SAP Note 1431798 Oracle 11.2.0: Database Parameter Settings Note Language: English Version: 47 Validity: Valid Since 21.02.2012 Summary Symptom This note contains SAP’s recommendations for the optimal configuration of Oracle Database Release 11.2. These parameter recommendations are relevant for all SAP products. This note will be updated regularly once a month. Beyond that‚ changes will only be made in exceptional cases for critical Oracle parameters. Change history: o February 14‚ 2012:
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theory postulated that in determining a strategic asset allocation an investor should choose from among the efficient portfolios consistent with that investor’s risk tolerance amongst other constraints and objectives. Efficient portfolios make efficient use of risk by offering the maximum expected return for specific level of variance or standard deviation of return. Therefore‚ the asset returns are considered to be normally distributed. Efficient portfolios plot graphically on the efficient frontier‚
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Sales Force Optimization: A Self Assessment Glen S. Petersen Copyright 2011‚ All Rights Reserved Page 1 Sales Force Optimization: A Self Assessment Table of Contents Chapter 1 Introduction................................................................................................................ 3 Chapter 2 Sales Force Optimization........................................................................................... 5 Chapter 3 Trends That Impact Sales Force Performance
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number of road accidents in the world. In this paper‚ we propose a highly efficient system to monitor the driving patterns. We shall use accelerometer and orientation sensor that are present in most of today’s smartphones. The solution will bring down the use of specialized hardware thus helping reduce cost and making implementation faster and easier. We shall use a pattern matching algorithm to compare the drivers’ driving style to predefined patterns depicting rash driving. These patterns
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LOG 501 Forecasting at EBBD Module 2 Jose Silva To: Report to Danny Wilco From: Jose Silva Subect: Forecasting at EBBD Problem Situation: The management team at EBBD wanted me to look deeper into the way EEBD utilizes forecasting methods‚ what other techniques are out there that could be available‚ and how they can improve their short term forecasting on an annual‚ quarterly‚ and monthly basis. They are also
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JMH follows different predictive models in order to enhance customer experience‚ and to increase customer referral as well. I will address 2 examples on how JMH uses predictive models. JMH created a predictive model based on member’s use of the ER (Emergency Room) services‚ it has been identified that if a patient has a constant use of the ER is more likely to become a mental health insurance user‚ with this information JMH is able to target recurrent users of the ER as potential members. The other
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Which of the following is the least useful sales forecasting model to use when sales are increasing? Select one: Trend adjusted exponential smoothing Weighted moving average Naïve Exponential smoothing ? Simple mean x Which of the following forecasting methods is most likely to be implemented to change an existing quantitative forecast to account for a new competitor in the marketplace? Select one: Gamma method Executive opinion Market research Naïve method Delphi method
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Linear Predictive Coding Jeremy Bradbury December 5‚ 2000 0 Outline I. II. Proposal Introduction A. Speech Coding B. Voice Coders C. LPC Overview III. Historical Perspective of Linear Predictive Coding A. B. C. IV. V. VI. History of Speech & Audio Compression History of Speech Synthesis Analysis/Synthesis Techniques Human Speech Production LPC Model LPC Analysis/Encoding A. B. C. D. E. Input speech Voice/Unvoiced Determination Pitch Period Estimation Vocal Tract Filter Transmitting the Parameters
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Second difference 13 Forecast based on ARIMA (0‚ 1‚ 4) model 13 Return the seasonal factors for forecasting 14 Part 4. Discussion of different methods and the results 15 Comparison of different methods in terms of time series plot 15 Comparison of different models in terms of error 17 Assumptions and the discussion on the sensitivity of assumptions 18 Conclusion 18 Business Forecasting Coursework Introduction The data of this coursework were drawn from the UK national statistics.
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Modeling Industry By: Alicia Louvan Did you know that the average height of a female model is around 5’10-5’11’ and weight is 120-124 pounds? When the actual healthy weight for women that is 5’10’-5’11 should weigh around 142-150 pounds‚ to me that is ridiculous and is a significant difference in weight (Evea). What the modeling industry has brought to society and to young teenage women is that apparently it is okay to be the size of a stick. I personally think that that it is completely unhealthy
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