By Energy.Gov Annual reports analyzing the wind energy industry released today by the Energy Department show continued rapid growth in wind power installations in 2015, demonstrating market resilience and underscoring the vitality of the U.S. wind energy market on a … Continue reading →

By Joel Bahr Berkeley News A new study co-authored by UC Berkeley professor Michael Manga confirms that earthquakes in America’s oil country — including a 4.8 magnitude quake that rocked Texas in 2012 — are being triggered by significant injections … Continue reading →

What Is Real-Time Conversation Analytics?

In contrast to post-call conversation analytics, which provides insights after the fact, real-time call conversation analytics can point them out at present times.

In this blog, I will walk through the essential steps to build a web app that can analyze call conversations in real-time to assist an agent. Once we’re finished, we’ll have an app which will:

Welcome back! In the first part of this series, we looked at a very "low-level" way to interact with a relational database by sending it raw SQL strings and retrieving the results. We created a very simple Express application that we can use as an example and deployed it on Heroku with a Postgres database.

In this part, we're going to examine a few libraries which build on top of that foundation, adding layers of abstraction that let you read and manipulate database data in a more "JavaScript-like" way.

[In the second part of his series, a Zone Leader begins the process of using Heroku for the very first time. In this article, he walks through the new account process, then performs the necessary setup of a database and RESTful API for use with the application built for a family member.]

In the "Moving Away From AWS and Onto Heroku" article, I provided an introduction of the application I wanted to migrate from Amazon's popular AWS solution to Heroku. While AWS is certainly meeting the needs of my customer (my mother-in-law), I am hoping for a solution that allows my limited time to be focused on providing business solutions instead of getting up to speed with DevOps processes.

“In computing, memoization or memoisation is an optimization technique used primarily to speed up computer programs by storing the results of expensive function calls and returning the cached result when the same inputs occur again” — Wikipedia article on memoization. 

I've written a two part article in Memoization in JavaScript. The first part explains the concept with basic implementation in JavaScript code. It details a way to apply the technique on function calls. It is generic to handle most JavaScript functions.

In the Alexa Skills for Node.JS ASK SDK development world, the Alexa Skills Kit (ASK) Command-Line Interface (CLI) is one of the most overlooked tools.

Boosting Developer Productivity

With proper use, one could really increase productivity when developing Alexa Skills. This is especially so if you are creating many Alexa Skills, either because you are in the learning process or you are just managing multiple Alexa Skills projects for yourself or your clients.

In the "Moving Away From AWS and Onto Heroku" article, I provided an introduction of the application I wanted to migrate from Amazon's popular AWS solution to Heroku.  Subsequently, the "Destination Heroku" article illustrated the establishment of a new Heroku account and focused on introducing a Java API (written in Spring Boot) connecting to a ClearDB instance within this new platform-as-a-service (PaaS) ecosystem.  My primary goal is to find a solution that allows my limited time to be focused on providing business solutions instead of getting up to speed with DevOps processes.

Quick Recap

As a TL;DR (too long; didn't read) to the original article, I built an Angular client and a Java API for the small business owned by my mother-in-law.  After a year of running the application on Elastic Beanstalk and S3, I wanted to see if there was a better solution that would allow me to focus more on writing features and enhancements and not have to worry about learning, understanding, and executing DevOps-like aspects inherent within the AWS ecosystem.

Handling user input with forms is the cornerstone of many common applications.

Applications use forms to enable users to log in, to update a profile, to enter sensitive information, and to perform many other data-entry tasks

Lambda functions are quite an intuitive concept of Modern C++ introduced in C++11, so there are already tons of articles on lambda function tutorials over the internet. But still, there are some untold things (like IIFE, types of lambda, etc.) left, which nobody talks about. Therefore, here I am to not only show you lambda function in C++, but we'll also cover how it works internally and other aspects of Lambda.

The title of this article is a bit misleading. Because lambda doesn't always synthesize to function pointer. It's an expression (precisely unique closure). But I have kept it that way for simplicity. So from now on, I will use lambda function and expression interchangeably.

See the Code - See it Full Page - See Details

This Pen uses: HTML, CSS, JavaScript, and

See the Code - See it Full Page - See Details

Horizontal and Vertical scrolling with faded out content. **Please note:** I have not cross browser tested this, however this method leverages `background-attachment: local`, currently usable in everything except Android Browser & Opera Mini according to <a href="https://caniuse.com/#feat=background-attachment" target="_blank">caniuse.com</a>, meaning there is great support across devices and many Android devices use Google Chrome for Android rather than the OS browser. **Additional note:** There is a bug when previewing this pen on mobile, due to loading the example within an `iframe`. The shadow rgba values are read as a non transparent, this does not happen when previewing locally not in an iframe :-)

This Pen uses: HTML, SCSS, JavaScript, and

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