...article info Article history: Received 20 July 2010 Received in revised form 1 October 2011 Accepted 3 October 2011 Available online xxxx Keywords: Tumor growth Gompertz model Non-linear observer Non-linear systems discretization abstract Cancer represents one of the most challenging issues for the biomedical research, due its large impact on the public health state. For this reason, many mathematical methods have been proposed to forecast the time evolution of cancer size and invasion. In this paper, we study how to apply the Gompertz’s model to describe the growth of an avascular tumor in a realistic setting. To this aim, we introduce mathematical techniques to discretize the model, an important requirement when discrete-time measurements are available. Additionally, we describe observed-based techniques, borrowed from the field of automation theory, as a tool to estimate the model unknown parameters. This identification approach is a promising alternative to traditional statistical methods, and it can be easily extended to other models of cancer growth as well as to the evaluation of not measurable variables, on the basis of the available measurements. We show an application of this method to the analysis of solid tumor growth and parameters estimation in presence of a...
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... TYPES OF DATA The first step in using statistics to make better decisions is to obtain measurements. There are two major types of measurements: quantitative and categorical. Task time, number of usability problems, and rating-scale data are quantitative. Things like gender, operating system, and usability problem type are categorical variables. Quantitative data fall on a spectrum from continuous to discrete-binary, as shown in Figure A.1. Note that the extreme discrete end of this spectrum includes binary categorical measurements such as pass/fail and yes/no. The more discrete the data, the larger the required sample size for the same level of precision as a continuous measure. Also, you’ll usually use different statistical tests for continuous versus discrete data (see Chapters 3–6). Discrete data have finite values, or buckets. You can count them. Continuous data technically have an infinite number of steps, which form a continuum. The number of usability problems would be discrete—there are a finite and countable number of observed usability problems. Time to complete a task is continuous since it could take any value from 0 to infinity, for example, 178.8977687 seconds. You can tell the difference between discrete and continuous data because discrete data can usually be preceded by the phrase “number of...
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...CEO Turnover in large Russian firms Introduction The main responsibility of Chief Executive Officer (CEO) is to form and implement strategic goals, policies and plans of the firms. The most studies show that Executive turnover has positive or negative impacts on firm performance. The decision of CEO’s change is an extremely important issue especially for the firms. There are two ways for a firm to change CEO. First one consists of the obligatory change of CEO depending on external influences due to worsening of firm’s performance. Second one (internal) consists of the resignation of CEO due to better career opportunities, this is a voluntary change, and board initiated turnover. Majority of the studies found in literature review show that CEO decisions and the change of CEO are influential factors on firm’s financial performance and vice versa. Studies such as Helmich (1974), Davidson et al. (1993) have approve that CEO turnover depends on firms' performance positively while Grusky (1964), Allen et al. (1979), Carroll (1984), Beatty and Zajac (1987), Haveman (1993) have argued that CEO change is effecting firms’ performance in a negative way. On the other hand, Boeker (1992) have argued that CEO turnover is not effective at all on firm’s performance. Other than these studies, Kesner and Sebora (1994) have used CEO turnover as a dependent variable. The results of their study showed that the higher turnover CEO results in lower firm performance. Similarly Virany...
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...Interest Rate Models, edited by Risk Publications, Alan Brace (1996)] [reprinted in The Debt Market, edited by Stephen Ross and Franco Modigliani (Edward Lear Publishing 2000)] [reprinted in The International Library of Critical Writings in Financial Economics: Options Markets edited by G.M. Constantinides and A..G. Malliaris (Edward Lear Publishing 2000)] Abstract This paper presents a simple discrete-time model for valuing options. The fundamental economic principles of option pricing by arbitrage methods are particularly clear in this setting. Its development requires only elementary mathematics, yet it contains as a special limiting case the celebrated Black-Scholes model, which has previously been derived only by much more difficult methods. The basic model readily lends itself to generalization in many ways. Moreover, by its very construction, it gives rise to a simple and efficient numerical procedure for valuing options for which premature exercise may be optimal. ____________________ † Our best thanks go to William Sharpe, who first suggested to us the advantages of the discrete-time...
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...Report on the Factors influencing house prices in Ames, Iowa. Name: Michelle O’ Regan Student number: 114462288 Degree: BSc Finance. Second Year Word Count: 1822 (not including appendix) Submission Date: 14th April, 2016 Introduction Throughout this report I endeavour to present a clear, concise documentation of the factors that influence house prices in Ames, Iowa. I will initiate this report with my estimate of the possible regression based on my economic theory, create a dummy variable in respect to the absence/presence of a garage, followed by a comprehensive description of continuous and discrete variables. Preceding this I aim to report an extensive description of my estimated regression, test said regression for multicollinearity and heteroscedasticity, predict possible solutions to these problems and re run the regression taking into consideration the possible solutions. Main Body Part (a) From my study of econometrics and my knowledge of house prices, the following equation is my estimate of the factors that influence the price of houses PR= f (SI, YD, GA, lnAGE) + + + - (see appendix 1.1 for variable details) My reasoning for the inclusion of the above variables and their predicted signs are as follows: SI: Generally speaking, the larger the home the more you pay as house buyers like to buy houses with as much...
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...this project, Ma’am Lizbeth for the valuable guidance and advice. We also would like to thank her for showing us some example that related to the topic of our project. Also, we would like to thank Ma’am Ariane (AVON) for providing us with a good environment and valuable information, and for guiding us on our project. Finally, honourable mentions go to our families and friends for the support and help they gave us in doing this project. Without the help of the individuals mentioned above, we would face many difficulties while doing this. 2 TABLE OF CONTENTS TITLE PAGE ACKNOWLEDGEMENT TABLE OF CONTENTS EXECUTIVE SUMMARY 1 2 3 4 1.0 COMPANY PROFILE 2.0 INTRODUCTION 2.1 Background and significance of the study 2.2 Statement of the problem 2.3 Objective of the study 2.4 Scope and limitations of the study 2.5 Date and Place of the study 2.6 Roadmap/Milestones 3.0 DESCRIPTION OF SYSTEM UNDER STUDY 3.1 Overview of Processes 4.0 DATA FLOW DIAGRAMS 4.1 Context Diagram 4.2 Diagram 0 5.0 DATA DICTIONARY 6.0 KEYWORD GLOSSARY 7.0 TRANSORM DESCRIPTION 8.0 RECOMMENDATIONS 8.1 Summary of Recommendation 8.2 Domain of Change 8.3 Data Flow Diagram 8.4 Data Dictionary 8.5 Keyword Glossary 9.0 CONCLUSION 5 6 6 6 7 7 7 7 9 9 13 13 14 15 51 53 55 55 55 67 68 68 69 3 EXECUTIVE SUMMARY This paper serves as a report of the study performed on...
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...Table of Content Page No. Introduction 2 Job Analysis 2 Nature of Job Analysis 2 Components of Job Analysis 4 Uses of Job Analysis 4-5 Steps in Job Analysis 6-7 Methods of collecting information 7-11 o Interview o Questionnaire o Observation o Participant diary/logs o Quantitative Job Analysis Technique Conclusion 11 Introduction A method of performing job analyses and delivering or providing access to the results of the job analyses by creating a list of job requirements and working conditions for each discrete task of a job, creating a physical demands analysis comprising a list of physical requirements of each discrete task of a job, and combining the lists into a job analysis database for determining whether a worker can perform a job. Job Analysis Job analysis is a systematic approach to defining the job role, description, requirements, responsibilities, evaluation, etc. It helps in finding out required level of education, skills, knowledge, training, etc for the job position. It also depicts the job worth i.e. measurable effectiveness of the job and contribution of job to the organization. Thus, it effectively contributes to setting up the compensation package for the job position. Nature of Job Analysis: Organisations consist of positions that have to be staffed. Job Analysis is the procedure through which we determine the task, duties and responsibilities...
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...Student Name _________________________________ Date _____________ SEC450 Database Traffic Load iLab Objectives In this lab, the students will examine the following objectives. • Creating Database traffic using the traffic generator • Specifying link statistics to monitor traffic flow • Running discrete event simulation (DES) • Adjusting link speeds to handle Database traffic. Scenario A small company is using the topology shown below. The Public Server is actually an offsite Database Server that contains company records. Assume that the 200.100.0.0/16 network represents the Internet. The Dallas and Chicago Servers and Hosts need to access the database server. Only users in the Dallas and Chicago LANs should be able to access the database server. Topology The last page of the lab assignment document contains a full page Topology. Remove this page and use it for reference to the topology and the IP addresses. Initial OpNet Preparation The Week 5 iLab is entitled Database Traffic Load. The following steps show how to create the project required for the Week 5 iLab. • Log into the Citrix iLab Environment (lab.devry.edu). • Click on the OpNet 17 icon. • Click the Accept button to Open OpNet 17. • Click File/Open and navigate to the F:\op_models\SEC450\SEC450.project\SEC450 file and click Open. • In OpNet 17 with the SEC450 project open, click File/Save As. • Save the project in...
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...must be accounted for in the network design. The state of the art methods in combating the security threats are usually founded on cryptographic approaches. These techniques typically assume limited computational resources at adversaries, are usually derived from unproven assumptions, and most of the time do not offer a measurable security notion. Information theoretic security, on the other hand, eliminates the aforementioned limitations of the cryptographic techniques at the physical layer of communication systems. In this thesis, we concentrate on both the theoretical and the practical aspects of physical layer security. We first start by analyzing elemental interference networks, in particular, two-user channels with an adversary. The problem here is to characterize the fundamental limits on secure transmission rates. Towards this end, we devise coding schemes, forming inner bounds to the capacity region, and compare the achievable rates with outer bounds. This analysis is useful to explore microscopic gains that can be leveraged by the different coding schemes, and our analysis shows that the inherent interference...
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...CHI-SQUARE TEST - ANALYSIS OF CONTINGENCY TABLES David C. Howell University of Vermont The term ”chi-square” refers both to a statistical distribution and to a hypothesis testing procedure that produces a statistic that is approximately distributed as the chi-square distribution. In this entry the term is used in its second sense. PEARSON’S CHI-SQUARE The original chi-square test, often known as Pearson’s chi-square, dates from papers by Karl Pearson in the earlier 1900s. The test serves both as a ”goodnessof-fit” test, where the data are categorized along one dimension, and as a test for the more common ”contingency table”, in which categorization is across two or more dimensions. Voinov and Nikulin, this volume, discuss the controversy over the correct form for the goodness of fit test. This entry will focus on the lack of agreement about tests on contingency tables. In 2000 the Vermont State legislature approved a bill authorizing civil unions. The vote can be broken down by gender to produce the following table, with the expected frequencies given in parentheses. The expected frequencies are computed as Ri × Cj /N, where Ri and Cj represent row and column marginal totals and N is the grand total. Vote Women Men Total Yes 35 (28.83) 60 (66.17) 95 No 9 (15.17) 41 (34.83) 50 Total 44 101 145 The standard Pearson chi-square statistic is defined as χ2 = (Oij − Eij )2 (35 − 28.83)2 (41 − 34.83)2 = + ··· + = 5.50 Eij 28.83 34.83 where i and j index the rows and columns of...
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... Computer and Information Science University of Pennsylvania Computer and Information Science University of Pennsylvania kakade@linc.cis.upenn.edu mkearns@cis.upenn.edu Yishay Mansour Luis E. Ortiz Computer Science Tel Aviv University Computer and Information Science University of Pennsylvania mansour@post.tau.ac.il leortiz@linc.cis.upenn.edu ABSTRACT We introduce new online models for two important aspects of modern financial markets: Volume Weighted Average Price trading and limit order books. We provide an extensive study of competitive algorithms in these models and relate them to earlier online algorithms for stock trading. Categories and Subject Descriptors F.2 [Analysis of Algorithms and Problem Complexity]: Miscellaneous; J.4 [Social and Behavioral Sciences]: Economics General Terms Algorithms, Economics Keywords Online Trading, Competitive Analysis, VWAP 1. INTRODUCTION While popular images of Wall Street often depict swashbuckling traders boldly making large gambles on just their market intuitions, the vast majority of trading is actually considerably more technical and constrained. The constraints often derive from a complex combination of business, regulatory and institutional issues, and result in certain kinds of “standard” trading strategies or criteria that invite algorithmic analysis. One of the most common activities in modern financial markets is known as Volume Weighted Average Price, or Permission...
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...achievement. If the learning of mathematics is highly dependent on its language and the teaching of math vocabulary is crucial, it is doubly so for ELLs. English language learners in secondary schools should have many opportunities to communicate their mathematical ideas and questions. Talking and writing about their mathematical thinking helps ELLs build word knowledge and oral expression and clarify their thinking. Discussions with the teacher or peers are also useful monitoring tools for teachers. Through listening and recording student conversations and peer problem solving, teachers can monitor individual student progress. Mathematics is no longer viewed as isolated, individualistic, or competitive. Mathematics problems are ideally suited to cooperative group discussions because they have solutions that can be objectively demonstrated. Students can persuade one another by the logic of their arguments. Mathematics problems can often be solved by several different approaches, and students in groups can discuss the merits of different proposed solutions (Robertson, Davidson, & Dees, 1994). For this and several other reasons mentioned throughout this chapter, cooperative learning takes a central place in mathematics instruction. Teaching and Learning Meaningful Math The lesson template for ExC-ELL is the same as that described in previous...
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...FAO COMMODITY AND TRADE POLICY RESEARCH WORKING PAPER No.22 Threshold cointegration in the sugarethanol-oil price system in Brazil: evidence from nonlinear vector error correction models George Rapsomanikis and David Hallam1 Commodities and Trade Division Food and Agriculture Organization of the United Nations September 2006 1 The authors are Economist and Chief in the Trade Policy Service, Commodities and Trade Division. FAO Commodity and Trade Policy Research Working Papers are published by the Commodities and Trade Division of the Food and Agriculture Organization of the United Nations (FAO). They are working documents and do not reflect the opinion of FAO or its member governments. Also available at http://www.fao.org/es/ESC/ Additional copies of this working paper can be obtained from Olwen.Gotts@fao.org The designations employed and the presentation of material in this information product do not imply the expression of any opinion whatsoever on the part of the Food and Agriculture Organization of the United Nations concerning the legal or development status of any country, territory, city or area or of its authorities, or concerning the delimitation of its frontiers or boundaries. All rights reserved. Reproduction and dissemination of material in this information product for educational or other non-commercial purposes are authorized without any prior written permission from the copyright holders provided the source is fully acknowledged. Reproduction...
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...1 A DSP A-Z http://www.unex.ucla.edu Digital Signal Processing An “A” to “Z” R.W. Stewart Signal Processing Division Dept. of Electronic and Electrical Eng. University of Strathclyde Glasgow G1 1XW, UK Tel: +44 (0) 141 548 2396 Fax: +44 (0) 141 552 2487 E-mail: r.stewart@eee.strath.ac.uk M.W. Hoffman Department of Electrical Eng. 209N Walter Scott Eng. Center PO Box 880511 Lincoln, NE 68588 0511 USA Tel: +1 402 472 1979 Fax: +1 402 472 4732 Email:hoffman@unlinfo.unl.edu © BlueBox Multimedia, R.W. Stewart 1998 2 The DSPedia DSPedia An A-Z of Digital Signal Processing This text aims to present relevant, accurate and readable definitions of common and not so common terms, algorithms, techniques and information related to DSP technology and applications. It is hoped that the information presented will complement the formal teachings of the many excellent DSP textbooks available and bridge the gaps that often exist between advanced DSP texts and introductory DSP. While some of the entries are particularly detailed, most often in cases where the concept, application or term is particularly important in DSP, you will find that other terms are short, and perhaps even dismissive when it is considered that the term is not directly relevant to DSP or would not benefit from an extensive description. There are 4 key sections to the text: • • • • DSP terms A-Z Common Numbers associated with DSP Acronyms References page 1 page 427 page 435 page 443 the...
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...Chapter 1 Discrete Probability Distributions 1.1 Simulation of Discrete Probabilities Probability In this chapter, we shall first consider chance experiments with a finite number of possible outcomes ω1 , ω2 , . . . , ωn . For example, we roll a die and the possible outcomes are 1, 2, 3, 4, 5, 6 corresponding to the side that turns up. We toss a coin with possible outcomes H (heads) and T (tails). It is frequently useful to be able to refer to an outcome of an experiment. For example, we might want to write the mathematical expression which gives the sum of four rolls of a die. To do this, we could let Xi , i = 1, 2, 3, 4, represent the values of the outcomes of the four rolls, and then we could write the expression X 1 + X 2 + X 3 + X4 for the sum of the four rolls. The Xi ’s are called random variables. A random variable is simply an expression whose value is the outcome of a particular experiment. Just as in the case of other types of variables in mathematics, random variables can take on different values. Let X be the random variable which represents the roll of one die. We shall assign probabilities to the possible outcomes of this experiment. We do this by assigning to each outcome ωj a nonnegative number m(ωj ) in such a way that m(ω1 ) + m(ω2 ) + · · · + m(ω6 ) = 1 . The function m(ωj ) is called the distribution function of the random variable X. For the case of the roll of the die we would assign equal probabilities or probabilities 1/6 to each of the outcomes....
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