Найти книгу: "Single-Molecule Optical Detection, Imaging and Spectroscopy"


Single-Molecule Optical Detection, Imaging and Spectroscopy Single-Molecule Optical Detection, Imaging and Spectroscopy

Автор: M. Orrit

Год издания: 0000

Single Molecule Spectroscopy is one of the hottest topics in today's chemistry. It brings us close to the the most exciting vision generations of chemists have been dreaming of: To observe and examine single molecules! While most of chemistry deals with myriads of molecules, this books presents the latest developments for the detection and investigation of single entities. Written by internationally renowned authors, it is a thorough and comprehensive survey of current methods and their applications.
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Автор: Джеймс Барри

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Автор: Buckstone John Baldwin

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Автор: Даниэль Дефо

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Fraud Analytics Using Descriptive, Predictive, and Social Network Techniques. A Guide to Data Science for Fraud Detection Fraud Analytics Using Descriptive, Predictive, and Social Network Techniques. A Guide to Data Science for Fraud Detection

Автор: Bart Baesens

Год издания: 

Detect fraud earlier to mitigate loss and prevent cascading damage Fraud Analytics Using Descriptive, Predictive, and Social Network Techniques is an authoritative guidebook for setting up a comprehensive fraud detection analytics solution. Early detection is a key factor in mitigating fraud damage, but it involves more specialized techniques than detecting fraud at the more advanced stages. This invaluable guide details both the theory and technical aspects of these techniques, and provides expert insight into streamlining implementation. Coverage includes data gathering, preprocessing, model building, and post-implementation, with comprehensive guidance on various learning techniques and the data types utilized by each. These techniques are effective for fraud detection across industry boundaries, including applications in insurance fraud, credit card fraud, anti-money laundering, healthcare fraud, telecommunications fraud, click fraud, tax evasion, and more, giving you a highly practical framework for fraud prevention. It is estimated that a typical organization loses about 5% of its revenue to fraud every year. More effective fraud detection is possible, and this book describes the various analytical techniques your organization must implement to put a stop to the revenue leak. Examine fraud patterns in historical data Utilize labeled, unlabeled, and networked data Detect fraud before the damage cascades Reduce losses, increase recovery, and tighten security The longer fraud is allowed to go on, the more harm it causes. It expands exponentially, sending ripples of damage throughout the organization, and becomes more and more complex to track, stop, and reverse. Fraud prevention relies on early and effective fraud detection, enabled by the techniques discussed here. Fraud Analytics Using Descriptive, Predictive, and Social Network Techniques helps you stop fraud in its tracks, and eliminate the opportunities for future occurrence.