Chapter 10 Auditing the Revenue Process SEC SAB101: Revenue recognition 1. 有persuasive evidence 有证据 2. Delivery occurred‚ service rendered，东西给了服务于需求 3. Price is fixed/determinable 价格固定 4. 有collectability钱收的回来 Fraud Risk in Revenue cycle: 欺诈风险 1. Side agreement: off-book‚ adjust record to entice customer 2. Channel stuffing: 填塞分销渠道，造成销售假象 inflate sales by forcing product through a distribution channel 3. Related party transaction: 实质重于形式原则substance over form是指企业应当按照交易或事项的经济实质进行会计核算，而不应当仅仅按照它们的法律形式作为会计核算的依据
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Enhancement Segmentation Technique for Iris Recognition System Based on Daugman’s Integro-Differential Operator Asama Kuder Nsaef Institute of Visual Informatics (IVI) Universiti Kebangsaan Malaysia Bangi‚ Selangor‚ Malaysia osama_ftsm@yahoo.com Azizah Jaafar Institute of Visual Informatics (IVI) Universiti Kebangsaan Malaysia Bangi‚ Selangor‚ Malaysia aj@ftsm.ukm.my Khider Nassif Jassim Faculty of Management and Economics Department of Statistics University of Wasit Al-Kut‚ Iraq khider_st@yahoo
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Related Literature Related literatures refer to the list of reference related to the study being conducted. This will serve as a guide. According to: Anil K. Jain‚ Brendan Klare‚ and Unsang Park of Michigan State University. Face Recognition Face recognition is the task of recognizing a person using digital face images. A FRS is typically designed to output a measure of similarity between two face images. Automated FRSs typically involve finding key facial landmarks (such as the center of
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cues other than name recognition‚ they were able to assess and accurately determine the importance of name recognition in electoral decisions. Other cues that were identified within the study included gender‚ incumbency status‚ spending‚ etc. The approach to this study was very deductive—the study started with basic name recognition progressively dials in on it’s importance compared to other cues. Now‚ the independent variable in each of the studies is going to be name recognition. Who the subjects
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AUTOMATIC FACE RECOGNITION INTRODUCTION: A facial recognition system is a computer application for automatically identifying or verifying a person from a digital image or a video frame from a video source. One of the ways to do this is by comparing selected facial features from the image and a facial database. It is typically used in security systems and can be compared to other biometrics such as fingerprint or eye iris recognition systems. Final template TRADITIONAL TECHNIQUES:
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appear. This paper will evaluate face recognition‚ identification‚ and classification on it. The second part will explain the role of concepts and categories in face recognition. The paper will evaluate the role of encoding and retrieval using long-term memory and the effects of face recognition. Finally‚ the possibly of errors can happen with race recognition. Face Recognition‚ Identification‚ and Classification Over the past decade or so face recognition has become a popular area of research
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Voice recognition software Patrick Maxfield CIS/207 July 24‚ 2013 Luciano Brito Voice recognition software Voice recognition software has come a long ways in a short time. It was first used in home appliances such as washing machines so the consumer could operate the washing controls through vocal commands and then the invention of mobile phones with voice-activated dialing came along. Know day’s voice recognition is so widely used that I could not begin to identify them all. The technology
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“Thoughts” on Redistribution and Recognition The ideas of redistribution and recognition by Fraser‚ really intrigued me to further my thoughts on these concepts. Fraser explains that recognition can be a cultural group looking for recognition of difference whereas redistribution is classified as a transfer or reduction of socioeconomic classes. This made me wonder‚ does redistribution include a progression of taxes according to income? If this is true‚ I can see a strong indication of how this
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Pattern recognition is a useful tool for mathematics‚ mathematical visualization‚ and art. After a brief description of Bongard’s methodology in the field of pattern recognition‚ the author introduces the concept of colour modularity and evaluates how it affects pattern recognition classification. Combining Bongard’s methodology and colour modularity‚ the author attains a richer‚ more persuasive dynamic in pattern description and recognition of five- and ten-pointed star polygons.". Keywords: pattern
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said Jackie Fenn‚ a Fellow in emerging trends and technologies for Gartner‚ a market research firm. GESTURE-RECOGNITION TECHNOLOGY In the early 1960s‚ users could move a light-emitting pen to control the Sketchpad computer-aided design system. Several subsequent commercial systems also worked with light-emitting pens. Research into camera-based computer vision for gesture recognition began in earnest in the early 1990s at places such as the Massachusetts Institute of Technology Media Lab‚ Japan’s
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