Guide 2 How to Plan and Budget for Your Healthcare Technology
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Topic 5 How Does the Regulatory Framework Affect Incentives for Research and Development?
Topic 5 How Does the Regulatory Framework Affect Incentives for Research and Development? Prepared for World Health Organization’s Commission on Intellectual Property Rights, Innovation, and Public Health (CIPIH) Response Prepared by USP CIPIH Advisory Panel International Health Expert Committee of USP’s Council of Experts November 16, 2005 Authors This paper is the work of a USP Advisory Panel whose members’ names, together with those of contributing USP staff, are included in Attachment 1. The Advisory Panel worked in accordance with USP’s rules and procedures at the direction of the International Health Expert Committee of USP’s Council of Experts, whose members’ names are included in Attachment 2. USP CIPIH Advisory Panel Response to Topic 5 November 2005 Page 2 Table of Contents Executive Summary...............................................................................................................5 Introduction............................................................................................................................7 Coincident Papers.........................................................................................................8 General Themes ............................................................................................................8 Developing Countries: The Challenges .................................................................................8 Disease Burden.............................................................................................................8 Table -
Towards a Fully Automated Extraction and Interpretation of Tabular Data Using Machine Learning
UPTEC F 19050 Examensarbete 30 hp August 2019 Towards a fully automated extraction and interpretation of tabular data using machine learning Per Hedbrant Per Hedbrant Master Thesis in Engineering Physics Department of Engineering Sciences Uppsala University Sweden Abstract Towards a fully automated extraction and interpretation of tabular data using machine learning Per Hedbrant Teknisk- naturvetenskaplig fakultet UTH-enheten Motivation A challenge for researchers at CBCS is the ability to efficiently manage the Besöksadress: different data formats that frequently are changed. Significant amount of time is Ångströmlaboratoriet Lägerhyddsvägen 1 spent on manual pre-processing, converting from one format to another. There are Hus 4, Plan 0 currently no solutions that uses pattern recognition to locate and automatically recognise data structures in a spreadsheet. Postadress: Box 536 751 21 Uppsala Problem Definition The desired solution is to build a self-learning Software as-a-Service (SaaS) for Telefon: automated recognition and loading of data stored in arbitrary formats. The aim of 018 – 471 30 03 this study is three-folded: A) Investigate if unsupervised machine learning Telefax: methods can be used to label different types of cells in spreadsheets. B) 018 – 471 30 00 Investigate if a hypothesis-generating algorithm can be used to label different types of cells in spreadsheets. C) Advise on choices of architecture and Hemsida: technologies for the SaaS solution. http://www.teknat.uu.se/student Method A pre-processing framework is built that can read and pre-process any type of spreadsheet into a feature matrix. Different datasets are read and clustered. An investigation on the usefulness of reducing the dimensionality is also done. -
Kwame Nkrumah University of Science and Technology, Kumasi
KWAME NKRUMAH UNIVERSITY OF SCIENCE AND TECHNOLOGY, KUMASI, GHANA Assessing the Social Impacts of Illegal Gold Mining Activities at Dunkwa-On-Offin by Judith Selassie Garr (B.A, Social Science) A Thesis submitted to the Department of Building Technology, College of Art and Built Environment in partial fulfilment of the requirement for a degree of MASTER OF SCIENCE NOVEMBER, 2018 DECLARATION I hereby declare that this work is the result of my own original research and this thesis has neither in whole nor in part been prescribed by another degree elsewhere. References to other people’s work have been duly cited. STUDENT: JUDITH S. GARR (PG1150417) Signature: ........................................................... Date: .................................................................. Certified by SUPERVISOR: PROF. EDWARD BADU Signature: ........................................................... Date: ................................................................... Certified by THE HEAD OF DEPARTMENT: PROF. B. K. BAIDEN Signature: ........................................................... Date: ................................................................... i ABSTRACT Mining activities are undertaken in many parts of the world where mineral deposits are found. In developing nations such as Ghana, the activity is done both legally and illegally, often with very little or no supervision, hence much damage is done to the water bodies where the activities are carried out. This study sought to assess the social impacts of illegal gold mining activities at Dunkwa-On-Offin, the capital town of Upper Denkyira East Municipality in the Central Region of Ghana. The main objectives of the research are to identify factors that trigger illegal mining; to identify social effects of illegal gold mining activities on inhabitants of Dunkwa-on-Offin; and to suggest effective ways in curbing illegal mining activities. Based on the approach to data collection, this study adopts both the quantitative and qualitative approach. -
Assessing the Environmental Adaptation of Wildlife And
Assessing the Environmental Adaptation of Wildlife and Production Animals Production and Wildlife of Adaptation Assessing Environmental the Assessing the Environmental Adaptation of Wildlife and • Edward Narayan Edward • Production Animals Applications of Physiological Indices and Welfare Assessment Tools Edited by Edward Narayan Printed Edition of the Special Issue Published in Animals www.mdpi.com/journal/animals Assessing the Environmental Adaptation of Wildlife and Production Animals: Applications of Physiological Indices and Welfare Assessment Tools Assessing the Environmental Adaptation of Wildlife and Production Animals: Applications of Physiological Indices and Welfare Assessment Tools Editor Edward Narayan MDPI • Basel • Beijing • Wuhan • Barcelona • Belgrade • Manchester • Tokyo • Cluj • Tianjin Editor Edward Narayan The University of Queensland Australia Editorial Office MDPI St. Alban-Anlage 66 4052 Basel, Switzerland This is a reprint of articles from the Special Issue published online in the open access journal Animals (ISSN 2076-2615) (available at: https://www.mdpi.com/journal/animals/special issues/ environmental adaptation). For citation purposes, cite each article independently as indicated on the article page online and as indicated below: LastName, A.A.; LastName, B.B.; LastName, C.C. Article Title. Journal Name Year, Volume Number, Page Range. ISBN 978-3-0365-0142-0 (Hbk) ISBN 978-3-0365-0143-7 (PDF) © 2021 by the authors. Articles in this book are Open Access and distributed under the Creative Commons Attribution (CC BY) license, which allows users to download, copy and build upon published articles, as long as the author and publisher areproperly credited, which ensures maximum dissemination and a wider impact of our publications. The book as a whole is distributed by MDPI under the terms and conditions of the Creative Commons license CC BY-NC-ND. -
General Linear Models - Part II
Introduction to General and Generalized Linear Models General Linear Models - part II Henrik Madsen Poul Thyregod Informatics and Mathematical Modelling Technical University of Denmark DK-2800 Kgs. Lyngby October 2010 Henrik Madsen Poul Thyregod (IMM-DTU) Chapman & Hall October 2010 1 / 32 Today Test for model reduction Type I/III SSQ Collinearity Inference on individual parameters Confidence intervals Prediction intervals Residual analysis Henrik Madsen Poul Thyregod (IMM-DTU) Chapman & Hall October 2010 2 / 32 Tests for model reduction Assume that a rather comprehensive model (a sufficient model) H1 has been formulated. Initial investigation has demonstrated that at least some of the terms in the model are needed to explain the variation in the response. The next step is to investigate whether the model may be reduced to a simpler model (corresponding to a smaller subspace),. That is we need to test whether all the terms are necessary. Henrik Madsen Poul Thyregod (IMM-DTU) Chapman & Hall October 2010 3 / 32 Successive testing, type I partition Sometimes the practical problem to be solved by itself suggests a chain of hypothesis, one being a sub-hypothesis of the other. In other cases, the statistician will establish the chain using the general rule that more complicated terms (e.g. interactions) should be removed before simpler terms. In the case of a classical GLM, such a chain of hypotheses n corresponds to a sequence of linear parameter-spaces, Ωi ⊂ R , one being a subspace of the other. n R ⊆ ΩM ⊂ ::: ⊂ Ω2 ⊂ Ω1 ⊂ R ; where Hi : µ 2 -
Security Systems Services World Report
Security Systems Services World Report established in 1974, and a brand since 1981. www.datagroup.org Security Systems Services World Report Database Ref: 56162 This database is updated monthly. Security Systems Services World Report SECURITY SYSTEMS SERVICES WORLD REPORT The Security systems services Report has the following information. The base report has 59 chapters, plus the Excel spreadsheets & Access databases specified. This research provides World Data on Security systems services. The report is available in several Editions and Parts and the contents and cost of each part is shown below. The Client can choose the Edition required; and subsequently any Parts that are required from the After-Sales Service. Contents Description ....................................................................................................................................... 5 REPORT EDITIONS ........................................................................................................................... 6 World Report ....................................................................................................................................... 6 Regional Report ................................................................................................................................... 6 Country Report .................................................................................................................................... 6 Town & Country Report ...................................................................................................................... -
A SAS* Macro System David S. Frankel, Exxon Company, USA Abstract the Statistical-Model Toolbo
The Statistical-Model Toolbox: A SAS* Macro System David S. Frankel, Exxon Company, U.S.A. Abstract However, if the objective is to estimate the expected value of • nonlinear function of the The statistical-model toolbox (SMT) is a SAS predicted variable and if the scatter in the macro system written in the Production Depart sample is Significant, the conventional approach ment of Exxon Company, U.S.A_, that provides two can lead to significant errors. In this case; powerful capabilities: a systematic way to model it is preferable to model the popUlation in scattered data and to model calculated results terms of conditional probability-density 'that are based on the scattered data; and, a way functions (PDF's) that are determined by central to create and manipulate synthetic probabil ity tendency ("1ocationll) and by variance ("scale"). distributions in the absence of measured data. PDF's are also referred to as distributions or The Production Department uses these capabi1 i statistical models. ties to address problems in petroleum reservoir description, where rock properties are Figure 2 depicts this statistical-model stochastic by nature. However, the tools are approac~. In a procedure analogous to complete 1y general and can be aPfl i ed to any regressl0n t the location and scale parameters continuous, numeric, random variab es. The most are estimated for normal (Gaussian) PDF's. The frequently used tool calculates expected values expected value of any function of the variable of arbitrary functions of one or two random is calculated by integrating the product of the variables. Other tools display distributions, function and the PDF over the entire range of calculate statistics, and generate random variable. -
Types of Sums of Squares
Types of Sums of Squares With flexibility (especially unbalanced designs) and expansion in mind, this ANOVA package was implemented with general linear model (GLM) approach. There are different ways to quantify factors (categorical variables) by assigning the values of a nominal or ordinal variable, but we adopt binary coding for each factor level and all applicable interactions into dummy (indicator) variables. An ANOVA can be written as a general linear model: Y = b0 + b1X1 + b2X2 + ... + bkXk+e With matrix notation, it is reduced to a simple form Y = Xb + e The design matrix for a 2-way ANOVA with factorial design 2X3 looks like Data Design Matrix A B A*B A B A1 A2 B1 B2 B3 A1B1 A1B2 A1B3 A2B1 A2B2 A2B3 1 1 1 1 0 1 0 0 1 0 0 0 0 0 1 2 1 1 0 0 1 0 0 1 0 0 0 0 1 3 1 1 0 0 0 1 0 0 1 0 0 0 2 1 1 0 1 1 0 0 0 0 0 1 0 0 2 2 1 0 1 0 1 0 0 0 0 0 1 0 2 3 1 0 1 0 0 1 0 0 0 0 0 1 After removing an effect of a factor or an interaction from the above full model (deleting some columns from matrix X), we obtain the increased error due to the removal as a measure of the effect. And the ratio of this measure relative to some overall error gives an F value, revealing the significance of the effect. -
CARE Guidelines for Case Reports: Explanation and Elaboration Document David S
Journal of Clinical Epidemiology 89 (2017) 218e235 CARE guidelines for case reports: explanation and elaboration document David S. Rileya,*, Melissa S. Barberb, Gunver S. Kienlec, Jeffrey K. Aronsond, Tido von Schoen-Angerere, Peter Tugwellf, Helmut Kieneg, Mark Helfandh, Douglas G. Altmani, Harold Soxj, Paul G. Werthmanng, David Moherk, Richard A. Risonl, Larissa Shamseerk, Christian A. Kochm, Gordon H. Sunn, Patrick Hanawayo, Nancy L. Sudakp, Marietta Kaszkin-Bettagq, James E. Carpenterr, Joel J. Gagniers,t aIntegrative Medicine Institute, 2437A NW Overton Street, Portland, OR 97210, USA; Helfgott Research Institute, 2220 SW 1st Ave, Portland, OR 97201, USA bIntegrative Medicine Institute, 2437A NW Overton Street, Portland, OR 97210, USA cSenior Research Scientist, University of Freiburg, Fahnenbergplatz, 79085 Freiburg im Breisgau, Germany; Senior Research Scientist, Institute for Applied Epistemology and Medical Methodology at the University of Witten-Herdecke, Zechenweg 6, 79111 Freiburg im Breisgau, Germany dUniversity of Oxford, Nuffield Department of Primary Care Health Sciences, Radcliffe Observatory Quarter, Woodstock Road, Oxford, OX2 6GG, UK eDepartment of Pediatrics, Centre medical de La Chapelle, Chemin de Compostelle 7, 1212 Grand-Lancy, Geneve, Switzerland; ACIM Institute, Filderklinik, Im Haberschlai 7, 70794 Filderstadt-Bonlanden, Germany fDepartment of Medicine University of Ottawa, 451 Smyth Rd, Ottawa, ON, Canada K1H 8M5 gSenior Research Scientist, Institute for Applied Epistemology and Medical Methodology at the University -
Yxilon - the Next Generation of Statistical Software
Yxilon - The Next Generation of Statistical Software Wolfgang H¨ardle Sigbert Klinke Uwe Ziegenhagen Institut f¨ur Statistik and Okonometrie¨ Humboldt-Universit¨at zu Berlin http://www.quantlet.org http://www.xplore-stat.de Contents of This Talk Introduction X Statistical Software Packages Requirements for Statistical Software Applications Introduction 1-1 “Each new generation of computers offers us new possiblities, at a time when we are far from using most of the possibilities offered by those already obsolete.” John W. Tukey (1965) Yxilon Introduction 1-2 Statistical Software Packages ACE, Alpha+, Analyse-it for Microsoft Excel, AnswerTree 3.0, Ascribe, 2ask, Askia, auditHOST,[B/D], Bellview® CAPI, Bellview® CATI, Bellview® Fusion, Bellview® Scan, Bellview® Web, Beyond 20/20, Beyond Question, Blaise, BMDP, Brand2hand,Clementine, CleverForm, Clicktools, Collect Data Now!, Community Express, Complete Report Automation, Confirmit, Cost$Benefit Analysis Tool, CSPro,DataSet V, DatStat Illume, Demographix, Dub Interviewer,Easyresearch - online surveys, Entryware™ Pro, EquivTest, ESBPDF Analysis, ESBStats, E-Tabs Enterprise, E-Tabs Interactive, E-Tabs Reader - Professional / Lite, E-Tabs Writer,Fitter, ForexastX Wizard, Formic 3, FUSE Enhanced Survey Solutions,GenStat, gllamm, Grader, GS+ Geostatistics for the Environmental Sciences,Halogen eSurveyor, HostedSurvey,IDAMS, IdeaMap.NET, Inquisite, InSite, Interviewer CAPI, Interviewer CATI, Interviewer VCC, Interviewer Web, Ioxphere, IRQuest, ISSA, IT, IYCQ Manager, IYSS,Jambo,KeyPlan, Keypoint -
Download This PDF File
Control Theory and Informatics www.iiste.org ISSN 2224-5774 (print) ISSN 2225-0492 (online) Vol 2, No.1, 2012 The Trend Analysis of the Level of Fin-Metrics and E-Stat Tools for Research Data Analysis in the Digital Immigrant Age Momoh Saliu Musa Department of Marketing, Federal Polytechnic, P.M.B 13, Auchi, Nigeria. Tel: +2347032739670 e-mail: [email protected] Shaib Ismail Omade (Corresponding author) Department of Statistics, School of Information and Communication Technology, Federal Polytechnic, P.M.B 13, Auchi, Nigeria. Phone: +2347032808765 e-mail: [email protected] Abstract The current trend in the information technology age has taken over every spare of human discipline ranging from communication, business, governance, defense to education world as the survival of these sectors depend largely on the research outputs for innovation and development. This study evaluated the trend of the usage of fin-metrics and e-stat tools application among the researchers in their research outputs- digital data presentation and analysis in the various journal outlets. The data used for the study were sourced primarily from the sample of 1720 out of 3823 empirical on and off line journals from various science and social sciences fields. Statistical analysis was conducted to evaluate the consistency of use of the digital tools in the methodology of the research outputs. Model for measuring the chance of acceptance and originality of the research was established. The Cockhran test and Bartlet Statistic revealed that there were significant relationship among the research from the Polytechnic, University and other institution in Nigeria and beyond. It also showed that most researchers still appeal to manual rather than digital which hampered the input internationally and found to be peculiar among lecturers in the system that have not yet appreciate IT penetration in Learning. -
Simulation Study to Compare the Random Data Generation from Bernoulli Distribution in Popular Statistical Packages
Simulation Study to Compare the Random Data Generation from Bernoulli Distribution in Popular Statistical Packages Manash Pratim Kashyap Department of Business Administration Assam University, Silchar, India [email protected] Nadeem Shafique Butt PIQC Institute of Quality Lahore, Pakistan [email protected] Dibyojyoti Bhattacharjee Department of Business Administration Assam University, Silchar, India [email protected] Abstract In study of the statistical packages, simulation from probability distributions is one of the important aspects. This paper is based on simulation study from Bernoulli distribution conducted by various popular statistical packages like R, SAS, Minitab, MS Excel and PASW. The accuracy of generated random data is tested through Chi-Square goodness of fit test. This simulation study based on 8685000 random numbers and 27000 tests of significance shows that ability to simulate random data from Bernoulli distribution is best in SAS and is closely followed by R Language, while Minitab showed the worst performance among compared packages. Keywords: Bernoulli distribution, Goodness of Fit, Minitab, MS Excel, PASW, SAS, Simulation, R language 1. Introduction Use of Statistical software is increasing day by day in scientific research, market surveys and educational research. It is therefore necessary to compare the ability and accuracy of different statistical softwares. This study focuses a comparison of random data generation from Bernoulli distribution among five softwares R, SAS, Minitab, MS Excel and PASW (Formerly SPSS). The statistical packages are selected for comparison on the basis of their popularity and wide usage. Simulation is the statistical method to recreate situation, often repeatedly, so that likelihood of various outcomes can be more accurately estimated.