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UPenn - LAW - 12
* * Draft May 28, 2001 * * INTERNET COMMERCE: DOING BUSINESS IN A NETWORKED WORLD MARGARET JANE RADIN, JOHN ROTHCHILD AND GREGORY M. SILVERMAN 2000, 2001 by Margaret Jane Radin, John Rothchild and Gregory M. Silverman Chapter Ten Privacy Online In t
UPenn - LAW - 619
* * Draft May 28, 2001 * * INTERNET COMMERCE: DOING BUSINESS IN A NETWORKED WORLD MARGARET JANE RADIN, JOHN ROTHCHILD AND GREGORY M. SILVERMAN 2000, 2001 by Margaret Jane Radin, John Rothchild and Gregory M. Silverman Chapter Ten Privacy Online In t
UPenn - LAW - 619
ELECTRONIC COMMERCE: LAW, TECHNOLOGY, AND BUSINESS (LAW 619).University o f Pennsylvania L a w School R . Polk Wagner, Fall 2000COURSE OUTLINEIA n I n t r o d u ct i o n t o e C o m m e r ce : L a w , T e ch n o l o gy , a n d B u s i n e s sA
UPenn - LAW - 07
Page 1 847 F.2d 255, *; 1988 U.S. App. LEXIS 8456, *; 7 U.S.P.Q.2D (BNA) 1281; Copy. L. Rep. (CCH) P26,293[note: this is an edited version of the case]Vault Corporation, Plaintiff-Appellant, v. Quaid Software Limited, DefendantAppellee No. 87-3516
UPenn - LAW - 619
Page 1 847 F.2d 255, *; 1988 U.S. App. LEXIS 8456, *; 7 U.S.P.Q.2D (BNA) 1281; Copy. L. Rep. (CCH) P26,293[note: this is an edited version of the case]Vault Corporation, Plaintiff-Appellant, v. Quaid Software Limited, DefendantAppellee No. 87-3516
UPenn - LAW - 09
COMPUTERS AND SCIENCEAnticircumvention Rules: Threat to SciencePamela SamuelsonScientists who study encryption or computer security or otherwise reverse engineer technical measures, who make tools enabling them to do this work, and who report the
UPenn - LAW - 619
COMPUTERS AND SCIENCEAnticircumvention Rules: Threat to SciencePamela SamuelsonScientists who study encryption or computer security or otherwise reverse engineer technical measures, who make tools enabling them to do this work, and who report the
UPenn - LAW - 12
Giving the Web a Memory Cost Its Users Privacyhttp:/www.nytimes.com/2001/09/04/technology/.September 4, 2001 TRACKS IN CYBERSPACEGiving the Web a Memory Cost Its Users PrivacyBy JOHN SCHWARTZThe first of three articles. ne day in June 1994,
UPenn - LAW - 619
Giving the Web a Memory Cost Its Users Privacyhttp:/www.nytimes.com/2001/09/04/technology/.September 4, 2001 TRACKS IN CYBERSPACEGiving the Web a Memory Cost Its Users PrivacyBy JOHN SCHWARTZThe first of three articles. ne day in June 1994,
UPenn - LAW - 01
The Original WWW: Web Lessons from the Early Days of RadioWard Hanson Stanford University Graduate School of Business 7/15/96WWWow do you evaluate a technology which has completely captured the publics imagination? One which has spawned thousands
UPenn - LAW - 619
The Original WWW: Web Lessons from the Early Days of RadioWard Hanson Stanford University Graduate School of Business 7/15/96WWWow do you evaluate a technology which has completely captured the publics imagination? One which has spawned thousands
UPenn - LAW - 07
[note: this is an edited version] Beyond Preemption: The Law and Policy of Intellectual Property Licensing Mark A. Lemley *California Law Review January, 1999 87 Calif. L. Rev. 111 Copyright 1999 Mark A. Lemley and California Law Review, Inc.* I
UPenn - LAW - 619
[note: this is an edited version] Beyond Preemption: The Law and Policy of Intellectual Property Licensing Mark A. Lemley *California Law Review January, 1999 87 Calif. L. Rev. 111 Copyright 1999 Mark A. Lemley and California Law Review, Inc.* I
UPenn - LAW - 05
* * Draft August 5, 2001 * * INTERNET COMMERCE: DOING BUSINESS IN A NETWORKED WORLD MARGARET JANE RADIN, JOHN ROTHCHILD AND GREGORY M. SILVERMAN 2000, 2001 by Margaret Jane Radin, John Rothchild and Gregory M. Silverman Chapter Sixteen Jurisdiction
UPenn - LAW - 619
* * Draft August 5, 2001 * * INTERNET COMMERCE: DOING BUSINESS IN A NETWORKED WORLD MARGARET JANE RADIN, JOHN ROTHCHILD AND GREGORY M. SILVERMAN 2000, 2001 by Margaret Jane Radin, John Rothchild and Gregory M. Silverman Chapter Sixteen Jurisdiction
UPenn - LAW - 14
[edited version]ANTITRUST AND THE INTERNET STANDARDIZATION PROBLEM Mark A. Lemley28 Conn. L. Rev. 1041 (1996)[ . . .]III. Antitrust and StandardsAntitrust law protects competition and the competitive process, by preventing certain types of c
UPenn - LAW - 619
[edited version]ANTITRUST AND THE INTERNET STANDARDIZATION PROBLEM Mark A. Lemley28 Conn. L. Rev. 1041 (1996)[ . . .]III. Antitrust and StandardsAntitrust law protects competition and the competitive process, by preventing certain types of c
UPenn - LAW - 12
* * Draft May 28, 2001 * * INTERNET COMMERCE: DOING BUSINESS IN A NETWORKED WORLD MARGARET JANE RADIN, JOHN ROTHCHILD AND GREGORY M. SILVERMAN 2000, 2001 by Margaret Jane Radin, John Rothchild and Gregory M. Silverman Chapter Ten Privacy Online [*]
UPenn - LAW - 619
* * Draft May 28, 2001 * * INTERNET COMMERCE: DOING BUSINESS IN A NETWORKED WORLD MARGARET JANE RADIN, JOHN ROTHCHILD AND GREGORY M. SILVERMAN 2000, 2001 by Margaret Jane Radin, John Rothchild and Gregory M. Silverman Chapter Ten Privacy Online [*]
UPenn - LAW - 619
* * Draft August 5, 2001 * * INTERNET COMMERCE: DOING BUSINESS IN A NETWORKED WORLD MARGARET JANE RADIN, JOHN ROTHCHILD AND GREGORY M. SILVERMAN 2000, 2001 by Margaret Jane Radin, John Rothchild and Gregory M. Silverman Chapter Sixteen Jurisdiction
UPenn - LAW - 07
[note: this is an edited version ]BEYOND PREEMPTION: THE LAW AND POLICY OF INTELLECTUAL PROPERTY LICENSINGMARK A. LEMLEY CALIFORNIA LAW REVIEW January, 1999 87 Calif. L. Rev. 111 * Professor of Law, University of Texas School of Law; Visiting Prof
UPenn - LAW - 619
[note: this is an edited version ]BEYOND PREEMPTION: THE LAW AND POLICY OF INTELLECTUAL PROPERTY LICENSINGMARK A. LEMLEY CALIFORNIA LAW REVIEW January, 1999 87 Calif. L. Rev. 111 * Professor of Law, University of Texas School of Law; Visiting Prof
UPenn - EPI - 521
Statistical Methods in Epidemiologic Research: EP 521 Center for Biostatistics and Epidemiology Spring 2007 (Revised 10/05/2007)Course Outline 14 Weeks of lectures (+ exam week) Jan 9 April 26. (no classes during Spring Break (Week of March 5) Lec
UPenn - BSTA - 790
Causal inference in biomedical research Two notions of causation: Causes of an effect/outcome Effects of a causeCauses of an effect What were causes of World War II? What are causes of lung cancer? What was the cause of outbreak of food poiso
UPenn - BSTA - 652
BSTA 652 Categorical Data Analysis Syllabus 2007 Fall Semester Sept 5 Dec 5, 2007Classes: Monday & Wednesday, 9:00-10:30am Rm 505, Blockley HallInstructor: Tom Ten Have, Professor of Biostatistics Rm 607 Blockley ttenhave@upenn.edu Office Phone:
UPenn - BSTA - 790
Assignment 2 1. Consider a very large cohort study with no covariates measured, and consider the causal risk ratio . You have available the usual information on treatment received and observed outcomes. Compute/derive bounds for the causal rate ratio
UPenn - EPI - 521
EP 521, Spring 2007, Vol II, Part 618Dose response and trends an example to bridge contingency tables, ordinary linear regression, and logisticWe have looked at measures of association with exposures (or treatments) that are unordered catego
UPenn - EPI - 521
EP 521, Spring 2006 Vol II, Part 416. Conditional Logistic Regression (CLR) for Matched or Stratified Data 6.1 Overview Have considered unconditional regression, e.g., logistic Results in estimate for intercept ( ) which corresponds to the basel
UPenn - EPI - 521
EP 521, 2007, Vol I, part 412.3 Stratification and matching in design Matching/stratification: Definitions Matching - linking a few people by means of their characteristics (age and gender) for example. There can be 1 to 1 or 1 to 2 or , , 1 to m
UPenn - EPI - 521
EP 521, Spring 2007, Vol I, Part 21.4Confounding and InteractionThese issues will be a central part of our study of statistical methods. How do we identify and control for confounding? How do we identify and estimate effect modification (intera
UPenn - EPI - 521
Statistical Methods in Epidemiologic Research: EP 521 Center for Biostatistics and Epidemiology Spring 2004 (Revised 01/29/2004)Course Outline 14 Weeks (+ exam week) Jan 13 April 29. Russell Localio, Asst. Prof., Division of Biostatistics, CCEB Co
UPenn - EPI - 521
EP 521, Spring 2007 Vol II, Part 416. Conditional Logistic Regression (CLR) for Matched or Stratified Data 6.1 Overview Have considered unconditional regression, e.g., logistic Results in estimate for intercept ( ) which corresponds to the baseli
UPenn - EPI - 521
EP 521, Spring 2007, Vol I, Part 11Statistical Methods in Epidemiologic Research(FOR CLASS USE ONLY DO NOT CITE OR REPRODUCE)EP 521 Spring 2007 Course Notes Vol I (Part 1 of 5)A. Russell Localio*, and Jesse A Berlin (The Great Master)*Depa
UPenn - EPI - 521
EP 521, Spring 2007, Vol II, Part 315Applied Logistic Regression ModelingIn this section, we shall use our knowledge of (a) the methods for writing regression models and solving for estimates, and (b) the theory of logistic regression, to wor
UPenn - EPI - 521
EP 521, Spring 2007. Vol II, Part 11Statistical Methods in Epidemiologic Research EP 521 Spring 2007 Course Notes Vol II (Part 1 of 9) Multivariable RegressionA. Russell Localio*, and Jesse A Berlin (The Great Master)*Department of Biostatisti
UPenn - EPI - 521
EP 521 Spring 2007, Vol II, Part 9 (Under development) 10 Propensity Scores (balancing scores) 10.1 Potential outcomes, confounding, and conditional independence Problem: In randomized studies: when there are two groups, treated and control: We rely
UPenn - EPI - 521
EP 521, Spring 2007, Vol II, Part 719 Survival Analysis 9.1 Survival and hazard functions 9.2 Survival data and censoring 9.3 Estimating survival functions 9.3.1 Life Table method 9.3.2 Kaplan-Meier method 9.4 Competing risks 9.5 Noninformative c
UPenn - EPI - 521
EP 521, Spring 2007 Vol II, Part 517Other generalized linear regression models for epidemiology We have focused on logistic regression and linear regression. But these are special case of generalized linear models: Ordinary least squares reg
UPenn - EPI - 521
EP 521 Spring 2007 Vol I, part 312.2 Stratified AnalysesMethods and formulae How do we analyze data in the presence of confounding (or effect modification)? This section focuses on Mantel Haenszel methods for stratified analysis of binary outcome
UPenn - EPI - 521
EP 521, Spring 2007, Vol II, Part 819.9 Cox (proportional hazards) multivariable survival methods We have examined the basic and principal methods of handling survival data: life tables, KaplanMeier estimates, and the log-rank test. These methods
UPenn - EPI - 521
EP 521 Spring 2007, Vol II, Part 21Regression Methods for binary outcomes (logistic regression) 4.1 Background 4.2 Logistic regression properties of the model 4.3 Logistic regression Use of the model 4.4 Likelihoods and likelihood ratios 4.5 Li
UPenn - EPI - 521
EP 521 Spring, 2004, Vol I, Part 513.Sample Size Estimation A key to study design are sample size or power calculations. Required of ever grant proposal In this section: (1) we begin with theory behind power calculations and demonstrate how sim
UPenn - BSTA - 790
Noncompliance in randomized trials Frequently in randomized trials, subjects do not comply with their assigned treatment regimen Examples: Health Insurance Plan (HIP) trial of screening for breast cancer (BC) 2 arms: control: no screening screening
UPenn - BSTA - 652
Reference: Agresti, Chapter 16. Categorical data are measured using a limited number of valuesor categories. Categorical variables may have a natural ordering (ordinal) orthe order may be irrelevant (nominal). They are common in biomedical sc
UPenn - MATH - 103
1. 2.Give an example of a pair of (different) functions that have the same derivative. Find an anti-derivative of each of the following functions: a) f (x) = sin(2x) b) f (x) = x3 x2 c) f (x) = x3.The points A,B,C,D (in some order) are success
UPenn - MATH - 103
UNIVERSITY of PENNSYLVANIA MATHEMATICS DEPARTMENTMathematics 103 Midterm I Fall 2006Your Name:_ Penn ID#_ Your Professor (check one): Crotty Komendarczyk Tapp Your TA: __Instructions: You have 2 hours to complete this examination. Please write
UPenn - MATH - 103
UNIVERSITY of PENNSYLVANIA MATHEMATICS DEPARTMENTMathematics 103 Midterm II Fall 2006Your Name:_ Penn ID#_ Your Professor (check one): Crotty Komendarczyk Tapp Your TA: __Instructions: You have 2 hours to complete this examination. Please write
UPenn - C - 90
U S I N G T H E S A M E S Y S T E M F O R A N A L Y Z I N G AND S Y N T H E S I Z I N G S E N T E N C E SPhillipeRincel*andPaul Sabatier* Bull S.A., CE1)IAG, 68 Route de Versailles, 78430 Louveciennes, France. * CNRS, Groupe Intelligen
UPenn - C - 73
BENTE MAEGAARD-EBBE S P A N G - H A N S S E NSEGMENTATION OF FRENCH SENTENCES1. This paper describes a programme which, by means of a very limited number of criteria, analyses French sentences into principal clauses and subordinate clauses. W
UPenn - J - 99
Computational LinguisticsVolume 25, Number 3Beyond Grammar: An Experience-based Theory of Language Rens Bod(University of Amsterdam) Stanford: CSLI Publications (Lecture notes number 88), 1998, xiii+168 pp; distributed by Cambridge University Pr
UPenn - P - 93
INTEGRATING WITHWORD BOUNDARY IDENTIFICATION SENTENCE UNDERSTANDINGKok Wee GanDepartment of Information Systems eJ Computer Science National University of SingaporeK e n t R i d g e C r e s c e n t , S i n g a p o r e 0511 Internet: gankw@iscs.
UPenn - J - 93
Text-Based Intelligent Systems: Current Research and Practice in Information Extraction and RetrievalPaul S. Jacobs (editor)(Research and Development Center, General Electric Company) Hillsdale, NJ: Lawrence Erlbaum Associates, 1992, viii + 281 pp.
UPenn - C - 90
RECOGNIZINGADVICE, WARNINGS,PROMISESAND THREATSKevin Donaghy School of Computer Science and Information Technology Rochester Institute of Technology, Rochester, New York 14623 hkd@cs.rit.eduIt is argued here that utterances in the imperative m
UPenn - P - 83
Crossed S e r i a l Dependencies: i low-power parseable extension to GPSG Henry Thompson Department of Artificial Intelligence and Program in Cognitive Science U n i v e r s i t y of Edinburgh Hope Park Square, Meadow Lane Edinburgh EH8 9NW SCOTLAND
UPenn - P - 96
Using textual clues to improve metaphor processingSt6phane FerrariLIMSI-CNRS P O B o x 133 F-91403 Orsay cSdex, FRANCE ferrari@limsi.frAbstract In this paper, we propose a textual clue approach to help metaphor detection, in order to improve the
UPenn - C - 88
Vi~tcenza I'~I~}NATARO PaL f. Lingaisfik u.Literattn,viss. Universitht Bielefeld PostfN~h 8640 D-4g0b~ Bielefeld 1 .4~<.x;~>~: The aim of the presenteA rc~:~ffeh is the dt~velop ~:~-~i: ~f a lh~gaisdc mo.del of the function01 cont~pts topic and ~i;,