I came across another silly little bug today. Take a look at the code below (assume ‘days’ is a parameter and that this snippet is part of a larger function)
Date now = new Date();
long nowMillis = now.getTime();
Timestamp nowTimestamp = new Timestamp(nowMillis);
long future = 3600 * 24 * days * 1000;
Timestamp expiryTimestamp = new Timestamp(nowMillis + future);
System.out.println(nowTimestamp);
System.out.println(expiryTimestamp);
Can you tell what is wrong with it ? What the code intends to do is to set an expiry timestamp to an element – X days from today. A caller called this code snippet with the value 5. Well there is nothing wrong so far. Here is the output
2010-04-27 10:37:10.497
2010-05-02 10:37:10.497
So then came along an element that needed an expiry of around 40 days. The caller calls with the value 40. Guess what the output is
2010-04-27 10:38:43.372
2010-04-17 17:35:56.076
I moved all development activities to linux recently. Part of the migration process involved getting used to some new apps like Kopete / Pidgin / KDE Snapshot etc. It was a breeze until I started debugging my code in eclipse.
I frequently use the eclipse keyboard shortcuts to cut down the time I spend coding / debugging. One of my favorite is Ctrl + Shift + i , which will open up the inspection box for a particular variable. This shortcut just did not work. For quite a few days I did not understand why. The other shortcuts like fix imports ( ctrl + shift + o ) seemed to be working fine. That’s when I stumbled across a kopete shortcut.
The java neural network Neuroph was making news recently about its integration with Hadoop. Neural networks can solve some interesting problems once they are trained. This article aims to provide the baby steps necessary to writing your first java program that loads a trained neural network.
Before you even begin to read anything that follows, a basic understanding of neural network terminology and the concept behind the same is necessary. The following articles are great starting points to understanding neural networks
Neuroph and neural networks – Part 1
Neuroph and neural networks – Part 2
Neuroph and neural networks – Part 3
Intro to neural networks
Cars and Signals:
We will simulate the scenario where cars wait at a signal and move only when the lights are green. This simple example should help get you started. Our aim is to define a neural network with the easyNeurons swing application; train it; import it into java and use it in an application.
I had the opportunity to work with the ATOM protocol in detail recently. One of the products related to ATOM that I stumbled across is the AtomServer. If you dont already know it, ATOM is accompanied by a publishing protocol. Its called ATOMPub in short. Unlike RSS this protocol allows you to perform CRUD operations on the entries that you define under a feed.
What does that mean ? For example, you could have an entry in a feed which you wish to edit. You can edit / remove this entry using PUT / DELETE HTTP requests to an appropriate URL hosted by a server. So this protocol allows a user to interact with the feed (among other things. The ATOM XML format can be extended).