Найти книгу: "Face Detection and Adaptation"

There are four fantastic stories, all of which are suitable for creating a film or an epic series. There are four fantastic stories, all of which are suitable for creating a film or an epic series. Features of the transplantation of the mind, the slave-owning and high-tech society of the future, intelligent animals, exploiting people and traveling around the sphere of Dyson await your attention. It’s funny and a bit sad

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.

Practical examples, sample reports, best practices and recommendations to help you deter, detect, and prevent financial statement fraud Financial statement fraud (FSF) continues to be a major challenge for organizations worldwide. Financial Statement Fraud: Prevention and Detection, Second Edition is a superior reference providing you with an up-to-date understanding of financial statement fraud, including its deterrence, prevention, and early detection. You will find A clear description of roles and responsibilities of all those involved in corporate governance and the financial reporting process to improve the quality, reliability and transparency of financial information. Sample reports, examples, and documents that promote a real-world understanding of incentives, opportunities, and rationalizations Emerging corporate governance reforms in the post-SOX era, including provisions of the SOX Act, global regulations and best practices, ethical considerations, and corporate governance principles Practical examples and real-world «how did this happen» discussions that provide valuable insight for corporate directors and executives, auditors, managers, supervisory personnel and other professionals saddled with anti-fraud responsibilities Expert advice from the author of Corporate Governance and Ethics and coauthor of the forthcoming Wiley textbook, White Collar Crime, Fraud Examination and Financial Forensics Financial Statement Fraud, Second Edition contains recommendations from the SEC Advisory Committee to reduce the complexity of the financial reporting process and improving the quality of financial reports.

The definitive book on adapting the classic work of Richard Wyckoff to today's markets Price and volume analysis is one of the most effective approaches to market analysis. It was pioneered by Richard Wyckoff, who worked on Wall Street during the golden age of technical analysis. In Trades About to Happen, veteran trader David Weis explains how to utilize the principles behind Wyckoff's work and make effective trades with this method. Page by page, Weis clearly demonstrates how to construct intraday wave charts similar to Wyckoff's originals, draw support/resistance lines, interpret the struggle for dominance in trading ranges, and recognize action signals at turning points. Analyzes markets one bar chart at a time, which recreates the ambiguity of actual trading Emphasizes reading price/volume charts without a secondary reliance on mathematical indicators Includes a short study guide in the appendix to help readers master the material Filled with in-depth insights and practical advice, Trades About to Happen promises to be the definitive work on utilizing Wyckoff's classic methods in today's turbulent markets.

A powerful new tool for all forensic accountants, or anyone who analyzes data that may have been altered Benford's Law gives the expected patterns of the digits in the numbers in tabulated data such as town and city populations or Madoff's fictitious portfolio returns. Those digits, in unaltered data, will not occur in equal proportions; there is a large bias towards the lower digits, so much so that nearly one-half of all numbers are expected to start with the digits 1 or 2. These patterns were originally discovered by physicist Frank Benford in the early 1930s, and have since been found to apply to all tabulated data. Mark J. Nigrini has been a pioneer in applying Benford's Law to auditing and forensic accounting, even before his groundbreaking 1999 Journal of Accountancy article introducing this useful tool to the accounting world. In Benford's Law, Nigrini shows the widespread applicability of Benford's Law and its practical uses to detect fraud, errors, and other anomalies. Explores primary, associated, and advanced tests, all described with data sets that include corporate payments data and election data Includes ten fraud detection studies, including vendor fraud, payroll fraud, due diligence when purchasing a business, and tax evasion Covers financial statement fraud, with data from Enron, AIG, and companies that were the target of hedge fund short sales Looks at how to detect Ponzi schemes, including data on Madoff, Waxenberg, and more Examines many other applications, from the Clinton tax returns and the charitable gifts of Lehman Brothers to tax evasion and number invention Benford's Law has 250 figures and uses 50 interesting authentic and fraudulent real-world data sets to explain both theory and practice, and concludes with an agenda and directions for future research. The companion website adds additional information and resources.