ESTIMATING THE RISK PREMIUM USING HISTORICAL DATA: A CASE OF THE NSE Introduction This study seeks to estimate the risk premium of a company using historical data. Analysts use historical data to estimate the risk premium of a company’s equity. This is because the historical data is readily available from the company’s financial statements and the securities exchanges for example the Nairobi Stock Exchange (NSE) in Kenya. Historical market data can be used to compute average returns and a measure
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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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Business Horizons (2009) 52‚ 357—365 www.elsevier.com/locate/bushor Social media: The new hybrid element of the promotion mix W. Glynn Mangold a‚*‚ David J. Faulds b a b College of Business & Public Affairs‚ Murray State University‚ Murray‚ KY 42071‚ U.S.A. College of Business Administration‚ University of Louisville‚ Louisville‚ KY 40292‚ U.S.A. KEYWORDS Integrated marketing communications; Social media; Consumer-generated media; Promotion mix Abstract The emergence of Internet-based
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Ms. Ellen I remember when I came from the Dominican Republic to USA. I was so frustrated because of the weather and language barrier. After two months my life started. I was going shopping‚ and going to restaurants Etc. One night I was thinking that I needed a job for many reasons. First‚ I needed to help my mom. Second‚ I wanted to be productive. After I knocked many doors‚ surfed the internet several times and hunted jobs everywhere with no good results finally I found someone who believed in
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APPLICATIONS AND REVIEWS‚ VOL. 37‚ NO. 3‚ MAY 2007 311 Gesture Recognition: A Survey Sushmita Mitra‚ Senior Member‚ IEEE‚ and Tinku Acharya‚ Senior Member‚ IEEE Abstract—Gesture recognition pertains to recognizing meaningful expressions of motion by a human‚ involving the hands‚ arms‚ face‚ head‚ and/or body. It is of utmost importance in designing an intelligent and efficient human–computer interface. The applications of gesture recognition are manifold‚ ranging from sign language through medical rehabilitation
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actions like kicking and punching as part of general Interaction detection was the initial step towards violent action recognition. Many methods were proposed for this purpose which includes Background subtraction or Human detection‚ Feature extraction and Classification. [4] address the problem of detecting human violence in video‚ such as fist fighting‚ kicking‚ hitting with objects. To detect violence this method rely on motion trajectory information and on orientation information of a person’s limbs
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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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of visual object processing. The experiment was based on the premis that participants would take longer to name visually presented objects whose characteristics were structurally similar compared to structurally distinct. We did not find evidence to support the cascade or sequential models for visually presented object naming. Introduction This investigation aims to repeat work carried out by Humphreys‚ Riddoch and Quinlan (1988) on the distinctions made in visual recognition and naming
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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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Disadvantages: a. Iris Recognition is intrusive. b. Due to fluctuations‚ the Iris is hard t pinpoint c. Iris Recognition is very expensive A. The iris is a small target and a scan cannot be performed properly if the person is more than a few meters way. In order for an iris to be properly scanned‚ the person’s head must be completely still. Eyelashes‚ lenses‚ and anything that would cause a reflection‚ could all make a scan difficult. It is a moving target and can be obscured by objects such as the eyelid
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