50 Years of IFIP - Developments and Visions IFIP – the International Federation for Information Processing
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Monash University's Campus LAN in the 1980S
MONET – Monash University’s Campus LAN in the 1980s – A Bridge to Better Networking Barbara Ainsworth, Neil Clarke, Chris Avram, Judy Sheard To cite this version: Barbara Ainsworth, Neil Clarke, Chris Avram, Judy Sheard. MONET – Monash University’s Campus LAN in the 1980s – A Bridge to Better Networking. IFIP International Conference on the History of Computing (HC), May 2016, Brooklyn, NY, United States. pp.23-48, 10.1007/978-3-319-49463-0_2. hal-01620140 HAL Id: hal-01620140 https://hal.inria.fr/hal-01620140 Submitted on 20 Oct 2017 HAL is a multi-disciplinary open access L’archive ouverte pluridisciplinaire HAL, est archive for the deposit and dissemination of sci- destinée au dépôt et à la diffusion de documents entific research documents, whether they are pub- scientifiques de niveau recherche, publiés ou non, lished or not. The documents may come from émanant des établissements d’enseignement et de teaching and research institutions in France or recherche français ou étrangers, des laboratoires abroad, or from public or private research centers. publics ou privés. Distributed under a Creative Commons Attribution| 4.0 International License MONET – Monash University’s Campus LAN in the 1980s – a Bridge to Better Networking Barbara Ainsworth1, Neil Clarke2, Chris Avram1, Judy Sheard1 1 Monash University, Monash Museum of Computing History, Melbourne, Australia {Barbara.Ainsworth,Chris.Avram,Judy.Sheard}@monash.edu 2 Deakin University, Audiovisual and Networks Unit, Melbourne, Australia [email protected] Abstract. Monash University, Australia developed an in-house local area network called MONET during the 1980s to meet the needs of the university’s computer users. -
DLTV Journal 5 1.Cdr
DLTV 5.1 JOURNAL The Journal of Digital Learning and Teaching Victoria V o l u m e 5 | N u m b e r 1 | 2 0 1 8 | I S S N 2 2 0 5 - 3 6 1 1 ( O n l i n e ) Contents EDITORIAL 2 DLTV Journal Pennie White and Roland Gesthuizen The Journal of Digital Learning and Teaching Victoria FROM THE PRESIDENT 3 Editors Ben Gallagher Pennie White Roland Gesthuizen VALE MARK RICHARDSON 5 Melinda Cashen Associate Editors Narissa Leung DIGICON18 AND THE DLTV AWARDS 6 Clark Burt Ben Gallagher Catherine Newington Irene Anderson BITS AND BYTES 8 Cameron Hocking VCE Programming Language Options to Consider Maria-Ana Sanchez Publisher Mind Mapping with VCE Software Development Digital Learning and Teaching Victoria Chris Paragreen Starting a STEM Space The DLTV Committee Celeste Pettinella of Management 2018-2019 Ben Gallagher- President TIME CAPSULE 11 Andrew Williamson - Vice President From CEGV 1979 to ACEC 2000: Australian computers in education Mel Cashen - Treasurer conferences come of age Narissa Leung - Secretary Anne McDougall & Barry McCrae Irene Anderson (co-opted) Clark Burt HOW DOES THE USE OF GAMEMAKER SOFTWARE FOSTER THE 16 Ian Fernee DEVELOPMENT OF CREATIVE PROBLEM– SOLVING SKILLS IN BOYS? Roland Gesthuizen Matthew Harrison Ben Marr Robert Maalouf Catherine Newington BUILDING A PLATFORM FOR CHANGE AND REDESIGNING 26 Fiona Turner (co-opted) THE ROLE OF A RESELLER Greg Bowen 61 Blyth Street Brunswick VIC 3056 Australia USING ROBOTS AND DIGITECH FOR STUDENTS WITH DISABILITIES 27 Phone: +61 3 9349 3733 K. Clark Burt Web: www.dltv.vic.edu.au Email: [email protected] Twitter: @DLTVictoria DITCHING THE DESKS 31 Flexible learning spaces focus on helping students be productive, comfortable Invitation to send contributions to Tim Douglas [email protected] ABN 20 211 799 378 3 POWERFUL WORDS CAN UNLOCK COMPUTER SCIENCE SUCCESS 35 Registration Number A0060428T The Digital Learning and Teaching Journal is Janice Mak published as a resource for all educators engaged in the effective use of information and communication technologies for teaching and learning. -
Quantum Hypercomputation—Hype Or Computation?
Quantum Hypercomputation—Hype or Computation? Amit Hagar,∗ Alex Korolev† February 19, 2007 Abstract A recent attempt to compute a (recursion–theoretic) non–computable func- tion using the quantum adiabatic algorithm is criticized and found wanting. Quantum algorithms may outperform classical algorithms in some cases, but so far they retain the classical (recursion–theoretic) notion of computability. A speculation is then offered as to where the putative power of quantum computers may come from. ∗HPS Department, Indiana University, Bloomington, IN, 47405. [email protected] †Philosophy Department, University of BC, Vancouver, BC. [email protected] 1 1 Introduction Combining physics, mathematics and computer science, quantum computing has developed in the past two decades from a visionary idea (Feynman 1982) to one of the most exciting areas of quantum mechanics (Nielsen and Chuang 2000). The recent excitement in this lively and fashionable domain of research was triggered by Peter Shor (1994) who showed how a quantum computer could exponentially speed–up classical computation and factor numbers much more rapidly (at least in terms of the number of computational steps involved) than any known classical algorithm. Shor’s algorithm was soon followed by several other algorithms that aimed to solve combinatorial and algebraic problems, and in the last few years the- oretical study of quantum systems serving as computational devices has achieved tremendous progress. According to one authority in the field (Aharonov 1998, Abstract), we now have strong theoretical evidence that quantum computers, if built, might be used as powerful computational tool, capable of per- forming tasks which seem intractable for classical computers. -
Alan Turing, Hypercomputation, Adam Smith and Next Generation Intelligent Systems
J. Intell. Syst. 21 (2012), 325–330 DOI 10.1515/jisys-2012-0017 © de Gruyter 2012 Something Old, Something New, Something Borrowed, Something Blue Part 1: Alan Turing, Hypercomputation, Adam Smith and Next Generation Intelligent Systems Mark Dougherty Abstract. In this article intelligent systems are placed in the context of accelerated Turing machines. Although such machines are not currently a reality, the very real gains in computing power made over previous decades require us to continually reevaluate the potential of intelligent systems. The economic theories of Adam Smith provide us with a useful insight into this question. Keywords. Intelligent Systems, Accelerated Turing Machine, Specialization of Labor. 2010 Mathematics Subject Classification. Primary 01-02, secondary 01A60, 01A67. 1 Introduction The editor-in-chief of this journal has asked me to write a series of shorter articles in which I try to illuminate various challenges in intelligent systems. Given space requirements they cannot be regarded as comprehensive reviews, they are intended to provide an overview and to be a point of departure for discussion and debate. The title of the series implies that I will look at both very old and rather new concepts and I will not be afraid to borrow from other subjects. Nor will I be afraid to incorporate radical “blue skies” ideas or hypotheses. By challenges I mean aspects of our subject which cannot easily be tackled by either theoretical means or through empirical enquiry. That may be because the questions raised are not researchable or because no evidence has yet been ob- served. Or it may be that work is underway but that no firm conclusions have yet been reached by the research community. -
Biological Computation: a Road
918 Biological Computation: A Road to Complex Engineered Systems Nelson Alfonso Gómez-Cruz Modeling and Simulation Laboratory Universidad del Rosario Bogotá, Colombia [email protected] Carlos Eduardo Maldonado Research Professor Universidad del Rosario Bogotá, Colombia [email protected] Provided that there is no theoretical frame for complex engineered systems (CES) as yet, this paper claims that bio-inspired engineering can help provide such a frame. Within CES bio- inspired systems play a key role. The disclosure from bio-inspired systems and biological computation has not been sufficiently worked out, however. Biological computation is to be taken as the processing of information by living systems that is carried out in polynomial time, i.e., efficiently; such processing however is grasped by current science and research as an intractable problem (for instance, the protein folding problem). A remark is needed here: P versus NP problems should be well defined and delimited but biological computation problems are not. The shift from conventional engineering to bio-inspired engineering needs bring the subject (or problem) of computability to a new level. Within the frame of computation, so far, the prevailing paradigm is still the Turing-Church thesis. In other words, conventional 919 engineering is still ruled by the Church-Turing thesis (CTt). However, CES is ruled by CTt, too. Contrarily to the above, we shall argue here that biological computation demands a more careful thinking that leads us towards hypercomputation. Bio-inspired engineering and CES thereafter, must turn its regard toward biological computation. Thus, biological computation can and should be taken as the ground for engineering complex non-linear systems. -
State of the Art of Information Technology Computing Models for Autonomic Cloud Computing †
Proceedings State of the Art of Information Technology Computing Models for Autonomic Cloud Computing † Eugene Eberbach Department of Computer Science and Robotics Engineering Program, Worcester Polytechnic Institute, 100 Institute Road, Worcester, MA 01609-2280, USA; [email protected]; Tel.: +1-508-831-4937 † Presented at the IS4SI 2017 Summit DIGITALISATION FOR A SUSTAINABLE SOCIETY, Gothenburg, Sweden, 12–16 June 2017. Published: 9 June 2017 Abstract: In the paper we present several models of computation for autonomic cloud computing. In particular, we justify that for autonomic cloud computing if we require perfect self-reflection, we need models of computation going beyond Turing machines. To approximate self-reflection, models below Turing machines are sufficient. The above claims are illustrated using as an example the DIME Network Architecture. Keywords: autonomic cloud computing; Turing machine; incompleteness; self-reflection; superTuring machines; DIME network architecture 1. Introduction A distributed system is a collection of independent computers that appears to its users as a single coherent system with basic characteristics: 1. concurrency of components, lack of a global clock, scalability and independent failures of components, 2. underlying transparency (inherited by cloud computing), hiding unnecessary details of management, networking, multi-computer implementation or services, 3. providing a uniform way of looking at the whole distributed system. We will consider two subclasses of distributed systems represented by cloud and autonomic computing. Cloud Computing is a relatively new concept in computing that emerged in the late 1990s and the 2000s (but having roots from 1960s—IBM VMs for System360/370/390), first under the name software as a service—the details of computing are hidden transparently in the networking “cloud” 1. -
The Codeeazee Tool Support for Computational Thinking in Python
EJERS, European Journal of Engineering Research and Science Vol. 3, No. 3, March 2018 The CodeEazee Tool Support for Computational Thinking in Python Francisca O. Oladipo, and Memunat A. Ibrahim the non-linear and dynamic programming processes as static Abstract—This paper describes the development of and linear, making them assume that the link between every CodeEazee, a problem solving, self- teaching tool for python problem and solution is simple and direct [10]. programming which deploys templates and games. In this Basically, two factors are fundamental to teaching work, the authors conducted a survey to determine the factors programming, which are: choosing a programming language responsible for the reduced interests of learners in programming, reviewed the various approaches used in and choosing an effective approach for teaching [11]. These teaching programming, and developed a python-for-python choices are essential to the students understanding teaching system to teach programming skills, computational programming and acquiring the necessary programming thinking, algorithms’ design, programming in general and skills, and also to prepare them for other higher Python programming specifically. The work would show how programming course [12]; and a wrong choice of the third party environment had enabled users with limited or programming language [9] or teaching approach can make no programming experiences to design applications through peer supports, templates and gamification, embedded in a learning programming difficult [13]. Similarly, knowing the programming tool. students’ learning styles will help in determining the best teaching approach to be used [14], leading to the conclusion Index Terms—Algorithms; Computation; Problem-Solving that finding and employing an appropriate teaching Skills; Programming; Python. -
Dines Bjørner Research, Bibliography, Biography and Publication List
CV: Dines Bjørner Research, Bibliography, Biography and Publication List Professor of Computing Science (Emeritus). Fredsvej 11, DK-2840 Holte, Denmark Dr.h.c., MAE, MRANS (AB), ACM Fellow, IEEE Fellow May 16, 2010 Dines Bjørner, Sept. 2007 For more photos see Sect. 5 Contents 2.3 Book Covers ............... 5 1 My Research 2 3 Biography 7 2 Publication Notes 3 4 References 9 2.1 Year-by-Year Listing ........... 3 2.2 Statistics ................. 4 5 Photos 24 1 My Research My research, since my IBM Vienna days, has focused on computing science,1 in particular program- ming methodology: on how to construct software. I was never much for the more foundational 1By computing science I understand the study of and knowledge about how to construct the “things” that can exist “inside” computers: data and processes. 1 side of computing, or as I call it, computer science.2 3 I am in particular “smitten” by the question what is a method ?. I see a method as a set of principles to be used in the analysis of problems and in the synthesis of solutions to these problems. I see the analysis and synthesis to be based on techniques and tools. The principles are then about the selection and practical use of the analysis and synthesis techniques and tools — research must uncover these principles, techniques and tools. Software engineering textbooks must cover them.4 I see a good software development method to be one that provides for efficient development approaches resulting in efficient software that meets customers expectations (and only and exactly those) and software that is correct (that is satisfies its requirements). -
Education in Australia Streams in the History Of
STREAMS IN THE HISTORY OF COMPUTER EDUCATION IN AUSTRALIA An Overview of School and University Computer Education Arthur Tatnall and Bill Davey Victoria University and RMIT University Australia E-mail: [email protected] Abstract: In world terms, Australia moved into the educational computing, both at the Higher Education and School levels, very early. This paper looks at how university subjects, and later how whole courses in computing evolved in Australia and how these had very little effect on the later use of computers in schools. We briefly examine how computers were first used in schools, and the influences that put them there and decided how they could be used. We relate an established a model of the growth of academic subjects to the emergence of the discipline area of computing, and in particular, to the Victorian Year 12 Computer Science subject. Key words: Computer science; Information systems; Computer education; Computers across the curriculum; School computing; University computing. 1. INTRODUCTION The Commonwealth of Australia is a federation of six states and two territories each having a considerable degree of independence. Constitutionally, education is the role of the individual State; the Commonwealth Government being limited to co-ordination, leadership and the funding of specific projects. While also considering Australia-wide issues, this paper will concentrate its perspective on the state of Victoria. In this paper we will provide an overview of the evolution and history of the various streams of educational computing in Australia: University-level Computer Science and Information Systems courses, Primary and Secondary School courses teaching about computing, and the use of computers in other 84 Arthur Tatnall and Bill Davey school subjects. -
Handbook 1981
THE UNIVERSITY OF MELBOURNE FACULTY 0F SCIENCE HANDBOOK 1981 PUBLISHED BY THE UNIVERSITY THIS HANDBOOK CONTAINS: 1. The courses offered by the faculty of Science. 2. The relevant University regulations. 3. Other information of importance to students. This handbook is your book of rules for work towards a Science degree. Read it carefully and use it to select combinations of subjects which will allow you to take the subjects you wish in subse- quent years. Consult faculty or departmental advisers before making your final enrolment. The complete Statutes and Regulations of the University may be found in the University Calendar which may be seen in the Baillieu Library or bought at the University Bookroom. Prospective students are referred to another booklet Guide to Science Courses. It Is distributed to most Victorian secondary schools and is available from the University Bookroom or the faculty office. The Science Faculty Handbook should be read in conjunction with the Student Diary issued free to all enrolling or re-enroll- ing students. A map of the University will be found in the Students' Infor- mation Booklet. In exceptional circumstances the Council is empowered to suspend subjects and to vary the syllabus of a subject. Details of any such altera- tion will be available from the faculty office and will be announced on departmental noticeboards. 2 TABLE OF CONTENTS Important Dates for Students Front cover This Handbook Contains 2 Preface 5 CHAPTER 1 General Information for AR Students 6 Continuing Education Student Diary CHAPTER 2 -
2015 Queensland Pearcey Entrepreneur Award
2018 Pearcey Day at DIF Tuesday, 28 August 2018 Pearcey Foundation Inc. Twitter: @pearcey_org #DIFVIC #DIFVicFeatureEvent https://pearcey.org.au Welcome Celebrating the Past; Informing the Present; Inspiring the Future Dr Peter Thorne Chairman, National Committee Twitter: @pearcey_org https://pearcey.org.au #DIFVIC #DIFVicFeatureEvent 2 Panel Speakers Dr Matthew Connell Powerhouse Museum Twitter: @pearcey_org https://pearcey.org.au #DIFVIC #DIFVicFeatureEvent 3 Panel Speakers David Piltz Telstra/Heritage Communication Ltd Twitter: @pearcey_org https://pearcey.org.au #DIFVIC #DIFVicFeatureEvent 4 TELECOMMUNICATIONS HERITAGE David Piltz Telstra Corp Ltd TELSTRA TELSTRA TELSTRA TEMPLATE TEMPLATE BLUE BLUE 4X3BETA4X3BETA| | TELPPTV4 TELPPTV4 COMMUNICATIONS HISTORY • Communication dates back Millennia ➢ Indigenous message sticks ➢ Smoke Signals ➢ Optical Telegraph by Semaphore Flags • Wired Communication ➢ Telegraph ➢ Telephone ➢ Switchboards ➢ Electromechanical exchanges ➢ Optical fibre • Wireless Communication ➢ Radio Telegraphy ➢ Radio Broadcasting ➢ Radio Duplex Voice • Advancements ➢ Semiconductors ➢ Computers ➢ Miniaturisation and Handheld devices HERITAGE ASSETS IN PMG / TELECOM / TELSTRA • Passionate individuals within Telstra and its predecessor entities have been working to protect the company’s historical legacy for many years. • The Collection has gone through various phases of organisational sponsorship and management over many years – this has included paid historical officers and individual state based approaches. • A ‘Telstra -
Short Biography
Lecture Automation Mailüfterl Homeostat Calendar Science M Logic Algebra Informatics Wien Austria Academy of Sciences Computer Art B I Cybernetics January 1 1920 InformationOCG Theorie Digitalization IFA IP Logic Vienna Definition Language Radarforschung ALGOL ComputerM usic Formale Definition l K History IBM Labor Vienna Pulse-code modulation horezmi Vocoder Robotics Telecommunications URR IBM Fellow Semiotics Transmission Abstracte Architekture Language Theory Turtle HEINZ ZEMANEK Computer Language Vienna University of Technology Human Computer Interaction An Austrian Computer Pioneer Heinz Zemanek - Biographical data Heinz Zemanek was born in Vienna on 1 January 1920. Education and military service (1925 - 1947) 1925 - 1929 primary school Vienna 1929 - 1937 secondary school Vienna (graduation with honours in 1937) 1937 - 1944 studies of radio mechanics at the Technical University of Vienna (TU) 1940 - 1945 Military service in a communication unit of the Wehrmacht Employment: Teleprinter practice in Vienna Switchboard operator in Kronstadt and Sofia Work at the manual transmission centres in Thessaloniki, Athens und Belgrade Teacher at the Wehrmacht intelligence service school Thessaloniki High frequency research at the Ernst Lechner Institut in Reichenau/Semmering Technical academy of the Luftwaffe, institute for communication engineering in Berlin-Gatow Work at the Zentralversuchsstelle der Hochfrequenzforschung in Ulm-Dornstadt (high frequency research) University thesis: 1944, Über die Erzeugung von kurzen Impulsen aus einer Sinusschwingung