How Forensic Science Lost Its Way and How It Might Yet Find It Michael J
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Course Catalog 2014-2015
Phoenix Union High School District COURSE CATALOG 2014-2015 Mathematics S cience Special Education Business E nglish P hysical Education / Health ELL Reading Career and Technical Education Performing Arts Art W orld Languages Social Studies JROTC Family and Consumer Science Magnets LEADERSHIP TEAM Dr. Kent Paredes Scribner, Superintendent Dr. Althe Allen, Assistant Superintendent for Instruction and Accountability Mr. Jose Arenas, Assistant Superintendent for Human Resources Ms. Lorrie Drobny, Assistant Superintendent for Business and Finance Ms. Nora Gutierrez, Assistant Superintendent for Operations Mr. Juvenal Lopez, Director of Certified Staff Ms. Carol Nau, Administrative Assistant to the Governing Board Mr. Craig Pletenik, Community Relations Manager Mr. Corey Woods, Director of College and Career Articulation GOVERNING BOARD Ms. Linda Abril Ms. Lela Alston Mr. Ian Danley Mr. Ricardo Gallego Ms. Amy Kobeta Ms. Laura Pastor Mr. Randy Schiller Phoenix Union High School District COURSE CATALOG 2014-2015 4502 North Central Avenue Phoenix, Arizona 85012 (602) 764-1100 www.PhoenixUnion.org Revised February 2014 Table of Contents Table TABLE OF CONTENTS General Information and Special Program Requirements ................................................................. II Districtwide Course Offerings Career and Technical Education (CTE)....................................................................................... C2 Agriscience .......................................................................................................................... -
Research Participants' Rights to Data Protection in the Era of Open Science
DePaul Law Review Volume 69 Issue 2 Winter 2019 Article 16 Research Participants’ Rights To Data Protection In The Era Of Open Science Tara Sklar Mabel Crescioni Follow this and additional works at: https://via.library.depaul.edu/law-review Part of the Law Commons Recommended Citation Tara Sklar & Mabel Crescioni, Research Participants’ Rights To Data Protection In The Era Of Open Science, 69 DePaul L. Rev. (2020) Available at: https://via.library.depaul.edu/law-review/vol69/iss2/16 This Article is brought to you for free and open access by the College of Law at Via Sapientiae. It has been accepted for inclusion in DePaul Law Review by an authorized editor of Via Sapientiae. For more information, please contact [email protected]. \\jciprod01\productn\D\DPL\69-2\DPL214.txt unknown Seq: 1 21-APR-20 12:15 RESEARCH PARTICIPANTS’ RIGHTS TO DATA PROTECTION IN THE ERA OF OPEN SCIENCE Tara Sklar and Mabel Crescioni* CONTENTS INTRODUCTION ................................................. 700 R I. REAL-WORLD EVIDENCE AND WEARABLES IN CLINICAL TRIALS ....................................... 703 R II. DATA PROTECTION RIGHTS ............................. 708 R A. General Data Protection Regulation ................. 709 R B. California Consumer Privacy Act ................... 710 R C. GDPR and CCPA Influence on State Data Privacy Laws ................................................ 712 R III. RESEARCH EXEMPTION AND RELATED SAFEGUARDS ... 714 R IV. RESEARCH PARTICIPANTS’ DATA AND OPEN SCIENCE . 716 R CONCLUSION ................................................... 718 R Clinical trials are increasingly using sensors embedded in wearable de- vices due to their capabilities to generate real-world data. These devices are able to continuously monitor, record, and store physiological met- rics in response to a given therapy, which is contributing to a redesign of clinical trials around the world. -
Overview of Reliability Engineering
Overview of reliability engineering Eric Marsden <[email protected]> Context ▷ I have a fleet of airline engines and want to anticipate when they mayfail ▷ I am purchasing pumps for my refinery and want to understand the MTBF, lambda etc. provided by the manufacturers ▷ I want to compare different system designs to determine the impact of architecture on availability 2 / 32 Reliability engineering ▷ Reliability engineering is the discipline of ensuring that a system will function as required over a specified time period when operated and maintained in a specified manner. ▷ Reliability engineers address 3 basic questions: • When does something fail? • Why does it fail? • How can the likelihood of failure be reduced? 3 / 32 The termination of the ability of an item to perform a required function. [IEV Failure Failure 191-04-01] ▷ A failure is always related to a required function. The function is often specified together with a performance requirement (eg. “must handleup to 3 tonnes per minute”, “must respond within 0.1 seconds”). ▷ A failure occurs when the function cannot be performed or has a performance that falls outside the performance requirement. 4 / 32 The state of an item characterized by inability to perform a required function Fault Fault [IEV 191-05-01] ▷ While a failure is an event that occurs at a specific point in time, a fault is a state that will last for a shorter or longer period. ▷ When a failure occurs, the item enters the failed state. A failure may occur: • while running • while in standby • due to demand 5 / 32 Discrepancy between a computed, observed, or measured value or condition and Error Error the true, specified, or theoretically correct value or condition. -
Lochner</I> in Cyberspace: the New Economic Orthodoxy Of
Georgetown University Law Center Scholarship @ GEORGETOWN LAW 1998 Lochner in Cyberspace: The New Economic Orthodoxy of "Rights Management" Julie E. Cohen Georgetown University Law Center, [email protected] This paper can be downloaded free of charge from: https://scholarship.law.georgetown.edu/facpub/811 97 Mich. L. Rev. 462-563 (1998) This open-access article is brought to you by the Georgetown Law Library. Posted with permission of the author. Follow this and additional works at: https://scholarship.law.georgetown.edu/facpub Part of the Intellectual Property Law Commons, Internet Law Commons, and the Law and Economics Commons LOCHNER IN CYBERSPACE: THE NEW ECONOMIC ORTHODOXY OF "RIGHTS MANAGEMENT" JULIE E. COHEN * Originally published 97 Mich. L. Rev. 462 (1998). TABLE OF CONTENTS I. THE CONVERGENCE OF ECONOMIC IMPERATIVES AND NATURAL RIGHTS..........6 II. THE NEW CONCEPTUALISM.....................................................18 A. Constructing Consent ......................................................18 B. Manufacturing Scarcity.....................................................32 1. Transaction Costs and Common Resources................................33 2. Incentives and Redistribution..........................................40 III. ON MODELING INFORMATION MARKETS........................................50 A. Bargaining Power and Choice in Information Markets.............................52 1. Contested Exchange and the Power to Switch.............................52 2. Collective Action, "Rent-Seeking," and Public Choice.......................67 -
Understanding Functional Safety FIT Base Failure Rate Estimates Per IEC 62380 and SN 29500
www.ti.com Technical White Paper Understanding Functional Safety FIT Base Failure Rate Estimates per IEC 62380 and SN 29500 Bharat Rajaram, Senior Member, Technical Staff, and Director, Functional Safety, C2000™ Microcontrollers, Texas Instruments ABSTRACT Functional safety standards like International Electrotechnical Commission (IEC) 615081 and International Organization for Standardization (ISO) 262622 require that semiconductor device manufacturers address both systematic and random hardware failures. Systematic failures are managed and mitigated by following rigorous development processes. Random hardware failures must adhere to specified quantitative metrics to meet hardware safety integrity levels (SILs) or automotive SILs (ASILs). Consequently, systematic failures are excluded from the calculation of random hardware failure metrics. Table of Contents 1 Introduction.............................................................................................................................................................................2 2 Types of Faults and Quantitative Random Hardware Failure Metrics .............................................................................. 2 3 Random Failures Over a Product Lifetime and Estimation of BFR ...................................................................................3 4 BFR Estimation Techniques ................................................................................................................................................. 4 5 Siemens SN 29500 FIT model -
Probability Analysis in Determining the Behaviour of Variable Amplitude Strain Signal Based on Extraction Segments
2141 Probability Analysis in Determining the Behaviour of Variable Amplitude Strain Signal Based on Extraction Segments Abstract M. F. M. Yunoh a This paper focuses on analysis in determining the behaviour of vari- S. Abdullah b, * able amplitude strain signals based on extraction of segments. The M. H. M. Saad c constant Amplitude loading (CAL), that was used in the laboratory d Z. M. Nopiah tests, was designed according to the variable amplitude loading e (VAL) from Society of Automotive Engineers (SAE). The SAE strain M. Z. Nuawi signal was then edited to obtain those segments that cause fatigue a damage to components. The segments were then sorted according to Department of Mechanical and Materials their amplitude and were used as a reference in the design of the Engineering, Faculty of Engineering & CAL loading for the laboratory tests. The strain signals that were Built Enviroment, Universiti Kebangsaan obtained from the laboratory tests were then analysed using fatigue Malaysia, 43600 UKM Bangi, Selangor, life prediction approach and statistics, i.e. Weibull distribution anal- Malaysia. [email protected] b ysis. Based on the plots of the Probability Density Function (PDF), [email protected] c Cumulative Distribution Function (CDF) and the probability of fail- [email protected]; d ure in the Weibull distribution analysis, it was shown that more than [email protected]; e 70% failure occurred when the number of cycles approached 1.0 x [email protected] 1011. Therefore, the Weibull distribution analysis can be used as an alternative to predict the failure probability. * Corresponding author: S. -
Computer Forensic Text Analysis with Open Source Software
Master Thesis Computer Science Thesis no: MCS-2003:17 June 2003 Computer Forensic Text Analysis with Open Source Software Christian Johansson Department of Software Engineering and Computer Science Blekinge Institute of Technology Box 520 SE – 372 25 Ronneby Sweden This thesis is submitted to the Department of Software Engineering and Computer Science at Blekinge Institute of Technology in partial fulfillment of the requirements for the degree of Master of Science in Computer Science. The thesis is equivalent to 20 weeks of full time studies. Contact Information: Author: Christian Johansson E-mail: [email protected] University advisor: Bengt Carlsson Department of Software Engineering and Computer Science Department of Internet : www.bth.se/ipd Software Engineering and Computer Science Phone : +46 457 38 50 00 Blekinge Institute of Technology Fax : + 46 457 271 25 Box 520 SE – 372 25 Ronneby ii Sweden ABSTRACT A computer forensic investigation is not only dependent on correct and flawless analysis of the given data, but also of this analysis being conducted within a reasonable amount of time and effort. Given the exponential growth in size of hard disk drives coupled with the fact that many phases in a computer forensic investigation are still performed manually, the compromise between accuracy and completeness is becoming more and more of a problem. This paper concentrates on the text analysis process within computer forensics, focusing on the use of open source software. It discusses and examines the different techniques used in the possible future streamlining of said process. Keywords: forensics, text analysis, natural language Acknowledgments The author would like to thank the following persons and institutions for the help and support they have given prior and during the writing of this thesis. -
Individual Failure Rate Modelling and Exploratory Failure Data Analysis for Power System Components
INDIVIDUAL FAILURE RATE MODELLING AND EXPLORATORY FAILURE DATA ANALYSIS FOR POWER SYSTEM COMPONENTS REPORT 2018:549 RISK- OCH TILLFÖRLITLIGHETSANALYS Individual Failure Rate Modelling and Exploratory Failure Data Analysis for Power System Components JAN HENNING JÜRGENSEN ISBN 978-91-7673-549-7 | © Energiforsk December 2018 Energiforsk AB | Phone: 08-677 25 30 | E-mail: [email protected] | www.energiforsk.se INDIVIDUAL FAILURE RATE MODELLING AND EXPLORATORY FAILURE DATA ANALYSIS FOR POWER SYSTEM COMPONENTS Foreword Detta projekt är en fortsättning på ett doktorandprojekt från tidigare programperiod. Etappen Riskanalys III hanterade projektet från licentiat till doktorsavhandling genom att stötta en slutrapportering. Projektet studerade om felfrekvensnoggrannheten på en enskild komponentnivå kan öka trots att det tillgängliga historiska feldatat är begränsat. Resultatet var att effekterna av riskfaktorer på felfrekvens med regressionsmodeller kvantifierades, samt en ökad förståelse av riskfaktorer och högre noggrannhet av felfrekvensen. Statistisk data-underbyggda metoder används fortfarande sällan i kraftsystemen samtidigt som metoder behövs för att förbättra felfrekvensnoggrannheten trots begränsade tillgängliga data. Metoden beräknar individuella felfrekvenser. Jan Henning Jürgensen från Kungliga Tekniska Högskolan, har varit projektledare för projektet. Han har arbetat under handledning av docent Patrik Hilber och professor Lars Nordström, bägge på KTH. Stort tack till följande programstyrelse för all hjälp och vägledning: • Jenny -
Bodies of Evidence Reconstructing History Through Skeletal Analysis 1St Edition Ebook, Epub
BODIES OF EVIDENCE RECONSTRUCTING HISTORY THROUGH SKELETAL ANALYSIS 1ST EDITION PDF, EPUB, EBOOK Grauer | 9780471042792 | | | | | Bodies of Evidence Reconstructing History through Skeletal Analysis 1st edition PDF Book Forensic Outreach. Forensic anthropology is the application of the anatomical science of anthropology and its various subfields, including forensic archaeology and forensic taphonomy , [1] in a legal setting. In addition to revealing the age, sex, size, stature, health, and ethnic population of the decedent, an examination of the skeleton may reveal evidence concerning pathology and any antemortem before death , perimortem at the time of death , or postmortem after death trauma. September Investigations often begin with a ground search team using cadaver dogs or a low-flying plane to locate a missing body or skeleton. It is also recommended that individuals looking to pursue a forensic anthropology profession get experience in dissection usually through a gross anatomy class as well as useful internships with investigative agencies or practicing anthropologists. Permissions Request permission to reuse content from this site. Assessment of the Reliability of Facial Reconstruction. In , the second of the soldiers' remains discovered at Avion , France were identified through a combination of 3-D printing software, reconstructive sculpture and use of isotopic analysis of bone. In cases like these, forensic archaeologists must practice caution and recognize the implications behind their work and the information they uncover. Practical Considerations. Taylor of Austin, Texas during the s. Historical Archaeology. American Anthropologist. Retrieved 10 September Hindustan Times. Wikimedia Commons has media related to Forensic facial reconstruction. The capability to uncover information about victims of war crimes or homicide may present a conflict in cases that involve competing interests. -
The Effects of Autocorrelation in the Estimation of Process Capability Indices." (1998)
Louisiana State University LSU Digital Commons LSU Historical Dissertations and Theses Graduate School 1998 The ffecE ts of Autocorrelation in the Estimation of Process Capability Indices. Lawrence Lee Magee Louisiana State University and Agricultural & Mechanical College Follow this and additional works at: https://digitalcommons.lsu.edu/gradschool_disstheses Recommended Citation Magee, Lawrence Lee, "The Effects of Autocorrelation in the Estimation of Process Capability Indices." (1998). LSU Historical Dissertations and Theses. 6847. https://digitalcommons.lsu.edu/gradschool_disstheses/6847 This Dissertation is brought to you for free and open access by the Graduate School at LSU Digital Commons. It has been accepted for inclusion in LSU Historical Dissertations and Theses by an authorized administrator of LSU Digital Commons. For more information, please contact [email protected]. INFORMATION TO USERS This manuscript has been reproduced from the microfilm master. U M I films the text directly from die original or copy submitted. Thus, some thesis and dissertation copies are in typewriter face, while others may be from any type o f computer printer. The quality o f this reproduction is dependent upon the quality o f the copy submitted. Broken or indistinct print, colored or poor quality illustrations and photographs, print bleedthrough, substandard margins, and improper alignment can adversely affect reproduction. hi the unlikely event that the author did not send UMI a complete manuscript and there are missing pages, these will be noted. Also, if unauthorized copyright material had to be removed, a note w ill indicate the deletion. Oversize materials (e.g., maps, drawings, charts) are reproduced by sectioning the original, beginning at the upper left-hand corner and continuing from left to right in equal sections with small overlaps. -
Pacific Northwest Division IAI Winter 2015
Pacific Northwest Division IAI Winter 2015 Pacific Northwest Division IAI From the desk of PNWD-IAI’s President Sherrie Wraspir 2014-2015 Greetings to you, Registration for the 51st Annual PNWD-IAI Annual Training Conference is under way! This year’s conference will be held at the Sheraton Portland Airport Hotel in Portland, Oregon, May 19-22nd. The newly renovated hotel is just a short, free shuttle ride from the airport and parking is free as well! This year’s conference is packed full of great lectures and workshops in a wide range of forensic disciplines to offer a well-rounded educational opportunity. Look for a complete listing in the conference flyer included in this newsletter or on our website. The workshops will be filled on a first-come, first-serve basis, so register early to reserve your spot! Both member registration, as well as vendor registration can be completed online through PayPal at www.pnwdiai.org. You can also mail in your registration, along with payment, using one of the payment methods located at the bottom of the registration form. Certification testing will be available this year on Thursday, May 21st. Check the appropriate box on the registra- tion form and return it by March 31st so we can arrange a proctor. If you are unsure if your application will be approved before the conference, please check with your certification committee. We made a few changes this year that I hope you find exciting. The traditional Tuesday and Wednesday night festivities have been combined into one special night to allow a free night to explore and network on your own. -
Chapter 2 Failure Models Part 1: Introduction
Chapter 2 Failure Models Part 1: Introduction Marvin Rausand Department of Production and Quality Engineering Norwegian University of Science and Technology [email protected] Marvin Rausand, March 14, 2006 System Reliability Theory (2nd ed), Wiley, 2004 – 1 / 31 Introduction Rel. measures Life distributions State variable Time to failure Distr. function Probability density Distribution of T Reliability funct. Failure rate Introduction Bathtub curve Some formulas MTTF Example 2.1 Median Mode MRL Example 2.2 Discrete distributions Life distributions Marvin Rausand, March 14, 2006 System Reliability Theory (2nd ed), Wiley, 2004 – 2 / 31 Reliability measures Introduction In this chapter we introduce the following measures: Rel. measures Life distributions State variable Time to failure ■ Distr. function The reliability (survivor) function R(t) Probability density ■ The failure rate function z(t) Distribution of T ■ Reliability funct. The mean time to failure (MTTF) Failure rate ■ The mean residual life (MRL) Bathtub curve Some formulas MTTF Example 2.1 of a single item that is not repaired when it fails. Median Mode MRL Example 2.2 Discrete distributions Life distributions Marvin Rausand, March 14, 2006 System Reliability Theory (2nd ed), Wiley, 2004 – 3 / 31 Life distributions Introduction The following life distributions are discussed: Rel. measures Life distributions State variable ■ The exponential distribution Time to failure ■ Distr. function The gamma distribution Probability density ■ The Weibull distribution Distribution of