Douglas Carl Engelbart was an American engineer and inventor, an early computer and Internet pioneer. He is best known for his work on founding the field of human–computer interaction while at his Augmentation Research Center Lab in SRI International, which resulted in creation of the computer mouse, the development of hypertext, networked computers, precursors to graphical user interfaces; these were demonstrated at The Mother of All Demos in 1968. Engelbart's law, the observation that the intrinsic rate of human performance is exponential, is named after him. In the early 1950s, he decided that instead of "having a steady job" – such as his position at Ames Research Center – he would focus on making the world a better place, he reasoned that because the complexity of the world's problems was increasing, because any effort to improve the world would require the coordination of groups of people, the most effective way to solve problems was to augment human intelligence and develop ways of building collective intelligence.
He believed that the computer, at the time thought of only as a tool for automation, would be an essential tool for future knowledge workers to solve such problems. He was a committed, vocal proponent of the development and use of computers and computer networks to help cope with the world's urgent and complex problems. Engelbart embedded a set of organizing principles in his lab, which he termed "bootstrapping", his belief was that when human systems and tool systems were aligned, such that workers spent time "improving their tools for improving their tools" it would lead to an accelerating rate of progress. NLS, the "oN-Line System," developed by the Augmentation Research Center under Engelbart's guidance with funding from ARPA, demonstrated numerous technologies, most of which are now in widespread use; the lab was transferred from SRI to Tymshare in the late 1970s, acquired by McDonnell Douglas in 1984, NLS was renamed Augment. At both Tymshare and McDonnell Douglas, Engelbart was limited by a lack of interest in his ideas and funding to pursue them, retired in 1986.
In 1988, Engelbart and his daughter Christina launched the Bootstrap Institute – known as The Doug Engelbart Institute – to promote his vision at Stanford University. In December 2000, United States President Bill Clinton awarded Engelbart the National Medal of Technology, the U. S.'s highest technology award. In December 2008, Engelbart was honored by SRI at the 40th anniversary of the "Mother of All Demos". Engelbart was born in Portland, Oregon, on January 30, 1925, to Carl Louis Engelbart and Gladys Charlotte Amelia Munson Engelbart, his ancestors were of German and Norwegian descent. He was the middle of three children, with a sister Dorianne, a brother David; the family lived in Portland, Oregon, in his early years, moved to the surrounding countryside along Johnson Creek when he was 8. His father died one year later, he graduated from Portland's Franklin High School in 1942. Midway through his undergraduate years at Oregon State University, he served two years in the United States Navy as a radio and radar technician in the Philippines.
It was there on a small island, in a tiny hut on stilts, he read Vannevar Bush's article "As We May Think", which inspired him. He returned to Oregon State and completed his bachelor's degree in electrical engineering in 1948. While at Oregon State, he was a member of Sigma Phi Epsilon social fraternity, he was hired by the National Advisory Committee for Aeronautics at the Ames Research Center, where he worked in wind tunnel maintenance. In his off hours he enjoyed hiking and folk dancing, it was there he met Ballard Fish, just completing her training to become an occupational therapist. They were married in Portola State Park on May 5, 1951. Soon after, Engelbart left Ames to pursue graduate studies at the University of California, Berkeley. There, he received an M. S. in electrical engineering in 1953 and a Ph. D. in the discipline in 1955. Engelbart's career was inspired in December 1950 when he was engaged to be married and realized he had no career goals other than "a steady job, getting married and living ever after".
Over several months he reasoned that: he would focus his career on making the world a better place any serious effort to make the world better would require some kind of organized effort that harnessed the collective human intellect of all people to contribute to effective solutions. If you could improve how we do that, you'd be boosting every effort on the planet to solve important problems – the sooner the better computers could be the vehicle for improving this capability. In 1945, Engelbart had read with interest Vannevar Bush's article "As We May Think", a call to action for making knowledge available as a national peacetime grand challenge, he had read something about the recent phenomenon of computers, from his experience as a radar technician, he knew that information could be analyzed and displayed on a screen. He envisioned intellectual workers sitting at display "working stations", flying through information space, harnessing their collective intellectual capacity to solve important problems together in much more powerful ways.
Harnessing collective intellect, facilitated by interactive computers, became his life's mission at a time when computers were viewed as number c
The Torre Velasca is a skyscraper built in the 1950s by the BBPR architectural partnership, in Milan, Italy. BBPR is an acronym from the name of its designers: Gianluigi Banfi, Lodovico Barbiano di Belgiojoso, Enrico Peressutti and Ernesto Nathan Rogers. At the time of the construction of the Torre Velasca, Banfi was dead; the Velasca Tower is part of the first generation of Italian modern architecture, while still being part of the Milanese context in which it was born, to which belongs the Milan Cathedral and the Sforza Castle. The tower 100 metres tall, has a peculiar and characteristic mushroom-like shape, it stands out in the city skyline, made of domes and other towers. Its structure recalls the Lombard tradition, made of medieval fortresses and towers, each having a massive profile. In such fortresses, the lower parts were always narrower, while the higher parts propped up by wood or stone beams; as a consequence, the shape of this building is the result of a modern interpretation of the typical Italian medieval castle.
At the same time, BBPR in this building satisfied the functional needs of space: narrower surfaces on the ground and more spacious ones on the top floors. The town planning laws imposed specific volumes. In 2011, the tower was placed under protection as a historic building; the tower during construction, seen from the Duomo of Milan. Photo by Paolo Monti The tower is located in the city centre of Milan, near the Duomo and the headquarters of the University of Milan, between the streets "corso di Porta Romana" and "via Larga". One of the exits of the Missori metro station is located right in front of it. Photo by Paolo Monti List of buildings in Milan
Nikolai V. Ivanov is a Russian mathematician who works on topology and group theory, he is a professor at Michigan State University. He obtained his Ph. D. under the guidance of Vladimir Abramovich Rokhlin in 1980 at the Steklov Mathematical Institute. According to Google Scholar, on 11 March 2018, Ivanov's works had received 2,234 citations and his h-index was 23, he is a fellow of the American Mathematical Society since 2012. He is the author of the book Subgroups of Teichmüller Modular Groups. Among his contributions to mathematics are his classification of subgroups of surface mapping class groups, the establishment that surface mapping class groups satisfy the Tits alternative. "Automorphisms of complexes of curves and of Teichmuller spaces", International Mathematics Research Notices 14, pp. 651–666. With John D. McCarthy: "On injective homomorphisms between Teichmüller modular groups I", Inventiones mathematicae 135, pp. 425–486. "On the homology stability for Teichmüller modular groups: closed surfaces and twisted coefficients", Contemporary Mathematics 150, pp. 149–149.
N. V. Ivanov website Ivanov's blog
The 1983 Orange Bowl featured the Nebraska Cornhuskers and the LSU Tigers. The game suffered from poor attendance due to riots in the Miami area, as well as the game having no impact on the national championship, since #2 Penn State was playing #1 Georgia at the same time in the Sugar Bowl in New Orleans. LSU began the season 7–0–1, notching two huge road victories in Southeastern Conference play, ousting #5 Florida 24–13 in October and #4 Alabama in November; the 20–10 triumph at Birmingham's Legion Field was the Tigers' first over the Crimson Tide since 1970 and lifted LSU to No. 6 in the national polls. One week after toppling Alabama, any faint national championship hopes LSU harbored were blown away with a stunning 27-24 loss to Mississippi State in Starkville; the Tigers recovered the next week to rout Florida State 55–21 in Baton Rouge to earn an Orange Bowl berth, but they inexplicably dropped a 31–28 decision to Tulane, a 28-point underdog, at home in the regular season finale. It was the Green Wave's first victory at Tiger Stadium since 1948, is Tulane's last triumph in the series, which has not been played on a yearly basis since 1994.
Despite the November swoon, LSU came into the bowl game ranked thirteenth in the UPI polls. Nebraska was 11–1 and ranked third in both polls, but they had been denied a chance to play for the national championship due to a controversial 27–24 loss at Penn State early in the season. Nebraska forced a three and out, scored on their first possession, capped by a 5-yard touchdown run by fullback Mark Schellen to take a 7–0 lead just four minutes into the game, the favored Huskers looked as if they would put the Tigers away early, but a series of miscues turned the game on its head. Toby Williams intercepted a Tiger pass at the Husker 7, but the Huskers fumbled the ball right back to LSU on the next play from scrimmage, Dalton Hilliard scored from the 1 to tie the game at 7. Nebraska drove to the LSU 15 before fumbling again inexplicably fumbled a third time after forcing LSU to punt. Turner Gill threw an interception; the Tigers took advantage with a second Hilliard 1-yard touchdown run, Nebraska found itself trailing 14–7 at halftime after committing four turnovers on four consecutive series.
Halftime provided no relief for the mistake-prone Husker offense, with a missed field goal on the opening drive of the second half, followed by yet another fumble. LSU converted the latest Husker error into a 28-yard Juan Bentanzos field goal, which gave them a 17–7 lead. On the next series, Nebraska held on to the football and went on a 12-play, 80-yard scoring drive, capped by an 11-yard swing pass from Turner Gill to Mike Rozier which pulled the Huskers within three at 17–14. Gill finished off a 7-play, 47-yard drive with a QB sneak early in the fourth to put the Huskers ahead 21–17. Another miscue, this time a dropped pass on a fake field goal, prevented the Huskers from extending their lead. LSU got a 49-yard field goal from Bentanzos late following an interception, but they could not get the ball back again, the Cornhuskers held on to win 21–20. First quarter Nebraska - Mark Schellen 5 run LSU – Dalton Hilliard 1 run Second quarter LSU – Hilliard 1 run Third quarter LSU – Field goal, Betanzos 28 Nebraska - Mike Rozier 11 pass from Turner Gill Fourth quarter Nebraska - Gill 1 run LSU – Field goal, Betanzos 49Source: Source: http://www.huskers.com/ViewArticle.dbml?
Bayes linear statistics is a subjectivist statistical methodology and framework. Traditional subjective Bayesian analysis is based upon specified probability distributions, which are difficult to specify at the necessary level of detail. Bayes linear analysis attempts to solve this problem by developing theory and practise for using specified probability models. Bayes linear in its current form has been developed by Michael Goldstein. Mathematically and philosophically it extends Bruno de Finetti's Operational Subjective approach to probability and statistics. Consider first a traditional Bayesian Analysis where you expect to shortly know D and you would like to know more about some other observable B. In the traditional Bayesian approach it is required that every possible outcome is enumerated i.e. every possible outcome is the cross product of the partition of a set of B and D. If represented on a computer where B requires n bits and D m bits the number of states required is 2 n + m; the first step to such an analysis is to determine a persons subjective probabilities e.g. by asking about their betting behaviour for each of these outcomes.
When we learn D conditional probabilities for B are determined by the application of Bayes' rule. Practitioners of subjective Bayesian statistics analyse datasets where the size of this set is large enough that subjective probabilities cannot be meaningfully determined for every element of D × B; this is accomplished by assuming exchangeability and the use of parameterized models with prior distributions over parameters and appealing to the de Finetti's theorem to justify that this produces valid operational subjective probabilities over D × B. The difficulty with such an approach is that the validity of the statistical analysis requires that the subjective probabilities are a good representation of an individual's beliefs however this method results in a precise specification over D × B and it is difficult to articulate what it would mean to adopt these belief specifications. In contrast to the traditional Bayesian paradigm Bayes linear statistics following de Finetti uses Prevision or subjective expectation as a primitive, probability is defined as the expectation of an indicator variable.
Instead of specifying a subjective probability for every element in the partition D × B the analyst specifies subjective expectations for just a few quantities that they are interested in or feel knowledgeable about. Instead of conditioning an adjusted expectation is computed by a rule, a generalization of Bayes' rule, based upon expectation; the use of the word linear in the title refers to de Finetti's arguments that probability theory is a linear theory. In Bayes linear statistics, the probability model is only specified, it is not possible to calculate conditional probability by Bayes' rule. Instead Bayes linear suggests the calculation of an Adjusted Expectation. To conduct a Bayes linear analysis it is necessary to identify some values that you expect to know shortly by making measurements D and some future value which you would like to know B. Here D refers to a vector containing data and B to a vector containing quantities you would like to predict. For the following example B and D are taken to be two-dimensional vectors i.e.
B =, D =. In order to specify a Bayes linear model it is necessary to supply expectations for the vectors B and D, to specify the correlation between each component of B and each component of D. For example the expectations are specified as: E = 5, E = 3, E = 5, E = 3 and the covariance matrix is specified as: X 1 X 2 Y 1 Y 2 X 1 1 u γ γ X 2 u 1 γ γ Y 1 γ γ 1 v Y 2 γ γ v 1; the repetition in this matrix, has some interesting implications to be discussed shortly. An adjusted expectation is a linear estimator of the form c 0 + c 1 X 1 + c 2 X 2 where c 0, c 1 and c 2 are chosen to minimise the prior expected loss for the observations i.e. Y
Taupo-nui-a-Tia College is a co-educational high school in Taupo, New Zealand. The school has about 1050 students. Taupo-nui-a-Tia College is a Cornerstone Values school. Taupo-nui-a-Tia College is ranked as one of the top performing schools in the central North Island, with NCEA results being above the national average for a decile 5 school; this school achieved steady results in the 2011 New Zealand Scholarship exams in Economics where 2 outstanding scholarships were gained. Taupo-nui-a-Tia College is held in high regard for its tradition of sporting achievement from many young sportsmen and sportswomen within the school. There is an impressive line-up of national achievers and some students, have gone on to represent their country on the world stage with their chosen sport. There are over 30 different sports codes in the school; the top performing sportsmen and sportswomen are invited to join the High Performance Programme, in order to aid them in their sporting careers. Taupo-nui-a-Tia College is renowned for its strength in the performing arts field, with NCEA Subjects in Music and Dance.
In 2011, the school reached the national finals of Stage Challenge. Recent productions in the school include High School Musical and Little Shop of Horrors; the college has many different music groups, including an a cappella group, Performing Arts Club, TNT Jazz band and a combined schools Wind Band for young musicians around Taupo. Able music students are invited to join the High Performance Music Extension Programme, in order to receive further tuition in their desired instrument. In 2011, the rebuilding of a new school gym was completed, it has a 21st-century touch, complete with a Dance Studio, larger gym arena and newer changing rooms. In 2012, the new Design and Innovation technology centre was opened by Prime Minister John Key; this building is two stories high, with state of the art 21st century type classrooms, Two commercial kitchens, specialist computer suites, an elevator. John Key stated that this building will be a major forefront in the innovation of newer school buildings around New Zealand.
Tauhara Ngauruhoe Ruapehu Tongariro Paula Bennett - 18th Deputy Prime Minister of New Zealand David Hamilton - New Zealand Composer Louisa Wall - Member of Parliament Lee Stensness - All Black Hud Rickit - All Black Shiloh Gloyn - Black Stick Nicole van der Kaay - Triathlete Mani Mitchell - Activist Taupo-nui-a-Tia College