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1 basic technical course
BTC, basic technical courseEnglish-Russian dictionary of planing, cross-planing and slotting machines > basic technical course
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2 basic technical course
Военный термин: начальный курс технической подготовкиУниверсальный англо-русский словарь > basic technical course
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3 BTC
1) Авиация: bus tie contactor2) Военный термин: Best Technical Course, Biochemical Test Coordinator, Boiler Technician Chief, basic technical course, buried trench concept4) Религия: Burn This Church5) Железнодорожный термин: Birmingham Terminal6) Финансы: Business Transaction Code, Код бизнес-операции7) Грубое выражение: Between The Cheeks, Big Thick Canadian, Bobby The Cunt8) Металлургия: black threaded and coupled (черная труба с резьбой и муфтой)9) Сокращение: Bachelor of Textile Chemistry, Basic Training Center, British Textile Confederation, Building Trades Council10) Университет: Bates Technical College11) Физиология: Bovine Tracheal Cartilage12) Школьное выражение: Belmont Technical College13) Вычислительная техника: Branch Target Cache, Biting The Carpet (DFUE-Slang, Usenet)14) Нефть: Baku Ceyhan pipeline, Baku-Tbilisi-Ceyhan15) Иммунология: Biologically Targeted Coherent, Blood Transfusion Centre16) Фирменный знак: Badger Truck Center, Beverage Trading Company17) Бурение: buttress-threaded connection18) Глоссарий компании Сахалин Энерджи: Baku-Tbilisi-Ceyhan project, buttress connection19) Менеджмент: budget to completion20) ЕБРР: business training centre21) Полимеры: benzene tetrachloride22) Программирование: Bit Test Complement23) Расширение файла: Bit Test and Complement24) Чат: Better Type Carefully -
4 BTC
BTC, basic technical course————————BTC, basic training center————————BTC, buried trench conceptпринцип "закрытой траншеи" (базирование ракет)English-Russian dictionary of planing, cross-planing and slotting machines > BTC
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5 skill
skil1) (cleverness at doing something, resulting either from practice or from natural ability: This job requires a lot of skill.) destreza, habilidad2) (a job or activity that requires training and practice; an art or craft: the basic skills of reading and writing.) técnica, arte•- skilful- skilfully
- skilfulness
- skilled
skill n1. habilidad / técnica2. habilidad / destrezatr[skɪl]1 (ability) habilidad nombre femenino, destreza; (talent) talento, don nombre masculino, dotes nombre femenino plural2 (technique) técnica, arte nombre masculinoskill ['skɪl] n1) dexterity: habilidad f, destreza f2) capability: capacidad f, arte m, técnica forganizational skills: la capacidad para organizarn.• acierto s.m.• amaño s.m.• apaño s.m.• arte s.m.• artesania s.f.• facultad s.m.• habilidad (Conocimiento práctico) s.f.• industria s.f.• maña s.f.• pericia s.f.• primor s.m.• práctica s.f.skɪla) u ( ability) habilidad fgame of skill — juego m de ingenio
skill IN/AT something: her skill at (doing) crosswords su habilidad para hacer crucigramas or para los crucigramas; the post requires skill in administration — el puesto requiere dotes or aptitudes administrativas
b) c ( technique)she has no secretarial skills — no sabe taquigrafía ni mecanografía (or procesamiento de textos etc)
social skills — don m de gentes
[skɪl]Nhis lack of skill in dealing with people — su inaptitud or falta de capacidad para tratar con la gente
technical skill(s) — conocimientos mpl técnicos
2) (=technique) técnica fcommunication skills — habilidad f or aptitud f para comunicarse
language skills — (with foreign languages) habilidad f para hablar idiomas
* * *[skɪl]a) u ( ability) habilidad fgame of skill — juego m de ingenio
skill IN/AT something: her skill at (doing) crosswords su habilidad para hacer crucigramas or para los crucigramas; the post requires skill in administration — el puesto requiere dotes or aptitudes administrativas
b) c ( technique)she has no secretarial skills — no sabe taquigrafía ni mecanografía (or procesamiento de textos etc)
social skills — don m de gentes
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6 training
( боевая) подготовка; обучение; тренировка; наведениеship-based training (for assault landing) — десантная подготовка совместно с кораблями и плавучими средствами
— career enhancing training— common-track training— continental US training— cross-rate training— gunnery-oriented training— hand-to-hand combat training— intra-unit training— joint service training— nuclear weapon training— physical readiness training— reserve cycle training— resident school training— rifle marksmanship training— systems specific training -
7 term
1. n период, срок; время; продолжительностьthe Labour Party tried to achieve this during its various terms of office — лейбористская партия пыталась добиться этого в периоды своего пребывания у власти
2. n срок тюремного заключения3. n срок квартальных платежейtenant of the term — владелец на срок; арендатор на срок
4. n семестр, четвертьin term, during term — в течение семестра
5. n триместрEaster term — весенний триместр, пасхальный триместр
Lent term — великопостный триместр, весенний триместр
6. n сессия7. n обыкн. l8. n условияterm of paragraph — условие; раздел
9. n условия оплатыwhat are your terms? — каковы ваши условия?, сколько вы берёте?
10. n обыкн. отношения11. n терминground term — базовый терм; элементарный терм
12. n выражение; слово13. n выражения, язык, способ выражатьсяin set terms — определённо, ясно
in broad terms the history of Shakespeare studies is familiar — в общем и целом история изучения Шекспира известна
14. n уст. граница, предел15. n уст. цель, конечная точка16. n уст. исходная, отправная точка; начало17. n уст. уст. назначенное время; срокlong term — долгий срок; долгосрочный
18. n уст. аренда на срок; срок выполнения обязательств19. n уст. назначенный день уплаты аренды20. n мед. нормальный период беременности; своевременное разрешение от бремениterm infant — ребёнок, родившийся в срок
21. n мед. уст. менструация22. n мед. мат. лог. член, элемент; терм23. n мед. физ. энергетический уровень; терм24. n мед. архит. колонна со скульптурой, пьедестал с бюстом; терм25. v выражать, называтьСинонимический ряд:1. administration (noun) administration; reign; rule2. condition (noun) condition; provision; proviso; qualification; reservation; specification; stipulation3. interval (noun) interval; spell4. life (noun) existence; life; lifetime5. limit (noun) bound; confines; end; limit; limitation6. period (noun) period; season; span7. period of time (noun) course; course of time; period of confinement; period of tenure; period of time; quarter; semester; session8. time (noun) duration; span; stretch; time9. word (noun) appellation; designation; expression; locution; name; nomenclature; phrase; terminology; vocable; word10. name (verb) baptise; baptize; call; characterise; christen; denominate; designate; dub; entitle; label; name; style; tag; title -
8 report
донесение, сообщение; доклад; рапорт; арт. звук выстрела; доносить; докладывать; рапортовать; представлять(ся) ( начальнику), pl. представление донесений ( пункт боевого приказа)meaconing, interference, jamming, intrusion report — донесение о применении комплексных помех типа «Миджи» (помехи РИС, пассивные и активные помехи, помехи средствам радиосвязи)
— bombing report— casualty situation report— exemption report— hotline report— letter efficiency report— logistics status report— minefield lifting report— nuclear attack report— performance evaluation report— weapons status report -
9 error
1) ошибка; погрешность2) искажение•error in indication — погрешность показания ( прибора); погрешность отсчёта;errors in the same sense — погрешности одного знака;error on the safe side — погрешность в сторону увеличения запаса прочности;to accumulate errors — накапливать погрешности;to combine errors — суммировать погрешности;to compensate error — 1. компенсировать ошибку ( показаний прибора) 2. возд. списывать (устранять) девиацию радиокомпаса;to distribute error of closure — геод. разбрасывать невязку;to hold measurement errors to... — удерживать погрешности измерений в пределах...;to introduce an error — вносить погрешность;to negate errors — исключать погрешности; компенсировать погрешности;to reduce errors — 1. уменьшать (снижать) погрешности 2. приводить погрешности ( к определённым условиям или определённому виду)error of approximation — погрешность приближения, погрешность аппроксимацииerror of closure — геод. невязкаerror or connection — геод. невязкаerror of direction — ошибка в определении направленияerror of division (error of graduation) — погрешность градуировкиerror of indication — погрешность показания ( прибора); погрешность отсчётаerror of observation — 1. погрешность наблюдения; погрешность отсчёта 2. геод. ошибка измерения, ошибка наблюденияerror of omission — 1. пропуск, пробел 2. упущениеerror of position — 1. погрешность в определении положения или местоположения 2. геод. координатная невязкаerror of traverse — геод. линейная невязка-
absolute error
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acceptable error
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accidental error
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accumulated error
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accumulative error
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accuracy error
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across-track error
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actual error
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additive error
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admissible error
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aggregate error
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airborne equipment error
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aliasing error
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alignment error
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along-track error
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altering error
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altimeter error
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ambiguity error
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amplitude error
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angular error
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appreciable error
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approximation error
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arithmetic error
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assigned error
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assumed error
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azimuth error
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backlash error
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base error
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basic error
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beam landing error
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bearing error
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bias error
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bias stability error
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bit error
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block mean-squared error
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boresight error
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burst error
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calibration error
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chaining error
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chip error
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chroma error
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closing error
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closure error in leveling
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closure error of angles
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closure error of azimuths
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closure error
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collimation error
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color error
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color-hue error
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color-purity error
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color-registration error
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combined error
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common error
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compass error
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compass turning error
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compensating errors
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complementary error
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component error
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composite error
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composition error
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computational error
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computation error
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computed error
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concealed error
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conformity error
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connection error
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consistent error
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constant error
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contributing error
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conventional error
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copying error
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course error
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crude error
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cumulative error
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cyclic error
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data error
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datum error
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day-to-day error
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dead-path error
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delay error
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detected error
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digital error
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displacement error
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distance error
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dynamic error
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dynamic phase error
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end errors
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erratic error
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estimated error
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estimation error
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excessive error
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exposure error
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extreme error
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fatal error
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fixed error
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flight technical error
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focusing error
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focus error
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folding error
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following error
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forecast error
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form error
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fractional error
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frequency error
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full-scale error
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gaging error
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gamma error
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gang error
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geometrical error
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geometric error
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glide path angular error
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graduation error
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gross error
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group-delay error
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guidance error
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guide positional error
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gyrocompass error
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hard error
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hardware error
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head-penetration error
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heeling error
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height-keeping error
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horizontal phase error
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hue error
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human error
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implementation error
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inbound error
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index error
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indicated displacement error
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indication error
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individual error
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inherent error
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inherited error
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initial error
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input error
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instrumental error
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instrument error
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interference error
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interlace error
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interpolation error
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interval error
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intolerable error
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intrinsic error
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introduced error
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ionosphere error
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lead error
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leveling error
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limiting error
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linear error
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linearity error
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logical error
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longitudinal error
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long-term error
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machine error
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marginal error
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maximum error
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maximum likely error
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maximum relative error
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maximum zero error
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mean error
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mean square error
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measurement error
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minimum error
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minimum mean-square error
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minimum prediction error
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mismatch error
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mispositioning error
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momentary error
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multiple error
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navigation error
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near-extreme error
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negative error
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noise error
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nominal error
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nonlinear error
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observation error
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observed error
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offset error
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omission error
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operator's error
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optimistic error
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outbound error
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output error
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overall error
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overlay error
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parity check error
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parity error
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partial error
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particular error
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parts-to-platen error
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patching error
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path following error
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peak error
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peak-to-peak error
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permissible error
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personal error
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pessimistic error
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phase error
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pitch error
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platen-to-machine error
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pointing error
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position error
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position following error
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positional error
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positioning error
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positive error
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predicted following error
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prediction error
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probable error
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procedural error
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propagation delay error
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quadrantal error
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quadratic phase error
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quadrature error
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quantization error
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radial displacement error
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radiation error
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random error
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range error
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ratio error
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reader error
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reading error
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reasonable error
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recoverable error
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reduced error
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reference limiting error
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registration error
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relative error
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residual error
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resistance error
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resolution error
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resultant error
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root-mean-square error
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rounding error
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routine/routine interface error
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run-time error
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sampling error
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saturation error
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scale calibration error
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scale error
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scanning error
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select error
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sequence error
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servo excess error
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servo following error
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sextant error
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shade error
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shading error
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sighting error
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significant error
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single error
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skew error
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slide-position error
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soft error
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software error
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speed error
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sporadic error
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standard error
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static error
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statistical error
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steady-state error
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steering error
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step-up error
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substitution error
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superposition error
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systematic error
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tape speed errors
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targeting error
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temperature error
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temporary error
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tilt error
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time error
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time-base error
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tool setting error
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total error
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tracking error
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transfer error
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transient error
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true error
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truncation error
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typing error
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typographic error
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unconcealable error
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uncorrectable error
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undetected error
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unrecoverable error
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unsuspected error
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user clock time bias error
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velocity error
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vertical phase error
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voltage error
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weighted mean error
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wiring error
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zero end error
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zero error
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zero setting error
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zero-drift error -
10 training
n мен., кадр, навчання; підготовка; тренування; a навчальний; підготовчийпрактична діяльність особи, яка націлена на поліпшення та удосконалення знань, умінь, навичок і т. ін. для виконання роботи (job¹) або досягнення визначеної цілі═════════■═════════adequate training відповідна підготовка; advanced training підвищення кваліфікації; advanced vocational training підвищення професійної кваліфікації; agricultural training сільськогосподарська підготовка (кадрів); apprentice trainings учнівство • професіонально-технічне навчання; appropriate training відповідне навчання; basic training первинна професійна підготовка; correspondence training заочне навчання; day release training навчання з відривом від роботи; environmental training природоохоронне навчання • навчання з охорони навколишнього середовища; executive training підготовка (і підвищення кваліфікації) керівників і спеціалістів; formal training формальне навчання; free training безплатне навчання; further training подальша підготовка; general training загальна підготовка; group training групове навчання; hands-on training практичне навчання; individual training індивідуальне навчання; industrial training виробниче навчання; in-house training підготовка власними силами; in-plant training виробниче навчання; in-service training навчання на місці роботи • підготовка без відриву від виробництва; job training професійне навчання; legal training юридична підготовка; management training підготовка керівних кадрів; mercantile training комерційна підготовка; occupational training професійне навчання; off-site training навчання з відривом від виробництва; on-the-job training навчання на місці (за місцем) роботи; orientation training професійна орієнтація; personnel training навчання персоналу; plant training виробниче навчання; practical training практичне навчання; preemployment training підготовка до влаштування на роботу; preliminary training попередня підготовка; preparatory training підготовче навчання; previous training попереднє навчання; product training навчання товарознавства; professional training професійне навчання • професійна підготовка; safety training навчання техніки безпеки; sales training підготовка торговельних працівників; sensitivity training тренування сприйнятливості; skills training професійне навчання; special training спеціалізована підготовка; specialized training спеціальна підготовка; staff training підготовка кадрів; supervisory training навчання середнього керівного персоналу; technical training технічне навчання; vocational training професійно-технічне навчання • професійна підготовка═════════□═════════to complete training проходити/пройти курс навчання; to conduct training проводити/ провести навчання; to extend training продовжувати/продовжити навчання; to get practical training проходити/пройти курс практичного навчання; to provide training забезпечувати/забезпечити навчання; to receive training отримувати/отримати підготовку; training allowance стипендія стажиста; training centre навчальний центр; training college професійне училище • технікум • педагогічний інститут; training course курс навчання; training of a crew навчання команди; training of personnel підготовка кадрів • навчання персоналу; training of specialists підготовка спеціалістів; training on the job навчання на місці роботи; training opportunity можливість професійного навчання; training pay стипендія стажиста; training period період навчання; training place місце навчання • місце проходження практики; training post посада стажиста; training scheme план навчання; training within industry система навчання в промисловості -
11 set
1) набор; комплект- semiconductor assembly set - set of Belleville springs - set of conventional set - set of drawing instruments - set of gate patterns - set of gauge blocks - set of logical elements - set of statistical data - set of technical aids- snap set2) партия3) совокупность; множество4) установка; агрегат- desk telephone set - dial telephone set- gear set- local-battery telephone set - man-pack radio set - multi-operator welding set - sound-powered telephone set - wall telephone set5) регулировка; настройка || регулировать; настраивать6) группа; ансамбль7) класс; семейство9) схватывание || схватываться10) затвердевание || затвердевать11) крепление || закреплять12) геол. свита пород13) осадка (грунта) || оседать ( о грунте)14) радиоточка15) спорт сет16) включать, приводить в действие17) мат. множествоset closed under operation — множество, замкнутое относительно операции
- absolutely compact set - absolutely continuous set - absolutely convex set - absolutely irreducible set - absolutely measurable set - affinely independent set - affinely invariant set - algebraically independent set - almost finite set - almost full set - angular cluster set - asymptotically indecomposable set - at most denumerable set - centro-symmetric set - completely bounded set - completely continuous set - completely generating set - completely improper set - completely irreducible set - completely nonatomic set - completely normal set - completely ordered set - completely productive set - completely reducible set - completely separable set - constructively nonrecursive set - convexly independent set - countably infinite setto set aside — не учитывать, не принимать во внимание; откладывать
- cut set- cyclically ordered set - deductively inconsistent set - derived set - doubly well-ordered set - dual set of equations - dynamically disconnected set - effectively enumerable set - effectively generating set - effectively nonrecursive set - effectively simple set - enumeration reducible set - finely perfect set - finitely definite set - finitely measurable set- flat set- full set- fully reducible set - functionally closed set - functionally complete set - functionally open set - fundamental probability set - generalized almost periodic set- goal set- internally stable set- knot set- left directed set - left normal set - left-hand cluster set - linearly ordered set - local peak set - locally arcwise set - locally closed set - locally compact set - locally connected set - locally contractible set - locally convex set - locally finite set - locally invariant set - locally negligible set - locally null set - locally polar set - locally polyhedral set - metrically bounded set - metrically dense set - multiply ordered set - nearly analytic set - nearly closed set - nonvoid set - normally ordered set- null set- open in rays set - partitioned data set- peak set- pole set- positively homothetic set- pure set- radially open set - rationally independent set - recursively creative set - recursively indecomposable set - recursively isomorphic set - recursively productive set - regularly convex set - regularly situated sets - relatively closed set - relatively compact set - relatively dense set - relatively interpretable set - relatively open set - right normal set - right-hand cluster set- scar set- sequentially complete set - serially ordered set - set of elementary events - set of first category - set of first kind - set of first species - set of possible outcomes - set of probability null - set of second category - set of second species - shift invariant set - simply connected set - simply ordered set - simply transitive set- skew set- star set- strongly bounded set - strongly closed set - strongly compact set - strongly connected set - strongly convex set - strongly dependent set - strongly disjoint sets - strongly enumerable set - strongly independent set - strongly minimal set - strongly polar set - strongly reducible set - strongly separated set - strongly simple set - strongly stratified set- tame set- tautologically complete set - tautologically consistent set - tautologically inconsistent set- test set- thin set- tie set- time set- totally disconnected set - totally imperfect set - totally ordered set - totally primitive set - totally unimodular set - totally unordered set - truth-table reducible set - uniformly bounded set - uniformly continuous set - uniformly convergent set - uniformly integrable set - uniformly universal set - unilaterally connected set- unit set- vacuous set- void set- weakly compact set - weakly convex set - weakly n-dimensional set - weakly stratified set - weakly wandering set - well chained set - well founded set - well measurable set - well ordering set - well quasiordered set -
12 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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13 error
nпомилка, похибка◊in [by, through] error — помилково
to compensate the error — 1) списувати девіацію (компаса); 2) компенсувати похибку (приладу)
to determine amount of the error — 1) визначати величину (радіо)девіації; 2) визначати величину похибки
•- acceptable error - accidental error - accumulated error - across-track error - actual error - aggregate error - airborne equipment error - alignment error - along-track error - altimeter error - altitude error - angular error - appreciable error - azimuth error - backlash error - backlash error of altimeter - basic error - bias error - compass error - component error - detected error - displacement error - drift error of altimeter - elevation error - error in indication - error in measurement - error of height - error of significance - flight technical error - following error - glide path angular error - gross error - guidance signal error - height-keeping error - hysteresis error - indicated displacement error - indicated glide path angular error - instrument error - lateral error - mean course error - mean glide path error - mean-square error - navigation error - observation error - offset error - optimistic error - parity error - path following error - pilot's error - quadrantal error - radial displacement error - radiation error - random error - range error - reading error - slaving error - static pressure system position error - steady-state error - systematic error - tactical error - track angle error - VOR airborne equipment error - VOR radial displacement error - VOR radial signal error - VOR radial variability error - zero setting error
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