Read a Sample
Total Page:16
File Type:pdf, Size:1020Kb
Load more
Recommended publications
-
Edsger Dijkstra: the Man Who Carried Computer Science on His Shoulders
INFERENCE / Vol. 5, No. 3 Edsger Dijkstra The Man Who Carried Computer Science on His Shoulders Krzysztof Apt s it turned out, the train I had taken from dsger dijkstra was born in Rotterdam in 1930. Nijmegen to Eindhoven arrived late. To make He described his father, at one time the president matters worse, I was then unable to find the right of the Dutch Chemical Society, as “an excellent Aoffice in the university building. When I eventually arrived Echemist,” and his mother as “a brilliant mathematician for my appointment, I was more than half an hour behind who had no job.”1 In 1948, Dijkstra achieved remarkable schedule. The professor completely ignored my profuse results when he completed secondary school at the famous apologies and proceeded to take a full hour for the meet- Erasmiaans Gymnasium in Rotterdam. His school diploma ing. It was the first time I met Edsger Wybe Dijkstra. shows that he earned the highest possible grade in no less At the time of our meeting in 1975, Dijkstra was 45 than six out of thirteen subjects. He then enrolled at the years old. The most prestigious award in computer sci- University of Leiden to study physics. ence, the ACM Turing Award, had been conferred on In September 1951, Dijkstra’s father suggested he attend him three years earlier. Almost twenty years his junior, I a three-week course on programming in Cambridge. It knew very little about the field—I had only learned what turned out to be an idea with far-reaching consequences. a flowchart was a couple of weeks earlier. -
Reinventing Education Based on Data and What Works • Since 1955
Reinventing Education Based on Data and What Works • Since 1955 Carnegie Mellon is reinventing education and the way we think about leveraging technology through its study of the science of learning – an interdisciplinary effort that we’ve been tackling for more than 50 years with both computer scientists and psychologists. CMU's educational technology innovations have inspired numerous startup companies, which are helping students to learn more effectively and efficiently. 1955: Allen Newell (TPR ’57) joins 1995: Prof. Kenneth R. Koedinger (HSS Prof. Herbert Simon’s research team as ’88,’90) and Anderson develop Practical a Ph.D. student. Algebra Tutor. The program pioneers a new form of computer-aided instruction for high 1956: CMU creates one of the world’s first school students based on cognitive tutors. university computation centers. With Prof. Alan Perlis (MCS ’42) as its head, it is a joint 1995: Prof. Jack Mostow (SCS ’81) undertaking of faculty from the business, develops Project LISTEN, an intelligent tutor Simon, Newell psychology, electrical engineering and that helps children learn to read. The National mathematics departments, and the Science Foundation included Project precursor to computer science. LISTEN’s speech recognition system as one of its top 50 innovations from 1950-2000. 1956: Simon creates a “thinking machine”—enacting a mental process 1995: The Center for Automated by breaking it down into its simplest Learning and Discovery is formed, led steps. Later that year, the term “artificial by Prof. Thomas M. Mitchell. intelligence” is coined by a small group Perlis including Newell and Simon. 1998: Spinoff company Carnegie Learning is founded by CMU scientists to expand 1956: Simon, Newell and J. -
Considerations for Use of Microcomputers in Developing Countrystatistical Offices
Considerations for Use of Microcomputers in Developing CountryStatistical Offices Final Report Prepared by International Statistical Programs Center Bureau of the Census U.S. Department of Commerce Funded by Office of the Science Advisor (c Agency for International Development issued October 1983 IV U.S. Department of Commerce Malcolm Baldrige, Secretary Clarence J. Brown, Deputy Secretary BUREAU OF THE CENSUS C.L. Kincannon, Deputy Director ACKNOWLEDGE ME NT S This study was conducted by the International Statistical Programs Center (ISPC) of the U.S. Bureau of the Census under Participating Agency Services Agreement (PASA) #STB 5543-P-CA-1100-O0, "Strengthening Scientific and Technological Capacity: Low Cost Microcomputer Technology," with the U.S. Agency for International Development (AID). Funding fcr this project was provided as a research grant from the Office of the Science Advisor of AID. The views and opinions expressed in this report, however, are those of the authors, and do not necessarily reflect those of the sponsor. Project implementation was performed under general management of Robert 0. Bartram, Assistant Director for International Programs, and Karl K. Kindel, Chief ISPC. Winston Toby Riley III provided input as an independent consultant. Study activities and report preparation were accomplished by: Robert R. Bair -- Principal Investigator Barbara N. Diskin -- Project Leader/Principal Author Lawrence I. Iskow -- Author William K. Stuart -- Author Rodney E. Butler -- Clerical Assistant Jerry W. Richards -- Clerical Assistant ISPC would like to acknowledge the many microcomputer vendors, software developers, users, the United Nations Statistical Office, and AID staff and contractors that contributed to the knowledge and experiences of the study team. -
The Advent of Recursion & Logic in Computer Science
The Advent of Recursion & Logic in Computer Science MSc Thesis (Afstudeerscriptie) written by Karel Van Oudheusden –alias Edgar G. Daylight (born October 21st, 1977 in Antwerpen, Belgium) under the supervision of Dr Gerard Alberts, and submitted to the Board of Examiners in partial fulfillment of the requirements for the degree of MSc in Logic at the Universiteit van Amsterdam. Date of the public defense: Members of the Thesis Committee: November 17, 2009 Dr Gerard Alberts Prof Dr Krzysztof Apt Prof Dr Dick de Jongh Prof Dr Benedikt Löwe Dr Elizabeth de Mol Dr Leen Torenvliet 1 “We are reaching the stage of development where each new gener- ation of participants is unaware both of their overall technological ancestry and the history of the development of their speciality, and have no past to build upon.” J.A.N. Lee in 1996 [73, p.54] “To many of our colleagues, history is only the study of an irrele- vant past, with no redeeming modern value –a subject without useful scholarship.” J.A.N. Lee [73, p.55] “[E]ven when we can't know the answers, it is important to see the questions. They too form part of our understanding. If you cannot answer them now, you can alert future historians to them.” M.S. Mahoney [76, p.832] “Only do what only you can do.” E.W. Dijkstra [103, p.9] 2 Abstract The history of computer science can be viewed from a number of disciplinary perspectives, ranging from electrical engineering to linguistics. As stressed by the historian Michael Mahoney, different `communities of computing' had their own views towards what could be accomplished with a programmable comput- ing machine. -
Oracle Vs. Nosql Vs. Newsql Comparing Database Technology
Oracle vs. NoSQL vs. NewSQL Comparing Database Technology John Ryan Senior Solution Architect, Snowflake Computing Table of Contents The World has Changed . 1 What’s Changed? . 2 What’s the Problem? . .. 3 Performance vs. Availability and Durability . 3 Consistecy vs. Availability . 4 Flexibility vs . Scalability . 5 ACID vs. Eventual Consistency . 6 The OLTP Database Reimagined . 7 Achieving the Impossible! . .. 8 NewSQL Database Technology . 9 VoltDB . 10 MemSQL . 11 Which Applications Need NewSQL Technology? . 12 Conclusion . 13 About the Author . 13 ii The World has Changed The world has changed massively in the past 20 years. Back in the year 2000, a few million users connected to the web using a 56k modem attached to a PC, and Amazon only sold books. Now billions of people are using to their smartphone or tablet 24x7 to buy just about everything, and they’re interacting with Facebook, Twitter and Instagram. The pace has been unstoppable . Expectations have also changed. If a web page doesn’t refresh within seconds we’re quickly frustrated, and go elsewhere. If a web site is down, we fear it’s the end of civilisation as we know it. If a major site is down, it makes global headlines. Instant gratification takes too long! — Ladawn Clare-Panton Aside: If you’re not a seasoned Database Architect, you may want to start with my previous articles on Scalability and Database Architecture. Oracle vs. NoSQL vs. NewSQL eBook 1 What’s Changed? The above leads to a few observations: • Scalability — With potentially explosive traffic growth, IT systems need to quickly grow to meet exponential numbers of transactions • High Availability — IT systems must run 24x7, and be resilient to failure. -
The Declarative Imperative Experiences and Conjectures in Distributed Logic
The Declarative Imperative Experiences and Conjectures in Distributed Logic Joseph M. Hellerstein University of California, Berkeley [email protected] ABSTRACT The juxtaposition of these trends presents stark alternatives. The rise of multicore processors and cloud computing is putting Will the forecasts of doom and gloom materialize in a storm enormous pressure on the software community to find solu- that drowns out progress in computing? Or is this the long- tions to the difficulty of parallel and distributed programming. delayed catharsis that will wash away today’s thicket of im- At the same time, there is more—and more varied—interest in perative languages, preparing the ground for a more fertile data-centric programming languages than at any time in com- declarative future? And what role might the database com- puting history, in part because these languages parallelize nat- munity play in shaping this future, having sowed the seeds of urally. This juxtaposition raises the possibility that the theory Datalog over the last quarter century? of declarative database query languages can provide a foun- Before addressing these issues directly, a few more words dation for the next generation of parallel and distributed pro- about both crisis and opportunity are in order. gramming languages. 1.1 Urgency: Parallelism In this paper I reflect on my group’s experience over seven years using Datalog extensions to build networking protocols I would be panicked if I were in industry. and distributed systems. Based on that experience, I present — John Hennessy, President, Stanford University [35] a number of theoretical conjectures that may both interest the database community, and clarify important practical issues in The need for parallelism is visible at micro and macro scales. -
Alan M. Turing – Simplification in Intelligent Computing Theory and Algorithms”
“Alan Turing Centenary Year - India Celebrations” 3-Day Faculty Development Program on “Alan M. Turing – Simplification in Intelligent Computing Theory and Algorithms” Organized by Foundation for Advancement of Education and Research In association with Computer Society of India - Division II [Software] NASSCOM, IFIP TC - 1 & TC -2, ACM India Council Co-sponsored by P.E.S Institute of Technology Venue PES Institute of Technology, Hoskerehalli, Bangalore Date : 18 - 20 December 2012 Compiled by : Prof. K. Rajanikanth Trustee, FAER “Alan Turing Centenary Year - India Celebrations” 3-Day Faculty Development Program on “Alan M. Turing – Simplification in Intelligent Computing Theory and Algorithms” Organized by Foundation for Advancement of Education and Research In association with Computer Society of India - Division II [Software], NASSCOM, IFIP TC - 1 & TC -2, ACM India Council Co-sponsored by P.E.S Institute of Technology December 18 – 20, 2012 Compiled by : Prof. K. Rajanikanth Trustee, FAER Foundation for Advancement of Education and Research G5, Swiss Complex, 33, Race Course Road, Bangalore - 560001 E-mail: [email protected] Website: www.faer.ac.in PREFACE Alan Mathison Turing was born on June 23rd 1912 in Paddington, London. Alan Turing was a brilliant original thinker. He made original and lasting contributions to several fields, from theoretical computer science to artificial intelligence, cryptography, biology, philosophy etc. He is generally considered as the father of theoretical computer science and artificial intelligence. His brilliant career came to a tragic and untimely end in June 1954. In 1945 Turing was awarded the O.B.E. for his vital contribution to the war effort. In 1951 Turing was elected a Fellow of the Royal Society. -
Copy 106 of DOC016
TURFR H1-13 by Gavin Claypool week--primarily on the ground. final period, a Morris pass was Gary Stormo carried the ball to early. With third down and 13 on Sports Editor Bisset carried fifteen times for 44 intercepted by Riverside on their the 43, and then Morris passed to the CIT 37, Edwards hit Jones with Down by four with seven minutes yards and a TD. Morton made 21. One second down, quaterback Steubs for the winning score. a pass for the six-pointer. Tormey's left, the Caltech Beavers rallied to several first downs in gaining 43 Jon Edwards found Davery Jones Three in a Row? kick was wide, leaving the score 6-0. defeat the U.c. Riverside Frosh, yards, including runs of 19 and 11 open for 37 yards to the Tech 35. The last time the Beavers won Later in the quarter, Frank 16--13, Saturday afternoon. yards that set up the field goal Two plays later, Jimmy Ardiss three in a row was in 1957, the last Hobbs recovered a Riverside fumble With 2:36 remaining in the attempt at the end of the first half. broke through the right side for the above .500 season for Tech. After deep in their territory to set up the fourth quarter, Lee Morris con Unlike the La Berne game, the go-ahead score. Mike Tormey's kick defeating U.C. Riverside (!) in the Beavers' score. Morris carried the nected with John Steubs for 43 Beavers did not lead in any made it 13-9. opener, the Techers proceeded to ball to the nine, and then hit Greg yards and the final touchdown. -
The Best Nurturers in Computer Science Research
The Best Nurturers in Computer Science Research Bharath Kumar M. Y. N. Srikant IISc-CSA-TR-2004-10 http://archive.csa.iisc.ernet.in/TR/2004/10/ Computer Science and Automation Indian Institute of Science, India October 2004 The Best Nurturers in Computer Science Research Bharath Kumar M.∗ Y. N. Srikant† Abstract The paper presents a heuristic for mining nurturers in temporally organized collaboration networks: people who facilitate the growth and success of the young ones. Specifically, this heuristic is applied to the computer science bibliographic data to find the best nurturers in computer science research. The measure of success is parameterized, and the paper demonstrates experiments and results with publication count and citations as success metrics. Rather than just the nurturer’s success, the heuristic captures the influence he has had in the indepen- dent success of the relatively young in the network. These results can hence be a useful resource to graduate students and post-doctoral can- didates. The heuristic is extended to accurately yield ranked nurturers inside a particular time period. Interestingly, there is a recognizable deviation between the rankings of the most successful researchers and the best nurturers, which although is obvious from a social perspective has not been statistically demonstrated. Keywords: Social Network Analysis, Bibliometrics, Temporal Data Mining. 1 Introduction Consider a student Arjun, who has finished his under-graduate degree in Computer Science, and is seeking a PhD degree followed by a successful career in Computer Science research. How does he choose his research advisor? He has the following options with him: 1. Look up the rankings of various universities [1], and apply to any “rea- sonably good” professor in any of the top universities. -
Learning to Code
PART ILEARNING TO CODE How Important is Programming? “To understand computers is to know about programming. The world is divided… into people who have written a program and people who have not.” Ted Nelson, Computer Lib/Dream Machines (1974) How important is it for you to learn to program a computer? Since the introduction of the first digital electronic computers in the 1940s, people have answered this question in surprisingly different ways. During the first wave of commercial computing—in the 1950s and 1960s, when 1large and expensive mainframe computers filled entire rooms—the standard advice was that only a limited number of specialists would be needed to program com- puters using simple input devices like switches, punched cards, and paper tape. Even during the so-called “golden age” of corporate computing in America—the mid- to late 1960s—it was still unclear how many programming technicians would be needed to support the rapid computerization of the nation’s business, military, and commercial operations. For a while, some experts thought that well-designed computer systems might eventually program themselves, requiring only a handful of attentive managers to keep an eye on the machines. By the late 1970s and early 1980s, however, the rapid emergence of personal computers (PCs), and continuing shortages of computer professionals, shifted popular thinking on the issue. When consumers began to adopt low-priced PCs like the Apple II (1977), the IBM PC (1981), and the Commodore 64 (1982) by the millions, it seemed obvious that ground-breaking changes were afoot. The “PC Revolution” opened up new frontiers, employed tens of thousands of people, and (according to some enthusiasts) demanded new approaches to computer literacy. -
SQL Vs Nosql
SQL vs NoSQL By: Mohammed-Ali Khan Email: [email protected] Date: October 21, 2012 YORK UNIVERSITY Agenda ● History of DBMS – why relational is most popular? ● Types of DBMS – brief overview ● Main characteristics of RDBMS ● Main characteristics of NoSQL DBMS ● SQL vs NoSQL ● DB overview – Cassandra ● Criticism of NoSQL ● Some Predictions / Conclusions History of DBMS – why relational is most popular? ● 19th century: US Government needed reports from large datasets to conduct nation-wide census. ● 1890: Herman Hollerith creates the first automatic processing equipment which allowed American census to be conducted. ● 1911: IBM founded. ● 1960s: Efforts to standardize the database technology – US DoD: Conference on Data Systems Language (Codasyl). History of DBMS – why relational is most popular? ● 1968: IBM introduced IMS DBMS (a hierarchical DBMS). ● IBM employee Edgar Codd not satisfied, quoted as saying: – “Taking the old line view, that the burden of finding information should be placed on users...” ● Edgar Codd publishes a paper “A relational Model of Data for large shared Data Banks” – Key points: Independence of data from hardware/storage implementation – High level non-procedural language for data access – Pointers/keys (primary/secondary) History of DBMS – why relational is most popular? ● 1970s: Two database projects launched based on relational model – Ingres (Department of Defence Initiative) – System R (IBM) ● Ingres had its own query language called QUEL whereas System R used SQL. ● Larry Ellison, who worked at IBM, read publications of the System R group and eventually founded ORACLE. History of DBMS – why relational is most popular? ● 1980: IBM introduced SQL for the mainframe market. ● In a nutshell, American Government's requirements had a strong role in development of the relational DBMS. -
Mount Litera Zee School Grade-VIII G.K Computer and Technology Read and Write in Notebook: 1
Mount Litera Zee School Grade-VIII G.K Computer and Technology Read and write in notebook: 1. Who is called as ‘Father of Computer’? a. Charles Babbage b. Bill Gates c. Blaise Pascal d. Mark Zuckerberg 2. Full Form of virus is? a. Visual Information Resource Under Seize b. Virtual Information Resource Under Size c. Vital Information Resource Under Seize d. Virtue Information Resource Under Seize 3. How many MB (Mega Byte) makes one GB (Giga Byte)? a. 1025 MB b. 1030 MB c. 1020 MB d. 1024 MB 4. Internet was developed in _______. a. 1973 b. 1993 c. 1983 d. 1963 5. Which was the first virus detected on ARPANET, the forerunner of the internet in the early 1970s? a. Exe Flie b. Creeper Virus c. Peeper Virus d. Trozen horse 6. Who is known as the Human Computer of India? a. Shakunthala Devi b. Nandan Nilekani c. Ajith Balakrishnan d. Manish Agarwal 7. When was the first smart phone launched? a. 1992 b. 1990 c. 1998 d. 2000 8. Which one of the following was the first search engine used? a. Google b. Archie c. AltaVista d. WAIS 9. Who is known as father of Internet? a. Alan Perlis b. Jean E. Sammet c. Vint Cerf d. Steve Lawrence 10. What us full form of GOOGLE? a. Global Orient of Oriented Group Language of Earth b. Global Organization of Oriented Group Language of Earth c. Global Orient of Oriented Group Language of Earth d. Global Oriented of Organization Group Language of Earth 11. Who developed Java Programming Language? a.