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1 production
production [pʀɔdyksjɔ̃]feminine noun* * *pʀɔdyksjɔ̃1) ( fait de produire) ( de produit) production; ( d'énergie) generationla production du nouveau modèle débutera le mois prochain — the new model will go into production next month
2) ( produits) gén products (pl), goods (pl); ( produits agricoles) produce [U]3) ( quantités produites) (de produits agricoles, matières premières) production; (de produits manufacturés, d'énergie) output, production4) ( dans une entreprise)5) Cinéma, Télévision (processus, film) production6) ( d'auteur) ( ouvrage) work; ( ensemble de l'œuvre) works (pl)7) ( présentation) presentation•Phrasal Verbs:* * *pʀɔdyksjɔ̃ nf1) (industrielle, agricole) production2) [usine] output3) (= œuvres) works pl* * *production nf1 ( fait de produire) (de marchandise, produit agricole, d'objet) production; ( d'électricité) production, generation; ( d'énergie) generation; mise en production putting into production; la production du nouveau modèle débutera le mois prochain the new model will go into production next month; arrêter la production d'un modèle to stop producing a model; la production d'anticorps/d'enzymes par l'organisme the production of antibodies/of enzymes by the body;3 ( quantités produites) (de produits agricoles, matières premières) production; (de produits manufacturés, d'énergie) output, production; la production de café a chuté coffee production has fallen; augmenter la production de pétrole to increase oil production; la production de notre entreprise s'élève à 5 millions de machines par an our firm's output is 5 million machines per year; le pays exporte 30% de sa production agricole the country exports 30% of its agricultural production; chiffres de la production production figures;4 ( dans une entreprise) (service de) la production production; directeur de la production production manager; il est à la production maintenant he is in production now;5 Cin, TV (processus, film) production; directeur de production production manager; production à grand spectacle spectacular;6 (d'écrivain, auteur) ( ouvrage) work; ( ensemble de l'œuvre) works (pl), output; production littéraire literary output; toute la production d'un auteur an author's complete works; la production dramatique du XIXe siècle 19th-century drama;7 ( présentation) Jur, Admin presentation; sur production de votre carte on presentation of your card.production assistée par ordinateur, PAO computer-aided manufacturing, CAM.[prɔdyksjɔ̃] nom féminin1. [activité économique]la production a augmenté/diminuéa. INDUSTRIE output has risen/droppedb. AGRICULTURE the yield is higher/lowerl'usine a une production de 10 000 voitures par an the factory turns out ou produces 10,000 cars a year3. [produits, AGRICULTURE] produce (substantif non comptable), production (substantif non comptable)le pays veut écouler sa production de maïs the country wants to sell off its maize crop ou the maize it has producedassistant/directeur de production production assistant/manager6. [œuvres]la production dramatique/romanesque du XVIIIe siècle 18th-century plays/novels7. [présentation] presentation9. TECHNOLOGIE -
2 Norton, Charles Hotchkiss
SUBJECT AREA: Mechanical, pneumatic and hydraulic engineering[br]b. 23 November 1851 Plainville, Connecticut, USAd. 27 October 1942 Plainville, Connecticut, USA[br]American mechanical engineer and machine-tool designer.[br]After an elementary education at the public schools of Plainville and Thomaston, Connecticut, Charles H.Norton started work in 1866 at the Seth Thomas Clock Company in Thomaston. He was soon promoted to machinist, and further progress led to his successive appointments as Foreman, Superintendent of Machinery and Manager of the department making tower clocks. He designed many public clocks.In 1886 he obtained a position as Assistant Engineer with the Brown \& Sharpe Manufacturing Company at Providence, Rhode Island, and was engaged in redesigning their universal grinding machine to give it more rigidity and make it more suitable for use as a production machine. In 1890 he left to become a partner in a newly established firm, Leland, Faulconer \& Norton Company at Detroit, Michigan, designing and building machine tools. He withdrew from this firm in 1895 and practised as a consulting mechanical engineer for a short time before returning to Brown \& Sharpe in 1896. There he designed a grinding machine incorporating larger and wider grinding wheels so that heavier cuts could be made to meet the needs of the mass-production industries, especially the automobile industry. This required a heavier and more rigid machine and greater power, but these ideas were not welcomed at Brown \& Sharpe and in 1900 Norton left to found the Norton Grinding Company in Worcester, Massachusetts. Here he was able to develop heavy-production grinding machines, including special machines for grinding crank-shafts and camshafts for the automobile industry.In setting up the Norton Grinding Company, Charles H.Norton received financial support from members of the Norton Emery Wheel Company (also of Worcester and known after 1906 as the Norton Company), but he was not related to the founder of that company. The two firms were completely independent until 1919 when they were merged. From that time Charles H.Norton served as Chief Engineer of the machinery division of the Norton Company, until 1934 when he became their Consulting Engineer.[br]Principal Honours and DistinctionsCity of Philadelphia, John Scott Medal 1925.BibliographyNorton was granted more than one hundred patents and was author of Principles of Cylindrical Grinding, 1917, 1921, Worcester, Mass.Further ReadingRobert S.Woodbury, 1959, History of the Grinding Machine, Cambridge, Mass, (contains biographical information and details of the machines designed by Norton).RTSBiographical history of technology > Norton, Charles Hotchkiss
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3 производство
с.1. production, manufacture2. (выполнение, совершение) execution3. разг. (фабрика, завод) factory; worksидти на производство — go* to work at a factory
4. воен. ( присвоение звания) promotion -
4 производство
с.1) ( изготовление какой-л продукции) production, manufactureпроизво́дство маши́н — production of machines
произво́дство о́буви — manufacture of shoes
маши́нное произво́дство — mechanical [-'kæn-] production
пото́чное произво́дство — line production
сре́дства произво́дства — means of production
произво́дство средств произво́дства — production of means of production
произво́дство предме́тов потребле́ния — production of consumer goods
произво́дство материа́льных благ — production of material values
спо́соб произво́дства — mode of production
изде́ржки произво́дства — the cost of production sg
2) (выполнение, совершение) executionпроизво́дство платеже́й — effecting of payment
произво́дство о́пытов — experimentation
произво́дство вы́стрела воен. — firing of a shot
3) разг. (фабрика, завод) factory; worksидти́ на произво́дство — go to work at a factory
4) воен. ( присвоение звания) promotion (to or to the rank of)произво́дство в майо́ры — promotion to major sg
5) ( судебное) processпрекрати́ть де́ло произво́дством, прекрати́ть произво́дство по де́лу юр. — dismiss a case
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5 производственное оборудование
production equipment, manufacturing facilities, production facilities, process machinesРусско-английский исловарь по машиностроению и автоматизации производства > производственное оборудование
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6 составлять до
•Production speeds of such machines range up to 600 parts per minute.
Русско-английский научно-технический словарь переводчика > составлять до
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7 применяемость механизмов
Production: where-used machinesУниверсальный русско-английский словарь > применяемость механизмов
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8 производство станков
Русско-английский синонимический словарь > производство станков
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9 Clark, Edward
SUBJECT AREA: Domestic appliances and interiors[br]fl. 1850s New York State, USA[br]American co-developer of mass-production techniques at the Singer sewing machine factory.[br]Born in upstate New York, where his father was a small manufacturer, Edward Clark attended college at Williams and graduated in 1831. He became a lawyer in New York City and from then on lived either in the city or on his rural estate near Cooperstown in upstate New York. After a series of share manipulations, Clark acquired a one-third interest in Isaac M. Singer's company. They soon bought out one of Singer's earlier partners, G.B.Zeiber, and in 1851, under the name of I.M.Singer \& Co., they set up a permanent sewing machine business with headquarters in New York.The success of their firm initially rested on marketing. Clark introduced door-to-door sales-people and hire-purchase for their sewing machines in 1856 ($50 cash down, or $100 with a cash payment of $5 and $3 a month thereafter). He also trained women to demonstrate to potential customers the capabilities of the Singer sewing machine. At first their sewing machines continued to be made in the traditional way, with the parts fitted together by skilled workers through hand filing and shaping so that the parts would fit only onto one machine. This resembled European practice rather than the American system of manufacture that had been pioneered in the armouries in that country. In 1856 Singer brought out their first machine intended exclusively for home use, and at the same time manufacturing capacity was improved. Through increased sales, a new factory was built in 1858–9 on Mott Street, New York, but it soon became inadequate to meet demand.In 1863 the Singer company was incorporated as the Singer Manufacturing Co. and began to modernize its production methods with special jigs and fixtures to help ensure uniformity. More and more specialized machinery was built for making the parts. By 1880 the factory, then at Elizabethport, New Jersey, was jammed with automatic and semi-automatic machine tools. In 1882 the factory was producing sewing machines with fully interchangeable parts that did not require hand fitting in assembly. Production rose from 810 machines in 1853 to half a million in 1880. A new family model was introduced in 1881. Clark had succeeded Singer, who died in 1875, as President of the company, but he retired in 1882 after he had seen through the change to mass production.[br]Further ReadingNational Cyclopaedia of American Biography.D.A.Hounshell, 1984, From the American System to Mass Production, 1800–1932. The Development of Manufacturing Technology in the United States, Baltimore (a thorough account of Clark's role in the development of Singer's factories).F.B.Jewell, 1975, Veteran Sewing Machines. A Collector's Guide, Newton Abbot.RLH -
10 Singer, Isaac Merritt
[br]b. 27 October 1811 Pittstown, New York, USAd. 23 July 1875 Torquay, Devonshire, England[br]American inventor of a sewing machine, and pioneer of mass production.[br]The son of a millwright, Singer was employed as an unskilled labourer at the age of 12, but later gained wide experience as a travelling machinist. He also found employment as an actor. On 16 May 1839, while living at Lockport, Illinois, he obtained his first patent for a rock-drilling machine, but he soon squandered the money he made. Then in 1849, while at Pittsburgh, he secured a patent for a wood-and metal-carving machine that he had begun five years previously; however, a boiler explosion in the factory destroyed his machine and left him penniless.Near the end of 1850 Singer was engaged to redesign the Lerow \& Blodgett sewing machine at the Boston shop of Orson C.Phelps, where the machine was being repaired. He built an improved version in eleven days that was sufficiently different for him to patent on 12 August 1851. He formed a partnership with Phelps and G.B. Zieber and they began to market the invention. Singer soon purchased Phelps's interest, although Phelps continued to manufacture the machines. Then Edward Clark acquired a one-third interest and with Singer bought out Zieber. These two, with dark's flair for promotion and marketing, began to create a company which eventually would become the largest manufacturer of sewing machines exported worldwide, with subsidiary factories in England.However, first Singer had to defend his patent, which was challenged by an earlier Boston inventor, Elias Howe. Although after a long lawsuit Singer had to pay royalties, it was the Singer machine which eventually captured the market because it could do continuous stitching. In 1856 the Great Sewing Machine Combination, the first important pooling arrangement in American history, was formed to share the various patents so that machines could be built without infringements and manufacture could be expanded without fear of litigation. Singer contributed his monopoly on the needle-bar cam with his 1851 patent. He secured twenty additional patents, so that his original straight-needle vertical design for lock-stitching eventually included such refinements as a continuous wheel-feed, yielding presser-foot, and improved cam for moving the needle-bar. A new model, introduced in 1856, was the first to be intended solely for use in the home.Initially Phelps made all the machines for Singer. Then a works was established in New York where the parts were assembled by skilled workers through filing and fitting. Each machine was therefore a "one-off" but Singer machines were always advertised as the best on the market and sold at correspondingly high prices. Gradually, more specialized machine tools were acquired, but it was not until long after Singer had retired to Europe in 1863 that Clark made the change to mass production. Sales of machines numbered 810 in 1853 and 21,000 ten years later.[br]Bibliography12 August 1851, US patent no. 8,294 (sewing machine)Further ReadingBiographies and obituaries have appeared in Appleton's Cyclopedia of America, Vol. V; Dictionary of American Biography, Vol XVII; New York Times 25 July 1875; Scientific American (1875) 33; and National Cyclopaedia of American Biography.D.A.Hounshell, 1984, From the American System to Mass Production 1800–1932. TheDevelopment of Manufacturing Technology in the United States, Baltimore (provides a thorough account of the development of the Singer sewing machine, the competition it faced from other manufacturers and production methods).RLH -
11 McKay, Hugh Victor
SUBJECT AREA: Agricultural and food technology[br]b. c. 1866 Drummartin, Victoria, Australiad. 21 May 1926 Australia[br]Australian inventor and manufacturer of harvesting and other agricultural equipment.[br]A farmer's son, at the age of 17 McKay developed modifications to the existing stripper harvester and created a machine that would not only strip the seed from standing corn, but was able to produce a threshed, winnowed and clean sample in one operation. The prototype was produced in 1884 and worked well on the two acres of wheat that had been set aside on the family farm. By arrangement with a Melbourne plough maker, five machines were made and sold for the 1885 season. In 1886 the McKay Harvester Company was formed, with offices at Ballarat, from which the machines, built by various companies, were sold. The business expanded quickly, selling sixty machines in 1888, and eventually rising to the production of nearly 2,000 harvesters in 1905. The name "Sunshine" was given to the harvester, and the "Sun" prefix was to appear on all other implements produced by the company as it diversified its production interests. In 1902 severe drought reduced machinery sales and left 2,000 harvesters unsold. McKay was forced to look to export markets to dispose of his surplus machines. By 1914 a total of 10,000 machines were being exported annually. During the First World War McKay was appointed to the Business Board of the Defence Department. Increases in the scale of production resulted in the company moving to Melbourne, where it was close to the port of entry of raw materials and was able to export the finished article more readily. In 1909 McKay produced one of the first gas-engined harvesters, but its cost prevented it from being more than an experimental prototype. By this time McKay was the largest agricultural machinery manufacturer in the Southern hemisphere, producing a wide range of implements, including binders. In 1916 McKay hired Headlie Taylor, who had developed a machine capable of harvesting fallen crops. The jointly developed machine was a major success, coming as it did in what would otherwise have been a disastrous Australian harvest. Further developments included the "Sun Auto-header" in 1923, the first of the harvesting machines to adopt the "T" configuration to be seen on modern harvesters. The Australian market was expanding fast and a keen rivalry developed between McKay and Massey Harris. Confronted by the tariff regulations with which the Australian Government had protected its indigenous machinery industry since 1906, Massey Harris sold all its Australian assets to the H.V. McKay company in 1930. Twenty-three years later Massey Ferguson acquired the old Sunshine works and was still operating from there in the 1990s.Despite a long-running history of wage disputes with his workforce, McKay established a retiring fund as well as a self-help fund for distressed cases. Before his death he created a charitable trust and requested that some funds should be made available for the "aerial experiments" which were to lead to the establishment of the Flying Doctor Service.[br]Principal Honours and DistinctionsCBE.Further ReadingGraeme Quick and Wesley Buchele, 1978, The Grain Harvesters, American Society of Agricultural Engineers (devotes a chapter to the unique development of harvesting machinery which took place in Australia).AP -
12 alzadora
= collator, gathering machine.Ex. We'll be able to purchase equipment we've been wanting for ages: an electronic offset printer; collators and folding machines and other graphic production-related paraphernalia.Ex. Machines were developed for carrying out these remaining processes between 1856 and 1903, all of them American in origin: case-making machines (1891-5); gathering machines (1900-3); and casing-in machines (1903).* * *= collator, gathering machine.Ex: We'll be able to purchase equipment we've been wanting for ages: an electronic offset printer; collators and folding machines and other graphic production-related paraphernalia.
Ex: Machines were developed for carrying out these remaining processes between 1856 and 1903, all of them American in origin: case-making machines (1891-5); gathering machines (1900-3); and casing-in machines (1903). -
13 autonomation
Opsa production system in which workers are allowed, and machines are equipped with a mechanism, to stop production if a defect in a product is detected during the production process. Autonomation became known through the Toyota production system. The concept evolved from braking devices on machines that automatically stop if a problem occurs. Within Toyota, the concept has been carried forward so that all machines are equipped with various safety devices to prevent defective products, and production workers are allowed to stop the production line if a problem occurs. The problem is then properly explored in order to find a solution and to ensure that everyone understands the underlying reasons for the problem. In the long term, this creates a more efficient production line. -
14 chaîne
chaîne° [∫εn]1. feminine nouna. (de métal) chainb. ( = ensemble, suite) chain ; [de montagnes] range• sur la première/deuxième chaîne on the first/second channel2. compounds► chaîne payante or à péage pay TV channel* * *ʃɛn
1.
1) ( entrave) chain2) ( de transmission) chain3) Industrie assembly lineon n'est pas à la chaîne! — (colloq) fig we're not machines, you know!
4) ( bijou) chain5) ( succession) chain6) ( organisation) network7) Géographie chain, range8) ( de télévision) channel9) Commerce chain10) Audio system11) Chimie chain
2.
chaînes nom féminin pluriel Automobile snow chainsPhrasal Verbs:* * *ʃɛn1. nf1) (pour lier, décorer) chainfaire la chaîne — to form a human chain, to form a chain
2) TV channel3) (stéréo) hi-fi system4) INFORMATIQUE string5) (= enchaînement)6) (montagneuse) range2. chaînes nfpl(= liens, asservissement) chains, shackles* * *A nf1 ( entrave) chain; mettre les chaînes à qn to put sb in chains; attacher qn avec des chaînes to chain sb up; attacher son chien à une chaîne to put one's dog on a chain; briser ses chaînes to cast off one's chains;2 Mécan chain; chaîne de transmission/de vélo transmission/bicycle chain; chaîne de sécurité safety chain;3 Ind assembly line; être/travailler à la chaîne to be/to work on the assembly line; produire (qch) à la chaîne to mass-produce (sth); production à la chaîne mass production; on n'est pas à la chaîne○! fig we're not machines, you know!; système éducatif à la chaîne conveyor-belt education system;5 ( succession) chain; des catastrophes en chaîne a series of disasters; réaction en chaîne chain reaction;7 Géog chain, range; chaîne de montagnes/des Pyrénées mountain/Pyrenean chain;8 ( de télévision) channel; chaîne de télévision television channel; deuxième chaîne channel 2; chaîne câblée/musicale/publique cable/music/public channel;10 Audio ( système) chaîne hi-fi hi-fi system; chaîne stéréo stereo system; chaîne compacte music centre;11 Chimie chain; chaîne moléculaire molecular chain;12 Tex warp.chaîne alimentaire food chain; chaîne d'arpenteur surveyor's chain; chaîne d'assemblage assembly line; chaîne de caractères character string; chaîne de commandement chain of command; chaîne éditoriale editorial process; chaîne de fabrication Ind production line; chaîne du froid cold chain; chaîne de montage Ind assembly line; chaîne nerveuse Anat sympathetic chain; chaîne des osselets Anat (chain of) bonelets; chaîne parlée Ling speech chain; chaîne de survie Méd chain of survival; chaîne thématique special interest channel.ⓘ Chaînes de télévision In all, France has 6 terrestrial TV channels. There are two state-owned channels, France 2 and France 3 where programmes are financed mostly by revenue from the TV licences paid by all TV owners, as well as four privately-owned channels. These are TF1 (télévision française 1) which has an obligation to ensure that 50% of its programmes are of French origin; Canal Plus, a subscription-operated channel which requires the use of a decoder except during brief periods when programmes are not scrambled (i.e. when they are broadcast en clair); la Cinquième (an educational channel) and Arte (a Franco-German cultural channel) which broadcast programmes on the same frequency but at different times of the day; and finally M6, a popular commercial channel.[ʃɛn] nom féminin1. [attache, bijou] chaina. [sur un bijou] safety chainb. [sur une porte] (door) chain4. AUDIO6. INDUSTRIEchaîne de montage/fabrication assembly/production linechaîne vide/de caractères nul/character string————————chaînes nom féminin pluriel————————à la chaîne locution adjectivale————————à la chaîne locution adverbiale[travailler, produire] on the production line————————en chaîne locution adjectivale -
15 Howe, Elias
[br]b. 9 July 1819 Spencer, Massachusetts, USAd. 3 October 1867 Bridgeport, Connecticut, USA[br]American inventor of one of the earliest successful sewing machines.[br]Son of Elias Howe, a farmer, he acquired his mechanical knowledge in his father's mill. He left school at 12 years of age and was apprenticed for two years in a machine shop in Lowell, Massachusetts, and later to an instrument maker, Ari Davis in Boston, Massachusetts, where his master's services were much in demand by Harvard University. Fired by a desire to invent a sewing machine, he utilized the experience gained in Lowell to devise a shuttle carrying a lower thread and a needle carrying an upper thread to make lock-stitch in straight lines. His attempts were so rewarding that he left his job and was sustained first by his father and then by a partner. By 1845 he had built a machine that worked at 250 stitches per minute, and the following year he patented an improved machine. The invention of the sewing machine had an enormous impact on the textile industry, stimulating demand for cloth because making up garments became so much quicker. The sewing machine was one of the first mass-produced consumer durables and was essentially an American invention. William Thomas, a London manufacturer of shoes, umbrellas and corsets, secured the British rights and persuaded Howe to come to England to apply it to the making of shoes. This Howe did, but he quarrelled with Thomas after less than one year. He returned to America to face with his partner, G.W.Bliss, a bigger fight over his patent (see I.M. Singer), which was being widely infringed. Not until 1854 was the case settled in his favour. This litigation threatened the very existence of the new industry, but the Great Sewing Machine Combination, the first important patent-pooling arrangement in American history, changed all this. For a fee of $5 on every domestically-sold machine and $1 on every exported one, Howe contributed to the pool his patent of 1846 for a grooved eye-pointed needle used in conjunction with a lock-stitch-forming shuttle. Howe's patent was renewed in 1861; he organized and equipped a regiment during the Civil War with the royalties. When the war ended he founded the Howe Machine Company of Bridgeport, Connecticut.[br]Further ReadingObituary, 1867, Engineer 24.Obituary, 1867, Practical Magazine 5.F.G.Harrison, 1892–3, Biographical Sketches of Pre-eminent Americans (provides a good account of Howe's life and achievements).N.Salmon, 1863, History of the Sewing Machine from the Year 1750, with a biography of Elias Howe, London (tells the history of sewing machines).F.B.Jewell, 1975, Veteran Sewing Machines, A Collector's Guide, Newton Abbot (a more modern account of the history of sewing machines).C.Singer (ed.), 1958, A History of Technology, Vol. V, Oxford: Clarendon Press (covers the mechanical developments).D.A.Hounshell, 1984, From the American System to Mass Production 1800–1932. TheDevelopment of Manufacturing Technology in the United States, Baltimore (examines the role of the American sewing machine companies in the development of mass-production techniques).RLH -
16 prensa offset
f.offset press.* * *(n.) = offset printer, offset printing press, offsetEx. We'll be able to purchase equipment we've been wanting for ages: an electronic offset printer; collators and folding machines and other graphic production-related paraphernalia.Ex. Appreciative of his efforts, Crane purchased a sophisticated offset printing press and other hardware for the production of library booklists, flyers, programs, etc..Ex. Libarians were sent differing sets of questionnaires where half were typed and then reproduced by ditto and half were reproduced by offset.* * *(n.) = offset printer, offset printing press, offsetEx: We'll be able to purchase equipment we've been wanting for ages: an electronic offset printer; collators and folding machines and other graphic production-related paraphernalia.
Ex: Appreciative of his efforts, Crane purchased a sophisticated offset printing press and other hardware for the production of library booklists, flyers, programs, etc..Ex: Libarians were sent differing sets of questionnaires where half were typed and then reproduced by ditto and half were reproduced by offset. -
17 relacionado con la producción
(adj.) = production-relatedEx. We'll be able to purchase equipment we've been wanting for ages: an electronic offset printer; collators and folding machines and other graphic production-related paraphernalia.* * *(adj.) = production-relatedEx: We'll be able to purchase equipment we've been wanting for ages: an electronic offset printer; collators and folding machines and other graphic production-related paraphernalia.
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18 Artificial Intelligence
In my opinion, none of [these programs] does even remote justice to the complexity of human mental processes. Unlike men, "artificially intelligent" programs tend to be single minded, undistractable, and unemotional. (Neisser, 1967, p. 9)Future progress in [artificial intelligence] will depend on the development of both practical and theoretical knowledge.... As regards theoretical knowledge, some have sought a unified theory of artificial intelligence. My view is that artificial intelligence is (or soon will be) an engineering discipline since its primary goal is to build things. (Nilsson, 1971, pp. vii-viii)Most workers in AI [artificial intelligence] research and in related fields confess to a pronounced feeling of disappointment in what has been achieved in the last 25 years. Workers entered the field around 1950, and even around 1960, with high hopes that are very far from being realized in 1972. In no part of the field have the discoveries made so far produced the major impact that was then promised.... In the meantime, claims and predictions regarding the potential results of AI research had been publicized which went even farther than the expectations of the majority of workers in the field, whose embarrassments have been added to by the lamentable failure of such inflated predictions....When able and respected scientists write in letters to the present author that AI, the major goal of computing science, represents "another step in the general process of evolution"; that possibilities in the 1980s include an all-purpose intelligence on a human-scale knowledge base; that awe-inspiring possibilities suggest themselves based on machine intelligence exceeding human intelligence by the year 2000 [one has the right to be skeptical]. (Lighthill, 1972, p. 17)4) Just as Astronomy Succeeded Astrology, the Discovery of Intellectual Processes in Machines Should Lead to a Science, EventuallyJust as astronomy succeeded astrology, following Kepler's discovery of planetary regularities, the discoveries of these many principles in empirical explorations on intellectual processes in machines should lead to a science, eventually. (Minsky & Papert, 1973, p. 11)5) Problems in Machine Intelligence Arise Because Things Obvious to Any Person Are Not Represented in the ProgramMany problems arise in experiments on machine intelligence because things obvious to any person are not represented in any program. One can pull with a string, but one cannot push with one.... Simple facts like these caused serious problems when Charniak attempted to extend Bobrow's "Student" program to more realistic applications, and they have not been faced up to until now. (Minsky & Papert, 1973, p. 77)What do we mean by [a symbolic] "description"? We do not mean to suggest that our descriptions must be made of strings of ordinary language words (although they might be). The simplest kind of description is a structure in which some features of a situation are represented by single ("primitive") symbols, and relations between those features are represented by other symbols-or by other features of the way the description is put together. (Minsky & Papert, 1973, p. 11)[AI is] the use of computer programs and programming techniques to cast light on the principles of intelligence in general and human thought in particular. (Boden, 1977, p. 5)The word you look for and hardly ever see in the early AI literature is the word knowledge. They didn't believe you have to know anything, you could always rework it all.... In fact 1967 is the turning point in my mind when there was enough feeling that the old ideas of general principles had to go.... I came up with an argument for what I called the primacy of expertise, and at the time I called the other guys the generalists. (Moses, quoted in McCorduck, 1979, pp. 228-229)9) Artificial Intelligence Is Psychology in a Particularly Pure and Abstract FormThe basic idea of cognitive science is that intelligent beings are semantic engines-in other words, automatic formal systems with interpretations under which they consistently make sense. We can now see why this includes psychology and artificial intelligence on a more or less equal footing: people and intelligent computers (if and when there are any) turn out to be merely different manifestations of the same underlying phenomenon. Moreover, with universal hardware, any semantic engine can in principle be formally imitated by a computer if only the right program can be found. And that will guarantee semantic imitation as well, since (given the appropriate formal behavior) the semantics is "taking care of itself" anyway. Thus we also see why, from this perspective, artificial intelligence can be regarded as psychology in a particularly pure and abstract form. The same fundamental structures are under investigation, but in AI, all the relevant parameters are under direct experimental control (in the programming), without any messy physiology or ethics to get in the way. (Haugeland, 1981b, p. 31)There are many different kinds of reasoning one might imagine:Formal reasoning involves the syntactic manipulation of data structures to deduce new ones following prespecified rules of inference. Mathematical logic is the archetypical formal representation. Procedural reasoning uses simulation to answer questions and solve problems. When we use a program to answer What is the sum of 3 and 4? it uses, or "runs," a procedural model of arithmetic. Reasoning by analogy seems to be a very natural mode of thought for humans but, so far, difficult to accomplish in AI programs. The idea is that when you ask the question Can robins fly? the system might reason that "robins are like sparrows, and I know that sparrows can fly, so robins probably can fly."Generalization and abstraction are also natural reasoning process for humans that are difficult to pin down well enough to implement in a program. If one knows that Robins have wings, that Sparrows have wings, and that Blue jays have wings, eventually one will believe that All birds have wings. This capability may be at the core of most human learning, but it has not yet become a useful technique in AI.... Meta- level reasoning is demonstrated by the way one answers the question What is Paul Newman's telephone number? You might reason that "if I knew Paul Newman's number, I would know that I knew it, because it is a notable fact." This involves using "knowledge about what you know," in particular, about the extent of your knowledge and about the importance of certain facts. Recent research in psychology and AI indicates that meta-level reasoning may play a central role in human cognitive processing. (Barr & Feigenbaum, 1981, pp. 146-147)Suffice it to say that programs already exist that can do things-or, at the very least, appear to be beginning to do things-which ill-informed critics have asserted a priori to be impossible. Examples include: perceiving in a holistic as opposed to an atomistic way; using language creatively; translating sensibly from one language to another by way of a language-neutral semantic representation; planning acts in a broad and sketchy fashion, the details being decided only in execution; distinguishing between different species of emotional reaction according to the psychological context of the subject. (Boden, 1981, p. 33)Can the synthesis of Man and Machine ever be stable, or will the purely organic component become such a hindrance that it has to be discarded? If this eventually happens-and I have... good reasons for thinking that it must-we have nothing to regret and certainly nothing to fear. (Clarke, 1984, p. 243)The thesis of GOFAI... is not that the processes underlying intelligence can be described symbolically... but that they are symbolic. (Haugeland, 1985, p. 113)14) Artificial Intelligence Provides a Useful Approach to Psychological and Psychiatric Theory FormationIt is all very well formulating psychological and psychiatric theories verbally but, when using natural language (even technical jargon), it is difficult to recognise when a theory is complete; oversights are all too easily made, gaps too readily left. This is a point which is generally recognised to be true and it is for precisely this reason that the behavioural sciences attempt to follow the natural sciences in using "classical" mathematics as a more rigorous descriptive language. However, it is an unfortunate fact that, with a few notable exceptions, there has been a marked lack of success in this application. It is my belief that a different approach-a different mathematics-is needed, and that AI provides just this approach. (Hand, quoted in Hand, 1985, pp. 6-7)We might distinguish among four kinds of AI.Research of this kind involves building and programming computers to perform tasks which, to paraphrase Marvin Minsky, would require intelligence if they were done by us. Researchers in nonpsychological AI make no claims whatsoever about the psychological realism of their programs or the devices they build, that is, about whether or not computers perform tasks as humans do.Research here is guided by the view that the computer is a useful tool in the study of mind. In particular, we can write computer programs or build devices that simulate alleged psychological processes in humans and then test our predictions about how the alleged processes work. We can weave these programs and devices together with other programs and devices that simulate different alleged mental processes and thereby test the degree to which the AI system as a whole simulates human mentality. According to weak psychological AI, working with computer models is a way of refining and testing hypotheses about processes that are allegedly realized in human minds.... According to this view, our minds are computers and therefore can be duplicated by other computers. Sherry Turkle writes that the "real ambition is of mythic proportions, making a general purpose intelligence, a mind." (Turkle, 1984, p. 240) The authors of a major text announce that "the ultimate goal of AI research is to build a person or, more humbly, an animal." (Charniak & McDermott, 1985, p. 7)Research in this field, like strong psychological AI, takes seriously the functionalist view that mentality can be realized in many different types of physical devices. Suprapsychological AI, however, accuses strong psychological AI of being chauvinisticof being only interested in human intelligence! Suprapsychological AI claims to be interested in all the conceivable ways intelligence can be realized. (Flanagan, 1991, pp. 241-242)16) Determination of Relevance of Rules in Particular ContextsEven if the [rules] were stored in a context-free form the computer still couldn't use them. To do that the computer requires rules enabling it to draw on just those [ rules] which are relevant in each particular context. Determination of relevance will have to be based on further facts and rules, but the question will again arise as to which facts and rules are relevant for making each particular determination. One could always invoke further facts and rules to answer this question, but of course these must be only the relevant ones. And so it goes. It seems that AI workers will never be able to get started here unless they can settle the problem of relevance beforehand by cataloguing types of context and listing just those facts which are relevant in each. (Dreyfus & Dreyfus, 1986, p. 80)Perhaps the single most important idea to artificial intelligence is that there is no fundamental difference between form and content, that meaning can be captured in a set of symbols such as a semantic net. (G. Johnson, 1986, p. 250)Artificial intelligence is based on the assumption that the mind can be described as some kind of formal system manipulating symbols that stand for things in the world. Thus it doesn't matter what the brain is made of, or what it uses for tokens in the great game of thinking. Using an equivalent set of tokens and rules, we can do thinking with a digital computer, just as we can play chess using cups, salt and pepper shakers, knives, forks, and spoons. Using the right software, one system (the mind) can be mapped into the other (the computer). (G. Johnson, 1986, p. 250)19) A Statement of the Primary and Secondary Purposes of Artificial IntelligenceThe primary goal of Artificial Intelligence is to make machines smarter.The secondary goals of Artificial Intelligence are to understand what intelligence is (the Nobel laureate purpose) and to make machines more useful (the entrepreneurial purpose). (Winston, 1987, p. 1)The theoretical ideas of older branches of engineering are captured in the language of mathematics. We contend that mathematical logic provides the basis for theory in AI. Although many computer scientists already count logic as fundamental to computer science in general, we put forward an even stronger form of the logic-is-important argument....AI deals mainly with the problem of representing and using declarative (as opposed to procedural) knowledge. Declarative knowledge is the kind that is expressed as sentences, and AI needs a language in which to state these sentences. Because the languages in which this knowledge usually is originally captured (natural languages such as English) are not suitable for computer representations, some other language with the appropriate properties must be used. It turns out, we think, that the appropriate properties include at least those that have been uppermost in the minds of logicians in their development of logical languages such as the predicate calculus. Thus, we think that any language for expressing knowledge in AI systems must be at least as expressive as the first-order predicate calculus. (Genesereth & Nilsson, 1987, p. viii)21) Perceptual Structures Can Be Represented as Lists of Elementary PropositionsIn artificial intelligence studies, perceptual structures are represented as assemblages of description lists, the elementary components of which are propositions asserting that certain relations hold among elements. (Chase & Simon, 1988, p. 490)Artificial intelligence (AI) is sometimes defined as the study of how to build and/or program computers to enable them to do the sorts of things that minds can do. Some of these things are commonly regarded as requiring intelligence: offering a medical diagnosis and/or prescription, giving legal or scientific advice, proving theorems in logic or mathematics. Others are not, because they can be done by all normal adults irrespective of educational background (and sometimes by non-human animals too), and typically involve no conscious control: seeing things in sunlight and shadows, finding a path through cluttered terrain, fitting pegs into holes, speaking one's own native tongue, and using one's common sense. Because it covers AI research dealing with both these classes of mental capacity, this definition is preferable to one describing AI as making computers do "things that would require intelligence if done by people." However, it presupposes that computers could do what minds can do, that they might really diagnose, advise, infer, and understand. One could avoid this problematic assumption (and also side-step questions about whether computers do things in the same way as we do) by defining AI instead as "the development of computers whose observable performance has features which in humans we would attribute to mental processes." This bland characterization would be acceptable to some AI workers, especially amongst those focusing on the production of technological tools for commercial purposes. But many others would favour a more controversial definition, seeing AI as the science of intelligence in general-or, more accurately, as the intellectual core of cognitive science. As such, its goal is to provide a systematic theory that can explain (and perhaps enable us to replicate) both the general categories of intentionality and the diverse psychological capacities grounded in them. (Boden, 1990b, pp. 1-2)Because the ability to store data somewhat corresponds to what we call memory in human beings, and because the ability to follow logical procedures somewhat corresponds to what we call reasoning in human beings, many members of the cult have concluded that what computers do somewhat corresponds to what we call thinking. It is no great difficulty to persuade the general public of that conclusion since computers process data very fast in small spaces well below the level of visibility; they do not look like other machines when they are at work. They seem to be running along as smoothly and silently as the brain does when it remembers and reasons and thinks. On the other hand, those who design and build computers know exactly how the machines are working down in the hidden depths of their semiconductors. Computers can be taken apart, scrutinized, and put back together. Their activities can be tracked, analyzed, measured, and thus clearly understood-which is far from possible with the brain. This gives rise to the tempting assumption on the part of the builders and designers that computers can tell us something about brains, indeed, that the computer can serve as a model of the mind, which then comes to be seen as some manner of information processing machine, and possibly not as good at the job as the machine. (Roszak, 1994, pp. xiv-xv)The inner workings of the human mind are far more intricate than the most complicated systems of modern technology. Researchers in the field of artificial intelligence have been attempting to develop programs that will enable computers to display intelligent behavior. Although this field has been an active one for more than thirty-five years and has had many notable successes, AI researchers still do not know how to create a program that matches human intelligence. No existing program can recall facts, solve problems, reason, learn, and process language with human facility. This lack of success has occurred not because computers are inferior to human brains but rather because we do not yet know in sufficient detail how intelligence is organized in the brain. (Anderson, 1995, p. 2)Historical dictionary of quotations in cognitive science > Artificial Intelligence
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19 cuidar
v.1 to look after (enfermo, niño, casa).Ella cuida a los chicos She looks after the kids.2 to take care of, to assist, to look after, to keep after.Ricardo cuida a sus padres Richard takes care of his parents.3 to keep watch over, to watch.El guarda cuida la casa The guard keeps watch over the house.4 to make an effort to, to take care to.Cuidamos mantener un buen servicio We take care to maintain a good service.* * *1 to look after, take care of, care for1 to take care of oneself, look after oneself■ ¡cuídate mucho! take good care of yourself!\cuidar(se) de que to make sure thatcuidar los detalles to pay attention to detailscuidar una herida to dress a woundcuidarse de (preocuparse) to worry about, mind* * *verb1) to take care of, look after2) pay attention to, watch* * *1. VT1) (=atender) [+ familia, jardín, edificio] to look after, take care of; [+ rebaño] to tendlas personas que deciden quedarse en casa y cuidar a sus hijos — people who decide to stay at home and look after their children
2) (=preocuparse por) [+ muebles, propiedades, entorno, salud] to look after, take care ofno cuidan nada la casa — they don't look after the house at all, they don't take any care of the house
3) (=poner atención en) [+ detalles, ortografía] to pay attention to, take care overen ese restaurante cuidan mucho los detalles — they pay great attention to detail o take great care over the details in that restaurant
el director cuidó al máximo la puesta en escena de la obra — the director took the greatest care over the production of the play
2. VI1)• cuidar de — to look after, take care of
¿quién cuidará de ti? — who will look after you?, who will take care of you?
•
cuidar de hacer algo — to take care to do sthsiempre cuidaba de mantener el termo lleno de agua caliente — he always took care to keep the thermos full of hot water
2)• cuidar con — † to be careful of
3.See:* * *1.verbo transitivoa) <juguetes/plantas/casa> to look after; < niño> to look after, take care of; < enfermo> to care for, look aftertienes que cuidar ese catarro/la salud — you should look after that cold/your health
b) <estilo/apariencia> to take care over2.cuidar vicuidar de algo/alguien — to take care of something/somebody
3.cuidar DE QUE + SUBJ: cuidarré de que no les falte nada — I'll make sure they have everything they need
cuidarse v prona) (refl) to take care of oneself, look after oneselfb) ( procurar no)cuidarse de + inf: se cuidó mucho or muy bien de (no) volver por ahí he took good care not to o he made very sure he didn't go back there; cuídate mucho de desobedecerme — you'd better do as I tell you
c) ( asegurarse)cuidar se DE + INF: se cuidó bien de cerrar las ventanas — she made sure she shut the windows
* * *= nurture, take + care of, tend, lubricate, nurse, give + care, groom.Ex. Studying the leisure reading preferences of teens can help library media specialists develop collections and programs that nurture a lifelong love of reading.Ex. The matter of bulk is well taken care of by improved microfilm.Ex. The flow of production dependent upon rows of clattering machines tended by tired children.Ex. The development of ABN has been lubricated by goodwill on the part of the parties involved.Ex. The author also evokes the story of the wolf who nursed Romulus and Remus in order to suggest the barbarity of Renaissance Rome.Ex. The traditional image of nurses, mostly women, in starched uniforms and white caps, giving care at the bedside in the hospital is out of date.Ex. Never has there been a greater interest in grooming pubic hair than there is today.----* cuidar a Alguien hasta su recuperación = nurse + Nombre + back to health.* cuidar de = look after, care (about/for), watch out for.* cuidar de la retaguardia = hold + the fort, hold + the fortress.* cuidar del rebaño = tend + flock.* cuidar ovejas = herd + sheep.* cuidar rebaños = herding.* cuidarse de = beware (of/that).* familiar que cuida de los mayores = kinkeeper.* persona que se cuida la línea = weight watcher.* * *1.verbo transitivoa) <juguetes/plantas/casa> to look after; < niño> to look after, take care of; < enfermo> to care for, look aftertienes que cuidar ese catarro/la salud — you should look after that cold/your health
b) <estilo/apariencia> to take care over2.cuidar vicuidar de algo/alguien — to take care of something/somebody
3.cuidar DE QUE + SUBJ: cuidarré de que no les falte nada — I'll make sure they have everything they need
cuidarse v prona) (refl) to take care of oneself, look after oneselfb) ( procurar no)cuidarse de + inf: se cuidó mucho or muy bien de (no) volver por ahí he took good care not to o he made very sure he didn't go back there; cuídate mucho de desobedecerme — you'd better do as I tell you
c) ( asegurarse)cuidar se DE + INF: se cuidó bien de cerrar las ventanas — she made sure she shut the windows
* * *= nurture, take + care of, tend, lubricate, nurse, give + care, groom.Ex: Studying the leisure reading preferences of teens can help library media specialists develop collections and programs that nurture a lifelong love of reading.
Ex: The matter of bulk is well taken care of by improved microfilm.Ex: The flow of production dependent upon rows of clattering machines tended by tired children.Ex: The development of ABN has been lubricated by goodwill on the part of the parties involved.Ex: The author also evokes the story of the wolf who nursed Romulus and Remus in order to suggest the barbarity of Renaissance Rome.Ex: The traditional image of nurses, mostly women, in starched uniforms and white caps, giving care at the bedside in the hospital is out of date.Ex: Never has there been a greater interest in grooming pubic hair than there is today.* cuidar a Alguien hasta su recuperación = nurse + Nombre + back to health.* cuidar de = look after, care (about/for), watch out for.* cuidar de la retaguardia = hold + the fort, hold + the fortress.* cuidar del rebaño = tend + flock.* cuidar ovejas = herd + sheep.* cuidar rebaños = herding.* cuidarse de = beware (of/that).* familiar que cuida de los mayores = kinkeeper.* persona que se cuida la línea = weight watcher.* * *cuidar [A1 ]vt1 ‹juguetes/libros› to look after, take care of; ‹casa/plantas› to look after; ‹niño› to look after, take care of; ‹enfermo› to care forseñora, le cuido el coche I'll take care of your car, Madamuna señora les cuida a los niños a woman takes care of o looks after the children for themcuida a su padre enfermo he cares for o looks after his sick fatherno sabe cuidar el dinero he's no good at looking after his moneyhay que cuidar la salud you must look after your healthcuídame la leche un momentito would you keep an eye on the milk for a moment?tienes que cuidar ese catarro you should look after that cold2 ‹estilo/detalles› to take care overdebes cuidar la ortografía you must take care over your spellingcuida mucho todos los detalles she goes to a great deal of trouble over every little detail, she pays great attention to detailcuida mucho su apariencia she takes great care over her appearance■ cuidarvicuidar DE algo/algn to take care OF sth/sbcuidaré de él como si fuera mío I'll take care of it o look after it as if it were my ownsabe cuidar de sí misma she knows how to take care of herselfcuidar DE QUE + SUBJ:cuida de que no les falte nada make sure they have everything they needcuidaré de que todo marche bien I'll make sure everything goes smoothly■ cuidarse1 ( refl) to take care of oneself, look after oneself¡cuídate! take care!, look after yourself!no se cuidan bien they don't take care of o look after themselves properly¡tú sí que sabes cuidarte! you certainly know how to look after yourself!, you don't live badly, do you?dejó de cuidarse she let herself go2 (procurar no) cuidarse DE + INF:se cuidan mucho de enfrentarse directamente they are very careful not to clash head-onse cuidó mucho or muy bien de (no) volver por ahí he took good care not to o he made very sure he didn't go back therecuídate mucho de andar diciendo cosas de mí you'd better not go round saying things about me* * *
cuidar ( conjugate cuidar) verbo transitivo
‹ niño› to look after, take care of;
‹ enfermo› to care for, look after
verbo intransitivo cuidar de algo/algn to take care of sth/sb;
cuidarse verbo pronominal ( refl) to take care of oneself, look after oneself;
¡cuídate! take care!;
se cuidó bien de no volver por ahí he made very sure he didn't go back there;
cuídate de decir algo que te comprometa take care not to say something which might compromise you
cuidar verbo transitivo & verbo intransitivo (vigilar, atender) to care for, look after: cuida tu ortografía, mind your spelling cuida de que tu hermano vaya pronto a la cama, make sure that your brother goes to bed soon
' cuidar' also found in these entries:
Spanish:
fregado
- mirar
- tratar
- velar
- criar
- cuidado
- enfermo
- línea
- vigilar
English:
attend
- attend to
- baby-sit
- care
- care for
- grouse
- house-sit
- look after
- mind
- mother
- notion
- nurse
- tend
- watch
- baby
- eye
- look
- minister
- nurture
- scrimp
* * *♦ vt1. [niño, animal, casa] to look after;[enfermo] to look after, to care for; [plantas] to look after, to tend2. [aspecto] to take care over;[ropa] to take care of, to look after;si no cuidas esos zapatos no te durarán if you don't look after those shoes they won't last;cuida mucho su aspecto físico he takes a lot of care over his appearance3. [detalles] to pay attention to;tienes que cuidar más la ortografía you must pay more attention to o take more care over your spelling♦ vicuidar de to look after;cuida de que no lo haga make sure she doesn't do it;cuida de que no se caiga (be) careful he doesn't fall* * *I v/t look after, take care ofII v/i:cuidar de look after, take care of* * *cuidar vt1) : to take care of, to look after2) : to pay attention tocuidar vi1)cuidar de : to look after2)cuidar de que : to make sure that* * *cuidar vb to look after -
20 McCormick, Cyrus
SUBJECT AREA: Agricultural and food technology[br]b. 1809 Walnut Grove, Virginia, USAd. 1884 USA[br]American inventor of the first functionally and commercially successful reaping machine; founder of the McCormick Company, which was to become one of the founding companies of International Harvester.[br]Cyrus McCormick's father, a farmer, began to experiment unsuccessfully with a harvesting machine between 1809 and 1816. His son took up the challenge and gave his first public demonstration of his machine in 1831. It cut a 4 ft swathe, but, wanting to perfect the machine, he waited until 1834 before patenting it, by which time he felt that his invention was threatened by others of similar design. In the same year he entered an article in the Mechanics Magazine, warning competitors off his design. His main rival was Obed Hussey who contested McCormick's claim to the originality of the idea, having patented his own machine six months before McCormick.A competition between the two machines was held in 1843, the judges favouring McCormick's, even after additional trials were conducted after objections of unfairness from Hussey. The rivalry continued over a number of years, being avidly reported in the agricultural press. The publicity did no harm to reaper sales, and McCormick sold twenty-nine machines in 1843 and fifty the following year.As the westward settlement movement progressed, so the demand for McCormick's machine grew. In order to be more central to his markets, McCormick established himself in Chicago. In partnership with C.M.Gray he established a factory to produce 500 harvesters for the 1848 season. By means of advertising and offers of credit terms, as well as production-line assembly, McCormick was able to establish himself as sole owner and also control all production, under the one roof. By the end of the decade he dominated reaper production but other developments were to threaten this position; however, foreign markets were appearing at the same time, not least the opportunities of European sales stimulated by the Great Exhibition in 1851. In the trials arranged by the Royal Agricultural Society of England the McCormick machine significantly outperformed that of Hussey's, and as a result McCormick arranged for 500 to be made under licence in England.In 1874 McCormick bought a half interest in the patent for a wire binder from Charles Withington, a watchmaker from Janesville, Wisconsin, and by 1885 a total of 50,000 wire binders had been built in Chicago. By 1881 McCormick was producing twine binders using Appleby's twine knotter under a licence agreement, and by 1885 the company was producing only twine binders. The McCormick Company was one of the co-founders of the International Harvester Company in 1901.[br]Bibliography1972, The Century of the Reaper, Johnson Reprint (the original is in the New York State Library).Further ReadingGraeme Quick and Wesley Buchele, 1978, The Grain Harvesters, American Society of Agricultural Engineers (deals in detail with McCormick's developments).G.H.Wendell, 1981, 150 Years of International Harvester, Crestlink (though more concerned with the machinery produced by International Harvester, it gives an account of its originating companies).T.W.Hutchinson, 1930, Cyrus Hall McCormick, Seedtime 1809–1856; ——1935, Cyrus Hall McCormick, Harvest 1856–1884 (both attempt to unravel the many claims surrounding the reaper story).Herbert N.Casson, 1908, The Romance of the Reaper, Doubleday Page (deals with McCormick, Deering and the formation of International Harvester).AP
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