Metropolis, Monte Carlo, and T MA N I A
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Computer Simulations and the Trading Zone
PETER &A Computer Simulations and the Trading Zone At the root of most accounts of the development of science is the covert premise that science is about ontology: What objects are there? How do they interact? And how do we discover them? It is a premise that underlies three distinct epochs of inquiry into the nature of science. Among the positivists, the later Carnap explicitly advocated a view that the objects of physics would be irretrievably bound up with what he called a "framework," a full set of linguistic relations such as is found in Newtonian or Eiustcini;~mechanics. That these frameworks held little in common did not trouble Car- nap; prediction mattered more than progress. Kuhn molded this notion and gave it a more historical focus. Unlike the positivists, Kuhn and other commentators of the 1960's wanted to track the process by which a community abandoned one framework and adopted another. To more recent scholars, the Kuhnian categoriza- tion of group affiliation and disaffiliation was by and large correct, but its underlying dynamics were deemed deficient because they paid insufficient attention to the sociological forces that bound groups to their paradigms. All three generations embody the root assumption that the analysis of science studies (or ought to study) a science classified and divided according to the objects of its inquiry. All three assume that as these objects change, particular branches of science split into myriad disconnected parts. It is a view of scientific disunity that I will refer to as "framework relativism. 55 In this essay, as before, I will oppose this view, but not by Computer Simulations I 19 invoking the old positivist pipe dreams: no universal protocol languages, no physicalism, no Corntian hierarchy of knowledge, and no radical reductionism. -
The Real Holocaust
THE REAL HOLOCAUST "Hitler will have no war, but he will be forced into it, not this year but later..." Emil Ludwig [Jew], Les Annales, June 1934 "We possess several hundred atomic warheads and rockets and can launch them at targets in all directions, perhaps even at Rome. Most European capitals are targets for our air force. Let me quote General Moshe Dayan: 'Israel must be like a mad dog, too dangerous to bother.' I consider it all hopeless at this point. We shall have to try to prevent things from coming to that, if at all possible. Our armed forces, however, are not the thirtieth strongest in the world, but rather the second or third. We have the capability to take the world down with us. And I can assure you that that will happen before Israel goes under." -- Martin van Creveld, Israeli professor of military history at the Hebrew University in Jerusalem in an interview in the Dutch weekly magazine: Elsevier, 2002, no. 17, p. 52-53. "We may never actually have to use this atomic weapon in military operations as the mere threat of its use will persuade any opponent to surrender to us." –Chaim Weizmann [Jew] "Jews Declared War on Germany. Even before the war started, the Jewish leaders on a worldwide basis had years before, declared that world Jewry was at war with Germany, and that they would utilize their immense financial, moral, and political powers to destroy Hitler and Nazi Germany. Principal among these was Chaim Weizmann, the Zionist leader, who so declared on September 5, 1939. -
Herman Heine Goldstine
Herman Heine Goldstine Born September 13, 1913, Chicago, Ill.; Army representative to the ENIAC Project, who later worked with John von Neumann on the logical design of the JAS computer which became the prototype for many early computers-ILLIAC, JOHNNIAC, MANIAC author of The Computer from Pascal to von Neumann, one of the earliest textbooks on the history of computing. Education: BS, mathematics, University of Chicago, 1933; MS, mathematics, University of Chicago, 1934; PhD, mathematics, University of Chicago, 1936. Professional Experience: University of Chicago: research assistant, 1936-1937, instructor, 1937-1939; assistant professor, University of Michigan, 1939-1941; US Army, Ballistic Research Laboratory, Aberdeen, Md., 1941-1946; Institute for Advanced Study, Princeton University, 1946-1957; IBM: director, Mathematics Sciences Department, 1958-1965, IBM fellow, 1969. Honors and Awards: IEEE Computer Society Pioneer Award, 1980; National Medal of Science, 1985; member, Information Processing Hall of Fame, Infornart, Dallas, Texas, 1985. Herman H. Goldstine began his scientific career as a mathematician and had a life-long interest in the interaction of mathematical ideas and technology. He received his PhD in mathematics from the University of Chicago in 1936 and was an assistant professor at the University of Michigan when he entered the Army in 1941. After participating in the development of the first electronic computer (ENIAC), he left the Army in 1945, and from 1946 to 1957 he was a member of the Institute for Advanced Study (IAS), where he collaborated with John von Neumann in a series of scientific papers on subjects related to their work on the Institute computer. In 1958 he joined IBM Corporation as a member of the research planning staff. -
Monte Carlo Simulation Techniques
Monte Carlo Simulation Techniques Ji Qiang Accelerator Modeling Program Accelerator Technology & Applied Physics Division Lawrence Berkeley National Laboratory CERN Accelerator School, Thessaloniki, Greece Nov. 13, 2018 Introduction: What is the Monte Carlo Method? • What is the Monte Carlo method? - Monte Carlo method is a (computational) method that relies on the use of random sampling and probability statistics to obtain numerical results for solving deterministic or probabilistic problems “…a method of solving various problems in computational mathematics by constructing for each problem a random process with parameters equal to the required quantities of that problem. The unknowns are determined approximately by carrying out observations on the random process and by computing its statistical characteristics which are approximately equal to the required parameters.” J. H. Halton, “A retrospective and prospective survey of the Monte Carlo Method,” SIAM Review, Vol. 12, No. 1 (1970). Introduction: What can the Monte Carlo Method Do? • Give an approximate solution to a problem that is too big, too hard, too irregular for deterministic mathematical approach • Two types of applications: a) The problems that are stochastic (probabilistic) by nature: - particle transport, - telephone and other communication systems, - population studies based on the statistics of survival and reproduction. b) The problems that are deterministic by nature: - the evaluation of integrals, - solving partial differential equations • It has been used in areas as diverse as physics, chemistry, material science, economics, flow of traffic and many others. Brief History of the Monte Carlo Method • 1772 Comte de Buffon - earliest documented use of random sampling to solve a mathematical problem (the probability of needle crossing parallel lines). -
Steering-The-Metropolis-V20
Steering the Metropolis Metropolitan Governance for Sustainable Urban Development Editors David Gómez-Álvarez • Eduardo López-Moreno • Robin Rajack Steering the Metropolis Metropolitan Governance for Sustainable Urban Development Editors David Gómez-Álvarez Eduardo López-Moreno Robin Rajack 3 Overview The publication proposed here provides state of the art scholarship on integrated approaches to metropolitan governance. The goal is to provide a variety of examples about the leading edge of effective metropolitan governance from a broad range of geographic, cross- disciplinary and thematic perspectives. A select group of scholars and experts examine current models of metropolitan governance as well as adminis- trative challenges and opportunities to achieve sustainable urban development. These examples carry different forms of innovation in areas such as planning, fnance, housing, services and citizen participation. Rationale In the last ffty years, migration, demographic changes and the transformation of land from rural to urban have provoked unprecedented rapid and expansive urbanization in different regions of the world, particularly in the Global South. In other regions from the Global North cities tend to shrink or stabilize in their populations having different gover- nance challenges. Increasingly metropolitan in character, urban expansion – and in some cases contraction - has brought to the fore a multiplicity of issues and diverse popula- tions at the intersection of different levels of governance. The spatial, legal, political, and social complexities of this phenomenon make effective metropolitan governance one of the most pressing challenges of our time in the search of sustainability. Today, it is diffcult to fnd a city of more than 500,000 inhabitants that is made only of one municipality. -
Berni Alder (1925–2020)
Obituary Berni Alder (1925–2020) Theoretical physicist who pioneered the computer modelling of matter. erni Alder pioneered computer sim- undergo a transition from liquid to solid. Since LLNL ulation, in particular of the dynamics hard spheres do not have attractive interac- of atoms and molecules in condensed tions, freezing maximizes their entropy rather matter. To answer fundamental ques- than minimizing their energy; the regular tions, he encouraged the view that arrangement of spheres in a crystal allows more Bcomputer simulation was a new way of doing space for them to move than does a liquid. science, one that could connect theory with A second advance concerned how non- experiment. Alder’s vision transformed the equilibrium fluids approach equilibrium: field of statistical mechanics and many other Albert Einstein, for example, assumed that areas of applied science. fluctuations in their properties would quickly Alder, who died on 7 September aged 95, decay. In 1970, Alder and Wainwright dis- was born in Duisburg, Germany. In 1933, as covered that this intuitive assumption was the Nazis came to power, his family moved to incorrect. If a sphere is given an initial push, Zurich, Switzerland, and in 1941 to the United its average velocity is found to decay much States. After wartime service in the US Navy, more slowly. This caused a re-examination of Alder obtained undergraduate and master’s the microscopic basis for hydrodynamics. degrees in chemistry from the University of Alder extended the reach of simulation. California, Berkeley. While working for a PhD In molecular dynamics, the forces between at the California Institute of Technology in molecules arise from the electronic density; Pasadena, under the physical chemist John these forces can be described only by quan- Kirkwood, he began to use mechanical com- tum mechanics. -
Managing Urban Growth
Managing Urban Growth Commission 2 Report 2011 Commission 2 Managing Urban Growth Presidency: Melbourne Vice-Presidency: Cairo Chair: The Hon. Justin Madden, MLC, Former Minister for Planning, Government of Victoria Vice-chair: HE Mr Ahmed El-Maghraby, Minister of Housing, Utilities and Urban Development, Egypt Coordinator: Mary Lewin, Manager International Affairs, Department of Planning and Community Development, Government of Victoria Participating Cities: Addis Ababa, Agra, Ahmedabad, Bamako, Bangalore, Barcelona, Belo Horizonte, Berlin, Cairo, Dakar, Douala, Isfahan, Guarulhos, Gyeonggi Province, Istanbul, Jamshedpur, Kolkata, Madrid, Manila, Mashhad, Melbourne, Mexico (State of), Moscow, New Delhi, Pune, Shiraz, São Paulo, Tabriz, Tehran, Udaipur, Vancouver Other Organizations: Global Cities Research Institute (RMIT University), UN Global Compact Cities Programme, Regional Vancouver Urban Observatory (RVu), National Institute of Urban Affairs (India), UN-Habitat, Urban Age Institute, ARUP Australia, IBM Acknowledgements: Mary Lewin, David Wilmoth, Christine Oakley, Meg Holden, Paul James, Lyndsay Neilson, Stephanie McCarthy, Matthew Snow, Peter Sagar, Art Truter Authors: See acknowledgements Managing Urban Growth Table of Contents 4 { INTRODUCTION 5 01. { URBANISATION AND GOVERNANCE 1.1. { Defining urbanisation and urban growth 5 1.2. { Responses to the challenges of urbanisation 10 23 02. { INFRASTRUCTURE AND SERVICE 2.1. { The good management of urban infrastructure 23 2.2. { The scale of the infrastructure challenge 26 2.3. { Responses 28 44 03. { INEQUITIES AND SOCIAL INCLUSION 3.1. { Defining positive social inclusion 44 3.2. { Positive responses 46 54 04. { LOCAL, REGIONAL AND GLOBAL ECONOMIES 4.1. { Issues and challenges 54 4.2. { Responses in the economic domain 57 61 05. { THE ENVIRONMENT 5.1. { Issues and challenges 62 5.2. -
Platform Systems Vs. Step Processes—The Value of Options and the Power of Modularity by Carliss Y
© Carliss Y. Baldwin Comments welcome. Design Rules, Volume 2: How Technology Shapes Organizations Chapter 13 Platform Systems vs. Step Processes—The Value of Options and the Power of Modularity By Carliss Y. Baldwin Note to Readers: This is a draft of Chapter 13 of Design Rules, Volume 2: How Technology Shapes Organizations. It builds on prior chapters, but I believe it is possible to read this chapter on a stand-alone basis. The chapter may be cited as: Baldwin, C. Y. (2019) “Platform Systems vs. Step Processes—The Value of Options and the Power of Modularity,” HBS Working Paper (January 2019). I would be most grateful for your comments on any aspect of this chapter! Thank you in advance, Carliss. Abstract The purpose of this chapter is to contrast the value structure of platform systems (e.g. a computer) with step processes (e.g. an assembly line). I first review the basic technical architecture of computers and argue that every computer is inherently a platform for performing computations as dictated by their programs. I state and prove five propositions about platform systems, which stand in contrast to the propositions derived for step processes in Chapter 8. The propositions suggest that platform systems and step processes call for different forms of organization. Specifically, step processes reward technical integration, unified governance, risk aversion, and the use of direct authority, while platform systems reward modularity, distributed governance, risk taking, and autonomous decision-making. Despite these differences, treating platform systems and step processes as mutually exclusive architectures sets up a false dichotomy. Creating any good requires carrying out a technical recipe, i.e., performing a series of steps. -
9. Metro Manila, Philippines Theresa Audrey O
9. Metro Manila, Philippines Theresa Audrey O. Esteban and Michael Lindfield 9.1 INTRODUCTION Metro Manila, the National Capital Region of the Philippines, is the seat of government and the most populous region of the Philippines. It covers an area of more than 636 square kilometres and is composed of the City of Manila and 16 other local government units (15 cities and one municipality) (). As the city has grown, the local government structure has led to a polycentric system of highly competitive cities in the metropolitan region. The impact of rapid urbanization on the city has been dramatic. Metro Manila is the centre of culture, tourism, Figure 9.1 Map of Metro Manila the economy, education and the government of the Philippines. Its most populous and largest city in terms of land area is Quezon City, with the centre of business and financial activities in Makati (Photo 9.1). Other commercial areas within the region include Ortigas Centre; Bonifacio Global City; Araneta Centre, Eastwood City and Triangle Park in Quezon City; the Bay City reclamation area; and Alabang in Muntinlupa. Among the 12 defined metropolitan areas in the Philippines, Metro Manila is the most populous.427 It is also the 11th most populous metropolitan area in the world.428 The 2010 census data from the Philippine National Statistics Office show Metro Manila having a population almost 11.85 million, which is equivalent to 13 percent of the population of the Philippines. 429 Metro Manila ranks as the most densely populated of the metropolitan areas in the Philippines. Of the ten most populous cities in Credit: Wikipedia Commons / Magalhaes. -
Urban Area Types of Urban Area
URBAN AREA TYPES OF URBAN AREA • An urban area is the region surrounding a city. Most inhabitants of urban areas have non-agricultural jobs. Urban areas are very developed, meaning there is a density of human structures such as houses, commercial buildings, roads, bridges, and railways. • "Urban area" can refer to towns, cities, and suburbs. An urban area includes the city itself, as well as the surrounding areas. Many urban areas are called metropolitan areas, or "greater," as in Greater New York or Greater London. • An urban area is a human settlement with high population density and infrastructure of built environment. Urban areas are created through urbanization and are categorized by urban morphology as cities, towns, conurbations or suburbs. • In urbanism, the term contrasts to rural areas such as villages and hamlets and in urban sociology or urban anthropology it contrasts with natural environment. • The creation of early predecessors of urban areas during the urban revolution led to the creation of human civilization with modern urban planning, which along with other human activities such as exploitation of natural resources leads to human impact on the environment. • The world's urban population in 1950 of just 746 million has increased to 3.9 billion in the decades since. • In 2009, the number of people living in urban areas (3.42 billion) surpassed the number living in rural areas (3.41 billion) and since then the world has become more urban than rural. • This was the first time that the majority of the world's population lived in a city. • In 2014 there were 7.2 billion people living on the planet, of which the global urban population comprised 3.9 billion. -
TME Volume 5, Numbers 2 and 3
The Mathematics Enthusiast Volume 5 Number 2 Numbers 2 & 3 Article 27 7-2008 TME Volume 5, Numbers 2 and 3 Follow this and additional works at: https://scholarworks.umt.edu/tme Part of the Mathematics Commons Let us know how access to this document benefits ou.y Recommended Citation (2008) "TME Volume 5, Numbers 2 and 3," The Mathematics Enthusiast: Vol. 5 : No. 2 , Article 27. Available at: https://scholarworks.umt.edu/tme/vol5/iss2/27 This Full Volume is brought to you for free and open access by ScholarWorks at University of Montana. It has been accepted for inclusion in The Mathematics Enthusiast by an authorized editor of ScholarWorks at University of Montana. For more information, please contact [email protected]. The Montana Mathematics Enthusiast ISSN 1551-3440 VOL. 5, NOS.2&3, JULY 2008, pp.167-462 Editor-in-Chief Bharath Sriraman, The University of Montana Associate Editors: Lyn D. English, Queensland University of Technology, Australia Claus Michelsen, University of Southern Denmark, Denmark Brian Greer, Portland State University, USA Luis Moreno-Armella, University of Massachusetts-Dartmouth International Editorial Advisory Board Miriam Amit, Ben-Gurion University of the Negev, Israel. Ziya Argun, Gazi University, Turkey. Ahmet Arikan, Gazi University, Turkey. Astrid Beckmann, University of Education, Schwäbisch Gmünd, Germany. John Berry, University of Plymouth,UK. Morten Blomhøj, Roskilde University, Denmark. Robert Carson, Montana State University- Bozeman, USA. Mohan Chinnappan, University of Wollongong, Australia. Constantinos Christou, University of Cyprus, Cyprus. Bettina Dahl Søndergaard, University of Aarhus, Denmark. Helen Doerr, Syracuse University, USA. Ted Eisenberg, Ben-Gurion University of the Negev, Israel. -
The New Metropolis: Rethinking Megalopolis
Regional Studies, Vol. 43.6, pp. 789–802, July 2009 The New Metropolis: Rethinking Megalopolis ROBERT LANGÃ and PAUL K. KNOX† ÃVirginia Tech – Metropolitan Institute, 1021 Prince Street, Suite 100, Alexandria, VA 22314, USA. Email: [email protected] †The Metropolitan Institute, School of Public and International Affairs, 123C Burruss Hall (0178), Virginia Tech, Blacksburg, VA 24061, USA. Email: [email protected] (Received January 2007: in revised form May 2007) LANG R. and KNOX P. K. The new metropolis: rethinking megalopolis, Regional Studies. The paper explores the relationship between metropolitan form, scale, and connectivity. It revisits the idea first offered by geographers Jean Gottmann, James Vance, and Jerome Pickard that urban expansiveness does not tear regions apart but instead leads to new types of linkages. The paper begins with an historical review of the evolving American metropolis and introduces a new spatial model showing changing metropolitan morphology. Next is an analytic synthesis based on geographic theory and empirical findings of what is labelled here the ‘new metropolis’. A key element of the new metropolis is its vast scale, which facilitates the emergence of an even larger trans-metropolitan urban structure – the ‘megapolitan region’. Megapolitan geography is described and includes a typology to show variation between regions. The paper concludes with the suggestion that the fragmented post-modern metropolis may be giving way to a neo-modern extended region where new forms of networks and spatial connectivity reintegrate urban space. Metropolitan morphology New metropolis Spatial connectivity Megapolitan region Spatial model American metropolis LANG R. et KNOX P.K. La nouvelle metropolis: repenser la me´gapole, Regional Studies.