Premised on the idea that one cannot know a science without knowing its history, History of Wireless offers a lively new treatment that introduces previously unacknowledged pioneers and developments, setting a new standard for understanding the evolution of this important...

Metallic nanoparticles hold promise for their potential applications in a wide array of disciplines ranging from materials science to medicine. This book brings the power of theoretical methods to an audience of experimentalists, and explicates the simulation of metallic clusters and nanoparticles. It begins with a summary of the current...

That’s why if you plan to set up a wireless...

The authors of this guide present a smorgasbord of tips and techniques for Visual Basic developers. The first part details the new features of Visual Basic 6 and lays out conventions for clear and productive programming style. However, these important preliminary discussions are covered in only two quick chapters, and most of the book is...

The Cocoa programming environment—Apple’s powerful set of clean, object-oriented APIs—is increasingly becoming the basis of almost all contemporary Mac OS X development. With its long history of constant refinement and improvement, Cocoa has matured into a sophisticated programming environment that can make...

Computer users spend a lot of time doing simple, mechanical data manipulation - changing the format of data, checking its validity, finding items with some property, adding up numbers, printing reports, and the like. All of these jobs ought to be mechanized, but it's a real nuisance to have to write a specialpurpose program in a...

• Building application using Kinect for Windows SDK.
• Covers the Kinect for Windows SDK v1.6.
• A practical step-by-step tutorial to make learning easy for a beginner.
• A detailed...

• Design a storage solution for your vSphere environment
• Troubleshoot vSphere Storage performance problems
• An advanced guide to vSphere Storage performance along with best practices to...

• Harness the ability to build algorithms for unsupervised data using deep learning concepts with R
• Master the common problems faced such as overfitting of data, anomalous datasets, image recognition, and performance tuning while building the models
• Build models relating to neural...