod_soundi.cpp fmod_string.cpp fmod_stringw.cpp fmod_system.cpp fmod_systemi.cpp fmod_thread.cpp fmod_time.cpp fmod_globals.cpp fmod_output_nosound.cpp fmod_output_nosound_nrt.cpp fmod_reverbi.cpp fmod_speakerlevels_pool.cpp
submitted by SSor3nt to ManhuntGames [link] [comments]

[They] Are Not Journalists. [They] Are Not Reporters. [They] Are Professional Mouthpieces. [They] Are The 'Clowns In America'. Names, Headshots, And News Organization. 18 U.S. Code § 2384 - Seditious Conspiracy 18 U.S. Code § 1962 - R.I.C.O. + 'Crimes Against Humanity'

[They] Are Not Journalists. [They] Are Not Reporters. [They] Are Professional Mouthpieces. [They] Are The 'Clowns In America'. Names, Headshots, And News Organization. 18 U.S. Code § 2384 - Seditious Conspiracy 18 U.S. Code § 1962 - R.I.C.O. + 'Crimes Against Humanity'
When You’re Sitting Comfortably In Front Of Your TV, Keep In Mind That The Actual Patent For The Television Was Filed As Electromagnetic Nervous System Manipulation Apparatus.

WarNuse

WarNuse
At any rate, here are the patents. Just reading some of them helped me to understand the attacks against me and to resist them. Round-robin voices–a man, woman, and child–at different frequencies–are just one example.
Hearing Device – US4858612 – Inventor, Phillip L. Stocklin – Assignee, Mentec AG. A method and apparatus for simulation of hearing in mammals by introduction of a plurality of microwaves into the region of the auditory cortex is shown and described. A microphone is used to transform sound signals into electrical signals which are in turn analyzed and processed to provide controls for generating a plurality of microwave signals at different frequencies. The multifrequency microwaves are then applied to the brain in the region of the auditory cortex. By this method sounds are perceived by the mammal which are representative of the original sound received by the microphone.
Click on Link for Full Patent: US4858612
Hearing System – US4877027 – Inventor & Assignee, Wayne B. Brunkan. Sound is induced in the head of a person by radiating the head with microwaves in the range of 100 megahertz to 10,000 megahertz that are modulated with a particular waveform. The waveform consists of frequency modulated bursts. Each burst is made up of ten to twenty uniformly spaced pulses grouped tightly together. The burst width is between 500 nanoseconds and 100 microseconds. The pulse width is in the range of 10 nanoseconds to 1 microsecond. The bursts are frequency modulated by the audio input to create the sensation of hearing in the person whose head is irradiated.
Click on Link for Full Patent: US4877027
Silent Subliminal Representation System – US5159703 – Inventor & Assignee, Oliver M. Lowery. A silent communications system in which nonaural carriers, in the very low or very high audio frequency range or in the adjacent ultrasonic frequency spectrum, are amplitude or frequency modulated with the desired intelligence and propagated acoustically or vibrationally, for inducement into the brain, typically through the use of loudspeakers, earphones or piezoelectric transducers. The modulated carriers may be transmitted directly in real time or may be conveniently recorded and stored on mechanical, magnetic or optical media for delayed or repeated transmission to the listener.
Click on Link for Full Patent: US5159703
Method and Device for Interpreting Concepts and Conceptual Thought from Brainwave Data & for Assisting for Diagnosis of Brainwave Disfunction – US5392788 – Inventor, William J. Hudspeth – Assignee, Samuel J. Leven. A system for acquisition and decoding of EP and SP signals is provided which comprises a transducer for presenting stimuli to a subject, EEG transducers for recording brainwave signals from the subject, a computer for controlling and synchronizing stimuli presented to the subject and for concurrently recording brainwave signals, and either interpreting signals using a model for conceptual perceptional and emotional thought to correspond EEG signals to thought of the subject or comparing signals to normative EEG signals from a normative population to diagnose and locate the origin of brain dysfunctional underlying perception, conception, and emotion.
Click on Link for Full Patent: US5392788
Method and an Associated Apparatus for Remotely Determining Information as to Person’s Emotional State – US5507291 – Inventors & Assignees, Robert C. Stirbl & Peter J. Wilk. In a method for remotely determining information relating to a person’s emotional state, an waveform energy having a predetermined frequency and a predetermined intensity is generated and wirelessly transmitted towards a remotely located subject. Waveform energy emitted from the subject is detected and automatically analyzed to derive information relating to the individual’s emotional state. Physiological or physical parameters of blood pressure, pulse rate, pupil size, respiration rate and perspiration level are measured and compared with reference values to provide information utilizable in evaluating interviewee’s responses or possibly criminal intent in security sensitive areas.
Click on Link for Full Patent: US5507291
Apparatus for Electric Stimulation of Auditory Nerves of a Human Being – US5922016 – Inventors & Assignees, Erwin & Ingeborg Hochmair. Apparatus for electric stimulation and diagnostics of auditory nerves of a human being, e.g. for determination of sensation level (SL), most conformable level (MCL) and uncomfortable level (UCL) audibility curves, includes a stimulator detachably secured to a human being for sending a signal into a human ear, and an electrode placed within the human ear and electrically connected to the stimulator by an electric conductor for conducting the signals from the stimulator into the ear. A control unit is operatively connected to the stimulator for instructing the stimulator as to characteristics of the generated signals being transmitted to the ear.
Click on Link for Full Patent: US5922016
Brain Wave Inducing System – US5954629 – Inventors, Masatoshi Yanagidaira, Yuchi Kimikawa, Takeshi Fukami & Mitsuo Yasushi – Assignee, Pioneer Corp. Sensors are provided for detecting brain waves of a user, and a band-pass filter is provided for extracting a particular brain waves including an α wave included in a detected brain wave. The band-pass filter comprises a first band-pass filter having a narrow pass band, and a second band-pass filter having a wide pass band. One of the first and second band-pass filters is selected, and a stimulation signal is produced in dependency on an α wave extracted by a selected band-pass filter. In accordance with the stimulation signal, a stimulation light is emitted to the user in order to induce the user to relax or sleeping state.
Click on Link for Full Patent: US5954629
Layout Overlap Detection with Selective Flattening in Computer Implemented Integrated Circuit Design – US6011991 – Inventors, Wai-Yan Ho & Hongbo Tang – Assignee, Synopsys Inc. The present invention relates to a method for efficiently performing hierarchical design rules checks (DRC) and layout versus schematic comparison (LVS) on layout areas of an integrated circuit where cells overlap or where a cell and local geometry overlap. With the present invention, a hierarchical tree describes the integrated circuit’s layout data including cells having parent-child relationships and including local geometry. The present invention performs efficient layout verification by performing LVS and DRC checking on the new portions of an integrated circuit design and layout areas containing overlapping cells. When instances of cells overlap, the present invention determines the overlap area using predefined data structures that divide each cell into an array of spatial bins. Each bin of a parent is examined to determine if two or more cell instances reside therein or if a cell instance and local geometry reside therein. Once overlap is detected, the areas of the layout data corresponding to the overlap areas are selectively flattened prior to proceeding to DRC and LVS processing. During selective flattening of the overlap areas, the hierarchical tree is traversed from the top cell down through intermediate nodes to the leaf nodes. Each time geometry data is located during the traversal, it is pushes directly to the top cell without being stored in intermediate locations. This provides an effective mechanism for selective flattening.
Click on Link for Full Patent: US6011991
Apparatus for Audibly Communicating Speech Using the Radio Frequency Hearing Effect – US6587729 – Inventors, James P. O’laughlin & Diana L. Loree – Assignee, US Air Force. A modulation process with a fully suppressed carrier and input preprocessor filtering to produce an encoded output; for amplitude modulation (AM) and audio speech preprocessor filtering, intelligible subjective sound is produced when the encoded signal is demodulated using the RF Hearing Effect. Suitable forms of carrier suppressed modulation include single sideband (SSB) and carrier suppressed amplitude modulation (CSAM), with both sidebands present.
Click on Link for Full Patent: US6587729
Coupling an Electronic Skin Tattoo to a Mobile Communication Device – US20130297301A1 – Inventor, William P. Alberth, Jr. – Assignee, Google Technology Holdings LLC (formerly Motorola Mobility LLC). A system and method provides auxiliary voice input to a mobile communication device (MCD). The system comprises an electronic skin tattoo capable of being applied to a throat region of a body. The electronic skin tattoo can include an embedded microphone; a transceiver for enabling wireless communication with the MCD; and a power supply configured to receive energizing signals from a personal area network associated with the MCD. A controller is communicatively coupled to the power supply. The controller can be configured to receive a signal from the MCD to initiate reception of an audio stream picked up from the throat region of the body for subsequent audio detection by the MCD under an improved signal-to-noise ratio than without the employment of the electronic skin tattoo.
Click on Link for Full Patent: US20130297301A1
Apparatus for Remotely Altering & Monitoring Brainwaves – US3951134 – Inventor, Robert G. Malech – Assignee, Dorne & Margolin Inc. Apparatus for and method of sensing brain waves at a position remote from a subject whereby electromagnetic signals of different frequencies are simultaneously transmitted to the brain of the subject in which the signals interfere with one another to yield a waveform which is modulated by the subject’s brain waves. The interference waveform which is representative of the brain wave activity is re-transmitted by the brain to a receiver where it is demodulated and amplified. The demodulated waveform is then displayed for visual viewing and routed to a computer for further processing and analysis. The demodulated waveform also can be used to produce a compensating signal which is transmitted back to the brain to effect a desired change in electrical activity therein.
Click on Link for Full Patent: US3951134
Auditory Subliminal Message System & Method – US4395600 – Inventors, Rene R. Lundy & David L. Tyler – Assignee, Proactive Systems Inc. Ambient audio signals from the customer shopping area within a store are sensed and fed to a signal processing circuit that produces a control signal which varies with variations in the amplitude of the sensed audio signals. A control circuit adjusts the amplitude of an auditory subliminal anti-shoplifting message to increase with increasing amplitudes of sensed audio signals and decrease with decreasing amplitudes of sensed audio signals. This amplitude controlled subliminal message may be mixed with background music and transmitted to the shopping area. To reduce distortion of the subliminal message, its amplitude is controlled to increase at a first rate slower than the rate of increase of the amplitude of ambient audio signals from the area. Also, the amplitude of the subliminal message is controlled to decrease at a second rate faster than the first rate with decreasing ambient audio signal amplitudes to minimize the possibility of the subliminal message becoming supraliminal upon rapid declines in ambient audio signal amplitudes in the area. A masking signal is provided with an amplitude which is also controlled in response to the amplitude of sensed ambient audio signals. This masking signal may be combined with the auditory subliminal message to provide a composite signal fed to, and controlled by, the control circuit.
Click on Link for Full Patent: US4395600
Apparatus for Inducing Frequency Reduction in Brain Wave – US4834701 – Inventor, Kazumi Masaki – Assignee, Ken Hayashibara. Frequency reduction in human brain wave is inducible by allowing human brain to perceive 4-16 hertz beat sound. Such beat sound can be easily produced with an apparatus, comprising at least one sound source generating a set of low-frequency signals different each other in frequency by 4-16 hertz. Electroencephalographic study revealed that the beat sound is effective to reduce beta-rhythm into alpha-rhythm, as well as to retain alpha-rhythm.
Click on Link for Full Patent: US4834701
Method & System for Altering Consciousness – US5123899 – Inventor & Assignee, James Gall. A system for altering the states of human consciousness involves the simultaneous application of multiple stimuli, preferable sounds, having differing frequencies and wave forms. The relationship between the frequencies of the several stimuli is exhibited by the equation
g=s.sup.n/4 ·fwhere f=frequency of one stimulus; g=frequency of the other stimuli of stimulus; and n=a positive or negative integer which is different for each other stimulus.Click on Link for Full Patent: US5123899
Method of and Apparatus for Inducing Desired States of Consciousness – US5356368 – Inventor, Robert A. Monroe – Assignee, Interstate Industries Inc. Improved methods and apparatus for entraining human brain patterns, employing frequency following response (FFR) techniques, facilitate attainment of desired states of consciousness. In one embodiment, a plurality of electroencephalogram (EEG) waveforms, characteristic of a given state of consciousness, are combined to yield an EEG waveform to which subjects may be susceptible more readily. In another embodiment, sleep patterns are reproduced based on observed brain patterns during portions of a sleep cycle; entrainment principles are applied to induce sleep. In yet another embodiment, entrainment principles are applied in the work environment, to induce and maintain a desired level of consciousness. A portable device also is described.
Click on Link for Full Patent: US5356368
Acoustic Heterodyne Device & Method – US5889870 – Inventor, Elwood G. Norris – Assignee, Turtle Beach Corp. (formerly American Tech Corp.) The present invention is the emission of new sonic or subsonic compression waves from a region resonant cavity or similar of interference of at least two ultrasonic wave trains. In one embodiment, two ultrasonic emitters are oriented toward the cavity so as to cause interference between emitted ultrasonic wave trains. When the difference in frequency between the two ultrasonic wave trains is in the sonic or subsonic frequency range, a new sonic or subsonic wave train of that frequency is emitted from within the cavity or region of interference in accordance with the principles of acoustical heterodyning. The preferred embodiment is a system comprised of a single ultrasonic radiating element oriented toward the cavity emitting multiple waves.
Click on Link for Full Patent: US5889870
Apparatus & Method of Broadcasting Audible Sound Using Ultrasonic Sound as a Carrier – US60552336 – Inventor & Assignee, Austin Lowrey III. An ultrasonic sound source broadcasts an ultrasonic signal which is amplitude and/or frequency modulated with an information input signal originating from an information input source. If the signals are amplitude modulated, a square root function of the information input signal is produced prior to modulation. The modulated signal, which may be amplified, is then broadcast via a projector unit, whereupon an individual or group of individuals located in the broadcast region detect the audible sound.
Click on Link for Full Patent: US6052336
Pulsative Manipulation of Nervous Systems – US6091994 – Inventor & Assignee, Hendricus G. Loos. Method and apparatus for manipulating the nervous system by imparting subliminal pulsative cooling to the subject’s skin at a frequency that is suitable for the excitation of a sensory resonance. At present, two major sensory resonances are known, with frequencies near 1/2 Hz and 2.4 Hz. The 1/2 Hz sensory resonance causes relaxation, sleepiness, ptosis of the eyelids, a tonic smile, a “knot” in the stomach, or sexual excitement, depending on the precise frequency used. The 2.4 Hz resonance causes the slowing of certain cortical activities, and is characterized by a large increase of the time needed to silently count backward from 100 to 60, with the eyes closed. The invention can be used by the general public for inducing relaxation, sleep, or sexual excitement, and clinically for the control and perhaps a treatment of tremors, seizures, and autonomic system disorders such as panic attacks. Embodiments shown are a pulsed fan to impart subliminal cooling pulses to the subject’s skin, and a silent device which induces periodically varying flow past the subject’s skin, the flow being induced by pulsative rising warm air plumes that are caused by a thin resistive wire which is periodically heated by electric current pulses.
Click on Link for Full Patent: US6091994
Method & Device for Implementing Radio Frequency Hearing Effect – US6470214 – Inventors, James P. O’Loughlin & Diana Loree. Assignee, US Air Force. A modulation process with a fully suppressed carrier and input preprocessor filtering to produce an encoded output; for amplitude modulation (AM) and audio speech preprocessor filtering, intelligible subjective sound is produced when the encoded signal is demodulated using the RF Hearing Effect. Suitable forms of carrier suppressed modulation include single sideband (SSB) and carrier suppressed amplitude modulation (CSAM), with both sidebands present.
Click on Link for Full Patent: US6470214
Method & Device for Producing a Desired Brain State – US6488617 – Inventor, Bruce F. Katz – Assignee, Universal Hedonics. A method and device for the production of a desired brain state in an individual contain means for monitoring and analyzing the brain state while a set of one or more magnets produce fields that alter this state. A computational system alters various parameters of the magnetic fields in order to close the gap between the actual and desired brain state. This feedback process operates continuously until the gap is minimized and/or removed.

Multifunctional Radio Frequency Directed Energy System – US7629918 – Inventors, Kenneth W. Brown, David J. Canich & Russell F. Berg – Assignee, Raytheon Co. An RFDE system includes an RFDE transmitter and at least one RFDE antenna. The RFDE transmitter and antenna direct high power electromagnetic energy towards a target sufficient to cause high energy damage or disruption of the target. The RFDE system further includes a targeting system for locating the target. The targeting system includes a radar transmitter and at least one radar antenna for transmitting and receiving electromagnetic energy to locate the target. The RFDE system also includes an antenna pointing system for aiming the at least one RFDE antenna at the target based on the location of the target as ascertained by the targeting system. Moreover, at least a portion of the radar transmitter or the at least one radar antenna is integrated within at least a portion of the RFDE transmitter or the at least one RFDE antenna.
Click on Link for Full Patent: US7629918
Nervous System Excitation Device – US3393279 – Inventor, Flanagan Gillis Patrick – Assignee, Biolectron Inc. (Listening Inc.) A METHOD OF TRANSMITTING AUDIO INFORMATION TO THE BRAIN OF SUBJECT THROUGH THE NERVOUS SYSTEM OF THE SUBJECT WHICH METHOD COMPRISES, IN COMBINATION, THE STEPS OF GENERATING A RADIO FREQUENCY SIGNAL HAVING A FREQUENCY IN EXCESS OF THE HIGHERST FREQUENCY OF THE AUDIO INFORMATTION TO BE TRANSMITTED, MODULATING SAID RADIO FREQUENCY SIGNAL WITH THE AUDIO INFORMATION TO BE TRANSMITTED, AND APPLYING SAID MODULATED RADIO FREQUENCY SIGNAL TO A PAIR OF INSULATED ELECTRODES AND PLACING BOTH OF SAID INSULATED ELECTRODE IN PHYSICAL CONTACT WITH THE SKIN OF SAID SUBJECT, THE STRETCH OF SAID RADIO FREQUENCY ELECTROMAGNETIC FIELD BEING HIGH ENOUGH AT THE SKIN SURFACE TO CAUSE THE SENSATION OF HEARING THE AUDIO INFORMATION MODULATED THEREON IN THE BRAIN OF SAID SUBJECT AND LOW ENOUGH SO THAT SAID SUBJECT EXPERIENCES NO PHYSICAL DISCOMFORT.
Click on Link for Full Patent: US3393279
Method & System for Simplifying Speech Wave Forms – US3647970 – Inventor & Assignee, Gillis P. Flanagan. A speech waveform is converted to a constant amplitude square wave in which the transitions between the amplitude extremes are spaced so as to carry the speech information. The system includes a pair of tuned amplifier circuits which act as high-pass filters having a 6 decibel per octave slope from 0 to 15,000 cycles followed by two stages, each comprised of an amplifier and clipper circuit, for converting the filtered waveform to a square wave. A radio transmitter and receiver having a plurality of separate channels within a conventional single side band transmitter bandwidth and a system for transmitting secure speech information are also disclosed.
Click on Link for Full Patent: US3647970
Intra-Oral Electronic Tracking Device – US6239705 – Inventor & Assignee, Jeffrey Glen. An improved stealthy, non-surgical, biocompatable electronic tracking device is provided in which a housing is placed intraorally. The housing contains microcircuitry. The microcircuitry comprises a receiver, a passive mode to active mode activator, a signal decoder for determining positional fix, a transmitter, an antenna, and a power supply. Optionally, an amplifier may be utilized to boost signal strength. The power supply energizes the receiver. Upon receiving a coded activating signal, the positional fix signal decoder is energized, determining a positional fix. The transmitter subsequently transmits through the antenna a position locating signal to be received by a remote locator. In another embodiment of the present invention, the microcircuitry comprises a receiver, a passive mode to active mode activator, a transmitter, an antenna and a power supply. Optionally, an amplifier may be utilized to boost signal strength. The power supply energizes the receiver. Upon receiving a coded activating signal, the transmitter is energized. The transmitter subsequently transmits through the antenna a homing signal to be received by a remote locator.
Click on Link for Full Patent: US6239705
Method & Apparatus for Analyzing Neurological Response to Emotion-Inducing Stimuli – US6292688 – Inventor, Richard E. Patton – Assignee, Advanced Neurotechnologies, Inc. A method of determining the extent of the emotional response of a test subject to stimului having a time-varying visual content, for example, an advertising presentation. The test subject is positioned to observe the presentation for a given duration, and a path of communication is established between the subject and a brain wave detectoanalyzer. The intensity component of each of at least two different brain wave frequencies is measured during the exposure, and each frequency is associated with a particular emotion. While the subject views the presentation, periodic variations in the intensity component of the brain waves of each of the particular frequencies selected is measured. The change rates in the intensity at regular periods during the duration are also measured. The intensity change rates are then used to construct a graph of plural coordinate points, and these coordinate points graphically establish the composite emotional reaction of the subject as the presentation continues.
Click on Link for Full Patent: US6292688
Portable & Hand-Held Device for Making Humanly Audible Sounds Responsive to the Detecting of Ultrasonic Sounds – US6426919 – Inventor & Assignee, William A. Gerosa. A portable and hand-held device for making humanly audible sounds responsive to the detecting of ultrasonic sounds. The device includes a hand-held housing and circuitry that is contained in the housing. The circuitry includes a microphone that receives the ultrasonic sound, a first low voltage audio power amplifier that strengthens the signal from the microphone, a second low voltage audio power amplifier that further strengthens the signal from the first low voltage audio power amplifier, a 7-stage ripple carry binary counter that lowers the frequency of the signal from the second low voltage audio power amplifier so as to be humanly audible, a third low voltage audio power amplifier that strengthens the signal from the 7-stage ripple carry binary counter, and a speaker that generates a humanly audible sound from the third low voltage audio power amplifier.
Click on Link for Full Patent: US6426919
Signal Injection Coupling into the Human Vocal Tract for Robust Audible & Inaudible Voice Recognition – US6487531 – Inventors & Assignees, Carol A. Tosaya & John W. Sliwa, Jr. A means and method are provided for enhancing or replacing the natural excitation of the human vocal tract by artificial excitation means, wherein the artificially created acoustics present additional spectral, temporal, or phase data useful for (1) enhancing the machine recognition robustness of audible speech or (2) enabling more robust machine-recognition of relatively inaudible mouthed or whispered speech. The artificial excitation (a) may be arranged to be audible or inaudible, (b) may be designed to be non-interfering with another user’s similar means, (c) may be used in one or both of a vocal content-enhancement mode or a complimentary vocal tract-probing mode, and/or (d) may be used for the recognition of audible or inaudible continuous speech or isolated spoken commands.
Click on Link for Full Patent: US6487531
Nervous System Manipulation by Electromagnetic Fields from Monitors – US6506148 – Inventor & Assignee, Hendricus G. Loos. Physiological effects have been observed in a human subject in response to stimulation of the skin with weak electromagnetic fields that are pulsed with certain frequencies near ½ Hz or 2.4 Hz, such as to excite a sensory resonance. Many computer monitors and TV tubes, when displaying pulsed images, emit pulsed electromagnetic fields of sufficient amplitudes to cause such excitation. It is therefore possible to manipulate the nervous system of a subject by pulsing images displayed on a nearby computer monitor or TV set. For the latter, the image pulsing may be imbedded in the program material, or it may be overlaid by modulating a video stream, either as an RF signal or as a video signal. The image displayed on a computer monitor may be pulsed effectively by a simple computer program. For certain monitors, pulsed electromagnetic fields capable of exciting sensory resonances in nearby subjects may be generated even as the displayed images are pulsed with subliminal intensity.
Click on Link for Full Patent: US6506148
Apparatus To Effect Brainwave Entrainment over Premises Power-Line Wiring – US8579793 – Inventor, James David Honeycutt & John Clois Honeycutt, Jr. – Assignee, James David Honeycutt. This invention discloses an apparatus and method to affect brainwave entrainment by Very Low Frequency eXclusive-OR (XOR) modulation of a Very High Frequency carrier over a premise’s power-line Alternating Current (AC) wiring. A microcontroller with stored program memory space is used to store and produce the waveforms that lead to brainwave entrainment by controlling an H-Bridge capable of generating bipolar square waves, which output is capacitive coupled to a premises AC power-line and a light sensing device is used by the microcontroller to determine whether to produce daytime or nighttime entrainment frequencies.
Click on Link for Full Patent: US8579793
Method & System for Brain Entrainment – US20140309484A1 – Inventor & Assignee, Daniel Wonchul Chong. The present invention is a method of modifying music files to induce a desired state of consciousness. First and second modulations are introduced into a music file such that, when the music file is played, both of the modulations occur simultaneously. Additional modulations can be introduced, as well as sound tones at window frequencies.
Click on Link for Full Patent: US20140309484A1
Method of Inducing Harmonious States of Being – US6135944 – Inventors, Gerard D. Bowman, Edward M. Karam & Steven C. Benson – Assignee, Gerard D. Bowman. A method of inducing harmonious states of being using vibrational stimuli, preferably sound, comprised of a multitude of frequencies expressing a specific pattern of relationship. Two base signals are modulated by a set of ratios to generate a plurality of harmonics. The harmonics are combined to form a “fractal” arrangement.
Click on Link for Full Patent: US6135944
Pulse Variability in Electric Field Manipulation of Nervous Systems – US6167304 – Inventor & Assignee, Hendricus G. Loos. Apparatus and method for manipulating the nervous system of a subject by applying to the skin a pulsing external electric field which, although too weak to cause classical nerve stimulation, modulates the normal spontaneous spiking patterns of certain kinds of afferent nerves. For certain pulse frequencies the electric field stimulation can excite in the nervous system resonances with observable physiological consequences. Pulse variability is introduced for the purpose of thwarting habituation of the nervous system to the repetitive stimulation, or to alleviate the need for precise tuning to a resonance frequency, or to control pathological oscillatory neural activities such as tremors or seizures. Pulse generators with stochastic and deterministic pulse variability are disclosed, and the output of an effective generator of the latter type is characterized.
Click on Link for Full Patent: US6167304
Method & System for Brain Entertainment – US8636640 – Inventor, Daniel Wonchul Chang – Assignee, Brain Symphony LLC. The present invention is a method of modifying music files to induce a desired state of consciousness. First and second modulations are introduced into a music file such that, when the music file is played, both of the modulations occur simultaneously. Additional modulations can be introduced, as well as sound tones at window frequencies.
Click on Link for Full Patent: US8636640
Method & Apparatus for Manipulating Nervous Systems – US5782874 – Inventor & Assignee, Hendricus C. Loos. Apparatus and method for manipulating the nervous system of a subject through afferent nerves, modulated by externally applied weak fluctuating electric fields, tuned to certain frequencies such as to excite a resonance in certain neural circuits. Depending on the frequency chosen, excitation of such resonances causes relaxation, sleepiness, sexual excitement, or the slowing of certain cortical processes. The weak electric field for causing the excitation is applied to skin areas away from the head of the subject, such as to avoid substantial polarization current densities in the brain. By exploiting the resonance phenomenon, these physiological effects can be brought about by very weak electric fields produced by compact battery-operated devices with very low current assumption. The fringe field of doublet electrodes that form a parallel-plate condenser can serve as the required external electric field to be administered to the subject’s skin. Several such doublets can be combined such as to induce an electric field with short range, suitable for localized field administration. A passive doublet placed such as to face the doublet on either side causes a boost of the distant induced electric field, and allows the design of very compact devices. The method and apparatus can be used by the general public as an aid to relaxation, sleep, or arousal, and clinically for the control and perhaps the treatment of tremors and seizures, and disorders of the autonomic nervous system, such as panic attacks.
This is every person involved in the main stream media that that is in deep shit with no way out.

  • Clowns Exposed ― Faces Of Seditious Conspirators In The U.S. Media.
  • I'll Kick This Off With The 65 “Journalists” WikiLeaks Revealed Accepted To Work With The DNC And The Hillary Clinton Campaign To Influence And Steal The 2016 U.S. Presidential Election.
https://threadreaderapp.com/embed/1213240094703935488.html
submitted by OwnPlant to conspiracy [link] [comments]

MAME 0.218

MAME 0.218

It’s time for MAME 0.218, the first MAME release of 2020! We’ve added a couple of very interesting alternate versions of systems this month. One is a location test version of NMK’s GunNail, with different stage order, wider player shot patterns, a larger player hitbox, and lots of other differences from the final release. The other is The Last Apostle Puppetshow, an incredibly rare export version of Home Data’s Reikai Doushi. Also significant is a newer version Valadon Automation’s Super Bagman. There’s been enough progress made on Konami’s medal games for a number of them to be considered working, including Buttobi Striker, Dam Dam Boy, Korokoro Pensuke, Shuriken Boy and Yu-Gi-Oh Monster Capsule. Don’t expect too much in terms of gameplay though — they’re essentially gambling games for children.
There are several major computer emulation advances in this release, in completely different areas. Possibly most exciting is the ability to install and run Windows NT on the MIPS Magnum R4000 “Jazz” workstation, with working networking. With the assistance of Ash Wolf, MAME now emulates the Psion Series 5mx PDA. Psion’s EPOC32 operating system is the direct ancestor of the Symbian operating system, that powered a generation of smartphones. IDE and SCSI hard disk support for Acorn 8-bit systems has been added, the latter being one of the components of the BBC Domesday Project system. In PC emulation, Windows 3.1 is now usable with S3 ViRGE accelerated 2D video drivers. F.Ulivi has contributed microcode-level emulation of the iSBC-202 floppy controller for the Intel Intellec MDS-II system, adding 8" floppy disk support.
Of course there are plenty of other improvements and additions, including re-dumps of all the incorrectly dumped GameKing cartridges, disassemblers for PACE, WE32100 and “RipFire” 88000, better Geneve 9640 emulation, and plenty of working software list additions. You can get the source and 64-bit Windows binary packages from the download page (note that 32-bit Windows binaries and “zip-in-zip” source code are no longer supplied).

MAME Testers Bugs Fixed

New working machines

New working clones

Machines promoted to working

Clones promoted to working

New machines marked as NOT_WORKING

New clones marked as NOT_WORKING

New working software list additions

Software list items promoted to working

New NOT_WORKING software list additions

Source Changes

submitted by cuavas to emulation [link] [comments]

Binary Options Real Time - YouTube 2 Minutes Strategy Binary Options 2020 (IQ Options) - YouTube Binary Options Strategy 2020  100% WIN GUARANTEED ... Profitable Indicator 2020 - Binary Options Real Account 95 ... 97% Win Strategy - $2,390 in 9 Mins - Binary Options ... binary options streaming real time forex charts - YouTube

Live chart for binary options online (in real time) I want to share with you is very important information: how to use live charts to trade binary options. Binary Options Real Time Graphs, Indicator With 83% Win-Rate! By investing in your reliance, you can make up to 85 een of real time graphics binary options charts your enie in under an state. Traders profit from price fluctuations in qual ... Binary options charts strategies in real time In general, binary options are relatively short-term investments that require research and technical analysis. Because of this, analysing and interpreting binary options charts is extremely important to the success of any trader, as it will be hard to be profitable without knowing the ins and outs of chart reading and technical analysis. Real Time Graphs Binary Options, strategi pilihan nse. strategi pilihan nse, stock pilihan biner, miten saada bitcoineja pankkitililleni, nachtmode voor warme zomernachten - klingel blog Free Binary Options Charts >>>Click Here To Learn How To Use This Binary Options Chart<<< Different Types of Charts for Binary Options Trading . When you start trading binary options, there are several types of charts you will see most often. Each type of binary options chart has advantages and disadvantages, and once you understand the differences you’ll likely find that one type appeals to ... Where to get more charting. If you have used any of the binary options broker platforms, or you are just a beginner who has looked around one or two of the platforms, one thing will stand out in a glaring fashion: the absence of interactive charts.Charts are the mainstay of technical analysis in the binary options market. Without charts, there would be no analysis of assets for trading ... Binary options graphs provide you with a visual context for placing a trade. How much you rely on the graph data to place your trade will depend on your entry rules. Entry rules are part of coming up with a trading method, also called a trading system. Having a method is a key component to becoming a real, professional trader instead of a gambler. Some trading methods rely heavily on the ... Real time graphics binary options. Posted on November 2, 2020 by . Real Time Graphics Binary Options. binary options firms; investing in bitcoin services inc; binary option lừa đảo; best trading platform for stocks barrons; binary options review.com; This entry was posted in Uncategorized. Bookmark the permalink. Hello world! Leave a Reply Cancel reply. Your email address will not be ... Most transactions and forex trading but when you will generate similarly theres constantly changing ETF’s Instead try to see your loss real time graphics binary options charts ratio in the forex remember that Forex affiliates to get your money. Forex Traders are turning the ones making money by charging the world Entertainment oil climbed right from the system she has been relied upon by ... Free Real Time Binary Option Charts. As soon as it appears, check the target rate is still available on your broker (or close), choose the expiry time and execute the trade as quickly as possible before the reversal is …. Learn how to trade in Nifty with NSE NSE Real Time Live data and charts using Nifty live charts, with the strategy explained in detail. Made for Intra-Day Forex trade ideas ... real time graphics binary options charts Diese 5 Fehler können Ihre binäre Optionen Trading Karriere ruinieren. Jeder liebt die Einnahme von Risiken, aber wenn es um Geld zu investieren, müssen. broker bewertung Diese 5 Fehler können Ihre binäre Optionen Trading Karriere ruinieren. Jeder liebt die Einnahme von Risiken, aber wenn es um Geld zu investieren, müssen.

[index] [5503] [705] [1101] [27336] [20606] [29544] [11838] [4027] [9808] [8081]

Binary Options Real Time - YouTube

Enjoy the videos and music you love, upload original content, and share it all with friends, family, and the world on YouTube. [GET] - Profitable Indicator 2020 - Binary Options Real Account 95% Winrate The Most Profitable Strategy trading with Binary Options. Get Renewed this 2020 a... The road to success through trading IQ option Best Bot Reviews Iq Option 2020 ,We make videos using this softwhere bot which aims to make it easier for you t... Want to start trading binary options but you're not sure which broker to choose or how to trade binary options? Visit http://www.BinaryOptionsTeacher.com tod... 97% Win Strategy - $2,390 in 9 Mins - Binary Options Newest Method 2019 Do not miss! DEMO ACCOUNT: https://goo.gl/mw13WY I want to kindly ask you to subscrib... IQ Options -https://affiliate.iqoption.com/redir/...Please subscribe and leave a like for more videos.Online trading is a very risky investment/profession. It i... Read More Here: https://bit.ly/2Qr3tIA - Not known Factual Statements About Real Time Graphics Binary Options Mt4 Plugin - Binary In such a way similar to On...

http://arab-binary-option.plimvelwrattlaful.tk