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cloudbearings's Projects

airport-delays icon airport-delays

A simulation of the US air traffic network with a best-path finder for flights and a KML heat map generator.

amortization_methods icon amortization_methods

Functions to calculate a 4th variable give only 3 variables. That is, if given principal amount, interest rate, and payment amount, calculate time period. Any combination of three variables will yield the 4th missing variable. Written in Java. Eventually intended to be the core of an Android app.

ampache icon ampache

A web based audio/video streaming application and file manager allowing you to access your music & videos from anywhere, using almost any internet enabled device.

ansible-spring-xd icon ansible-spring-xd

This is an Ansible project to deploy SpringXD, Zookeeper, Redis and HSQLDB as a 6-node fully working SpringXD cluster.

appdirectintegration icon appdirectintegration

A simple java web application to integrate with AppDirect and to leverage the AppDirect's marketplace

arbor icon arbor

Augmented Reality Web Service

aresume icon aresume

An eye-tracking research found out that recruiters spend only 6 seconds reviewing an individual resume (http://cdn.theladders.net/static/images/basicSite/pdfs/TheLadders-EyeTracking-StudyC2.pdf). AResume is an augmented reality app that makes the process of reading a resume fun and interactive. It does so

ariss icon ariss

It consists in an augmented reality android application that will enable to spot the station by using a smartphone camera.

armuseum icon armuseum

A Augmented Reality Museum visiting Android App

artex icon artex

Augmented Reality Text Translation

atmosphere-rabbitmq-example icon atmosphere-rabbitmq-example

Servlet Atmosphere framework example showing push directly to the client from a rabbitmq ( spring-rabbit) message. Scaffold app produced using thymeleaf with tiles and spring mvc.

atom icon atom

Originally, ATOM (Automated Theory of Mind) was intended to be a rule-based simulation of how people form intentions from goals, beliefs, and other states. It also aimed to model how people monitor their progress on intentions. It was to be implemented in Prolog (for the agent reasoning parts) and in Java (for simulated physical environments for the agents, and for generating graphical views). The Prolog portion would require infrastructure that isn't built-in to Prolog in order for unit-testing to be possible, and we need automated testing for the ever-larger chunks of reasoning that each agent will be designed to do. Such tests require tight control of initial conditions, such as the environment, and the plan was that, eventually, the Prolog unit-tester would be integrated with a parent TestNG tester in Java. At this point, ATOM is an inference engine capable of both backward and forward-chaining, and of maintaining a trace of its reasoning. Such traces are used to verify the reasoning, and this aspect of the original design was achieved. However, the objective to simulate attributions of mental states, particularly now when we have chosen to use simple animations like Heider and Simmel's (1944), appears to require an ability to propagate constraints before committing to var bindings. For constraint propagation, we are moving away from Amzi Prolog (which nonetheless has the best Prolog debugger I've seen) to ECLiPSe which is another flavor of Prolog whose primary use is constraint propagation and which has an active user base that includes AI researchers. We plan to continue using ATOM as the core reasoning engine of the Wayang project, which is ECLiPSe-based and has already been embedded in Java (allowing for integrations such as Adobe SWF-parsing, visualizations, and the TestNG testing framework). --David Pautler 2009-12-04

augmented-reality-app-backend icon augmented-reality-app-backend

The backend for an augmented reality android app which makes employee collaboration with virtual notes in a real room possible.

bacsexportreport icon bacsexportreport

Demonstration Query for hiring. This MySQL query produces data for Barclays batch payment from my employer's database.

car-price-prediction-system icon car-price-prediction-system

Technologies: Nutch 1.6, MapReduce in Java, Mahout. For selling a used car, its price can be predicted by giving some attributes. e.g. Car Model, total miles, engine type. Trained data will be provided to our system to predict the price for new data. Used Nutch to crawl car data from 52 states which is on craigslist.org. Over 0.3 million records were fetched. The content was then pruned using two MapReduce Jobs. The first MapReduce cleaned the data removing unwanted unicode symbols and incomplete data (information without car model or total miles or engine or price). The Second MapReduce extracted the required attributes and emitted in tsv format. This tsv was then provided to a Naïve Based Classifier in Mahout. A classification model was built from the training data. This models predicts the price when attributes like car model model, miles, engine was provided.

class-reload-agent icon class-reload-agent

Monitors Java class files in the file system for changes and reloads them into a running Java virtual machine. Use this during development to reload classes instead of redeploying an application.

clienda icon clienda

Android app to manage clients, orders and payments.

cloud-pokes icon cloud-pokes

Lightweight Java library for sending push notifications to iOS or Android devices via APNS or GCM.

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