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МИНИСТЕРСТВО ОБРАЗОВАНИЯ И НАУКИ РОССИЙСКОЙ ФЕДЕРАЦИИ
Федеральное государственное автономное
образовательное учреждение высшего образования
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САНКТ-ПЕТЕРБУРГСКИЙ ГОСУДАРСТВЕННЫЙ УНИВЕРСИТЕТ
АЭРОКОСМИЧЕСКОГО ПРИБОРОСТРОЕНИЯ
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ТЕХНИЧЕСКИЙ ПЕРЕВОД
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Information systems mathematical support
and administration
Учебно-методическое пособие
Санкт-Петербург
2015
УДК81.25(075.8)
ББК 81.2-7я73
Т38
Рецензенты:
кандидат филологических наук, доцент А. О. Костылев;
старший преподаватель А. В. Ерышева
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Утверждено
редакционно-издательским советом университета
в качестве учебно-методического пособия
Авторы: И. И. Громовая, О. В. Злобина,
М. В. Левченко, М. А. Чиханова
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Т38 Технический перевод. Information systems mathematical support
and administration: учеб.-метод. пособие. – СПб.: ГУАП, 2015. – 50 с.
Пособие состоит из трех частей и приложения. В первой части
рассматриваются общие вопросы теории и практики перевода применительно к специальному техническому переводу; во второй части представлены основные межъязыковые приемы преобразования
исходного текста и способы их реализации; третья часть представляет собой практикум перевода, переводческого анализа и редактирования наиболее сложных текстов. Используются современные
аутентичные тексты из британских и американских источников.
Издание предназначено для студентов направления «Математическое обеспечение и администрирование информационных систем» и направлено на освоение и развитие практических навыков
перевода.
УДК 81.25(075.8)
ББК 81.2-7я73
© Санкт-Петербургский государственный
университет аэрокосмического
приборостроения, 2015
CHAPTER I
ПРОБЛЕМЫ ТЕХНИЧЕСКОГО ПЕРЕВОДА И ИХ РЕШЕНИЕ
1. Лингвистические основы перевода
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Перевод любого текста можно считать определенным видом
преобразования. Основное требование – сохранение информации,
которая без искажения и неточностей должна быть передана на
другом языке. Другими словами, при переводе текста должен быть
сохранен план содержания при неизбежных изменениях плана выражения, т. к. языковые системы участвующих в переводе языков
существенно различаются.
Тексты, представленные в настоящем пособии, относятся к научному стилю речи, который характеризуется рядом особенностей.
Основу языкового оформления подобных текстов отличает стандартизированные, клишированные выражения, синтаксическая полнота высказываний, наличие аналитических конструкций и т. д.
Тема научного текста не влияет на то, как оформлен текст, т. е.
на способ его оформления. Знание особенностей научного стиля
речи, которые приняты в английской и русской научной традиции,
существенно облегчает выбор лексических и грамматических соответствий.
Объективность изложения достигается с помощью определенных лингвистических средств, например, в качестве подлежащего
часто выступает имя существительное, как правило, термин. В русскоязычной традиции не приветствуется использование в научных
текстах личного местоимения «я», в английской традиции, напротив, местоимение «I» может выступать в роли подлежащего. Следовательно, фразу «In my work» на русский язык следует перевести
либо «В настоящей работе», либо «В нашей работе».
В научных текстах отдают предпочтение «безличному» описанию экспериментов, рассуждений, результатов исследований, выводов. В русских текстах в таких случаях используются глагольные
конструкции типа «была предпринята попытка показать», «были
проведены эксперименты», «в настоящей работе затрагивается
ряд важных вопросов», «можно сделать следующий вывод», «необходимо обратить внимание», «следует подчеркнуть» и т. п.
В научных текстах обязательно присутствуют общеязыковые
лексические сокращения, специальные терминологические сокращения, условные обозначения.
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Однако прежде чем приступить к переводу текста, следует провести анализ, который должен состоять из нескольких этапов. Такой анализ принято назвать переводческим анализом текста.
Не торопитесь сразу приступать к переводу. Время, затраченное на подготовку, окупится!
1 этап. Выработка переводческой стратегии, т. е. определение
последовательности переводческих действий. Этот этап часто называют предпереводческим анализом текста, предполагающим
1) сбор «внешней информации», т. е. сведений о тексте:
– кто является автором/авторами текста.
– является ли переводимый текст самостоятельным или это
фрагмент текста, статья из какого-либо научного или научно-популярного журнала, или это фрагмент монографии, параграф учебника. В этом случае следует собрать информацию об этой монографии,
учебнике, журнале. Знание этих фактов позволяет определить, что
можно, а что нельзя допускать в переводе текста.
2) определение целевой аудитории и времени создания текста:
– кто является получателем текста (специалисты, широкий
круг читателей, студенты, ученики и т. д.).
3) выявление совокупности типов информации1 (когнитивная, оперативная, эмоциональная, эстетическая), представленных в тексте.
В научном тексте основным видом информации является когнитивная информации, т. е. объективные сведения о внешнем мире.
Когнитивная информация представлена в тексте лексикой общенаучного описания, (часто это клишированные языковые средства) и терминами. В пределах одной области знаний термин всегда
однозначен и всегда соотнесен только с одним объектом, т. е. термин внеконтекстуален. В другой области знаний этот же термин
может обозначать совершенно другое понятие или иной объект действительности, следовательно, это разные термины.
Для английских научных текстов характерен прямой порядок
слов, именные структуры, широкое использование простых двусоставных предложений со сложным сказуемым, включающим
глагол-связку и именную/ глагольную часть, настоящее время
глагола, которое показывает события с максимальной степенью
обобщения, частое использование пассивных конструкции (как
глагольных, так и других лексико-грамматические средств со значением пассивности), атрибутивных групп, использование вместо
1 См., например, И. С. Алексеева. Профессиональный тренинг переводчика.
СПб., 2008.
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глаголов отглагольных именных форм с предлогами, эллиптических конструкций, так как научный текст стремится к компактности изложения.
Научные тексты может отличать высокая компрессивность,
или плотность, информации, которая выражается аббревиатурами, различными сокращениями, графиками, схемами, таблицами,
формулами и т. д.
Оперативная информация – это предписание к совершению
определенных действий, следовательно, она может быть выражена
глаголами в императиве (повелительном наклонении), инфинитивом со значением императивности (прочитать, написать, выделить, подчеркнуть, обратить внимание, запомнить и т. д.), модальными глаголами и модальными словами и т. д.
Другие виды информации (эмоциональная, экспрессивная) могут присутствовать в научном тексте, но в ограниченном объеме.
Эмоциональная информация будет передаваться с помощью эмоционально окрашенной лексики. Информация такого рода может
присутствовать в научно-популярных текстах и в текстах учебников.
Эстетическая информация преобладает в художественных текстах.
2 этап. Собрав сведения о тексте и установив, какие виды информации присутствуют, необходимо определить коммуникативное задание текста, которое, как правило, заключается в том,
чтобы сообщить новые сведения, доказать научную гипотезу, убедить в своей правоте. Верное определение коммуникативного задания позволяет достаточно легко выделить в тексте так называемые
доминанты перевода, т. е. определить информацию, которая оказывается главной при переводе, например, термины, нейтральная
общенаучная лексика, сложные слова, различные, в том числе терминологические сокращения, аббревиатуры, пассивные конструкции, неопределенно-личные или безличные грамматические структуры, т. е. средства, благодаря которым сохраняется логичность и
объективность.
3 этап. Далее следует внимательно проанализировать содержание текста и его грамматическую структуру. Это два взаимосвязанных процесса, которые не следует отделять друг от друга, поскольку для отдельных фрагментов текста существуют определенные
соответствия в виде слов, словосочетаний, грамматических конструкций. Только исходя из смысловой и грамматической структуры текста, можно снять лексическую и грамматическую неопределенность или избыточность. Параллельный анализ грамматиче5
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ской и смысловой структур текста в результате позволяют создать
правильный вариант перевода.
Однако без использования ряда переводческих операций, называемых трансформациями, невозможно добиться адекватного, корректного перевода. Трансформации (от латинского глагола
«transformare» – «превращать», «преображать», «переводить»),
или преобразования, текста вызваны несовпадением, а иногда и
расхождением лексико-грамматических систем языков, участвующих в переводе.
Следовательно, причинами переводческих трансформаций могут быть:
– несовпадение языковых систем языка оригинала (ИЯ) и языка
перевода (ПЯ);
– несовпадение языковых норм ИЯ и ПЯ;
– стремление использовать выражения и конструкции, характерные для ПЯ;
– несовпадение объемов понятий в ИЯ и ПЯ;
– необходимость соблюдать нормы сочетаемости слов в ПЯ;
– необходимость соблюдения стилистических норм ИЯ и ПЯ.
Переводческие трансформации являются обычной процедурой
любого процесса перевода. Как правило, лексические или грамматические трансформации в чистом виде встречаются редко. Чаще
они сочетаются.
Принято выделять следующие виды трансформаций:
1. Замены, в том числе функциональные:
1) грамматические – форм слова, частей речи, членов предложения, замены простого предложения сложным и наоборот, союзных
предложений бессоюзными и т. д.;
2) лексические и лексико-грамматические:
– конкретизация (замена широкого понятия узким, абстрактного – конкретным);
– генерализация (замена узкого понятия широким, конкретного – абстрактным);
– прием смыслового развития/ или смысловая модуляция (замена словарного соответствия контекстуальным, выполняющим
аналогичную функцию в тексте перевода);
– антонимический перевод (замена утвердительной конструкции отрицательной или наоборот);
– компенсация потерь в процессе перевода (когда элементам исходного текста невозможно найти эквиваленты в тексте перевода,
или когда эквиваленты есть, но их нельзя использовать в силу того,
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что они выполняют различные функции). В этих случаях в переводе используются другие средства ПЯ.
2. Перестановки, например, изменения порядка следования
слов в предложении или перестановки главного и придаточного
предложений.
3. Добавления продиктованы разными синтаксическими и лексическими структурами русского и английского языков.
4. Опущения оказываются необходимы при переводе семантически избыточных элементов, например, при переводе парных синонимов.
5. Описание значения исходной единицы или комментарий применяется в условиях отсутствия регулярного словарного соответствия.
6. Уподобление используется при переводе грамматических
форм в условиях составных конструкций, комбинаторика которых
не совпадает в ИЯ и ПЯ.
7. Конверсия применяется в условиях различных требований,
применяемых к эксплицитности выражения в ИЯ и ПЯ, а также
при различии комбинаторных правил сочетаемости грамматических форм. Она заключается в изменении морфологического статуса исходной грамматической единицы при полном или частичном
сохранении ее категориальных значений.
8. Развертывание проявляется в расщеплении лексико-грамматической единицы на составляющие, каждая из которых несет
часть исходной информации, например, для преобразования синтетических форм в аналитические.
9. Стяжение выражается в сокращении морфологической формы ИЯ при условии полного или частичного сохранения ее категориальных значений, что позволяет более лаконично передать ту же
самую информацию.
2. Перевод терминов и терминологических сочетаний
К этому типу слов предъявляются особые требования. «Прежде
всего, термин должен быть точным, т. е. иметь строго определенное
значение, которое может быть раскрыто путем логического определения, устанавливающего место обозначенного термином понятия
в системе понятий данной области науки или техники»1.Термин –
1 Латышев Л. К., Федоров А. В. Учебное пособие по теории перевода. М., 2007,
С. 55–56.
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это слово или словосочетание, принятое для точного выражения
специального понятия или обозначение специального предмета в
той или иной области знаний.1
Термины могут представлять собой простые термины-существительные, сокращенные термины, сложные термины, многокомпонентные термины, термины-глаголы, термины-прилагательные,
термины-словосочетания, «которые создаются путем добавления
к термину, обозначающему родовое понятие, конкретизирующих
признаков с целью получить видовые понятия, непосредственно
связанные с исходным».2 Термины могут также представлять собой терминологическую группу с ядерным, ключевым словом и несколькими предложными или беспредложными определениями,
которые могут располагаться слева или справа от ядерного слова.
Термины не должны зависеть от контекста, напротив, они должны обеспечивать четкое и точное указание на реальные объекты и
явления, устанавливать однозначное понимание специалистами
передаваемой информации. Не должно быть терминов-синонимов
с совпадающими значениями. Термин лишен субъективности, он
всегда и везде объективен, лишен эмоционального оттенка, метафоричности, образности.
Состав терминологии не является постоянным. Он изменяется
и пополняется за счет изменения значений, пополнения новыми
терминами, например, в связи с появлением и разработкой новых
образцов технических товаров.
Образование терминов происходит следующим образом (способы образования, характерные для английского языка):
– морфологический способ: а) аффиксация; б) словосложение;
в) конверсия; г) аббревиация
– лексико-семантический способ: а) перенос значения; б) изменение значения; в) расширение значения; г) сужение значения
– заимствование из других областей науки и техники;
– заимствование из других языков.
Задача переводчика заключается в том, чтобы адекватно передать понятие иностранного языка средствами языка перевода. При
переводе обязательно следует учитывать роль контекста, значение
термина в данном окружении, в предлагаемой ситуации. Не забывайте про сдвиг значения термина при использовании множественного числа. Не всегда буквальное соответствие термину – это
1 Нелюбин Л. Л. Введение в технику перевода. М., 2009, С. 58–59.
2 Паршин А. Теория и практика перевода, (электронное издание). С. 67.
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правильный выбор переводчика. Буквализм может привести к стиранию специфики реалий иностранного языка. Либо может возникнуть ошибка, т. к. используемые в тексте оригинала термины
могут выражать понятия, характерные для данной предметной области в исходном языке, и в связи с этим могут не соответствовать
реалиям, принятым в языке перевода.
С точки зрения понимания и трудностей перевода термины делятся на три группы:
1. Термины, обозначающие реалии иностранной действительности, идентичные реалиям российской действительности. Перевод
таких терминов трудностей не вызывает.
Традиционно предлагаются следующие способы перевода подобных терминов:
– интернациональные термины, когда формы английского и
русского терминов связаны;
– русский эквивалент, формы английского и русского термина
не связаны;
– перевод многокомпонентных английских терминов многокомпонентными русскими терминами. Компоненты термина совпадают по форме и значению;
– общее значение многокомпонентных терминов в обоих языках
совпадает, но есть различия в отдельных компонентах;
2. Термины, обозначающие реалии иностранной действительности, отсутствующие в русской действительности. Такие термины
имеют общепринятые терминологические эквиваленты в русском
языке и переводятся (а) подбором аналога или (б) адекватной заменой с учетом контекста и знаний предметной области.
3. Термины, обозначающие реалии иностранной действительности, отсутствующие в русской действительности. Эти термины не
имеют зафиксированных традицией терминологических эквивалентов.
Возможные варианты перевода: описание; пословный перевод;
частичная или полная транслитерация; соединение транслитерации и пословного перевода; транскрибирование; соединение транскрибирования и перевода.
4. Термины-неологизмы объясняются автором в контексте или
сопровождаются комментарием.
На этапе выбора эквивалента для перевода очень важной оказывается информация, полученная на этапе анализа формы и содержания термина или терминологического словосочетания, соотнесения формы и содержания. Этот анализ может избавить пере9
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водчика от необходимости обращения к словарю, так как, уяснив
значение термина, можно самостоятельно подобрать эквивалент в
языке перевода. Подобный анализ также облегчает процесс поиска и выбора переводного эквивалента, он указывает, какой частью
речи является термин и какова его роль в предложении.
В выборе эквивалента могут помочь узкоспециальные словари и
изучение литературы по теме.
Определенные сложности при переводе терминов и терминологических сочетаний могут быть вызваны:
– несовпадением терминологических систем;
– недостаточным владением терминологией на русском языке;
– неоднородностью специальной терминологии;
– терминологическими заимствованиями из других областей
науки или из общеупотребительной лексики;
–наличием терминов-синонимов;
– недостатком фоновых знаний;
– неумением работать со словарем;
– отсутствием словарного эквивалента.
Помните! Однозначность термина не следует путать с однозначным вариантом перевода термина на другой язык, т. к. переводной
эквивалент – это только один из возможных вариантов перевода.
Объем понятий, обозначенных терминами в языке оригинала и
перевода не совпадает!
3. Перевод многокомпонентных терминов
Особую трудность при переводе составляют многокомпонентные
термины, особенно осложненные аббревиатурами.
По количеству компонентов термины бывают двух-, трех-, четырехкомпонентными (и более).
При большом количестве компонентов сочетания для сохранения семантико-стилистических связей эти компоненты принято
соединять дефисом.
Последовательность проведения семантико-стилистического
анализа при переводе многокомпонентных терминов
1. Перевести ключевое слово (как правило, это последнее слово
терминологического ряда).
2. Проанализировать смысловые связи между компонентами
и выделить смысловые группы, начиная с первого слова слева направо.
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3. Установить связи между выделенными смысловыми группами, провести перевод всего терминологического ряда справа налево, начиная с ключевого слова.
4. Провести стилистический анализ и отредактировать перевод.
Способы перевода многокомпонентных терминов
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1. Самый простой способ – с использованием аналогичной препозитивной атрибутивной группы. Этот способ заключается в последовательном переводе составляющих данное сочетание компонентов.
2. Перестановка компонентов. В этом случае перевод следует
осуществлять справа налево: сначала переводятся один или два последних компонента (они несут основную смысловую нагрузку),
затем последовательно справа налево переводится каждый компонент сочетания или смысловая группа.
3. При помощи именных предложных сочетаний типа «существительное + предлог + существительное».
4. При помощи причастных или деепричастных оборотов.
5. Описательный перевод.
4. Рабочие источники информации
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Все рабочие источники информации, с которыми работает переводчик, можно разделить на общие и специальные.
К общим источникам информации принято относить (а) словари общего назначения (двуязычные, фразеологические, толковые
(одноязычные), словари иностранных слов, словари синонимов и
антонимов, общие энциклопедические словари) и (б) специальные
источники информации (специальные словари, специальные энциклопедии и справочники по различным отраслям науки и техники,
специальную литературу и другие источники информации).
5. Практические рекомендации
по научному и техническому переводу
При переводе научно-технической литературы на первый план
выходит понимание предмета переводимого текста. Большое значение имеет и знание соответствующей русской терминологии,
принятой в каждой конкретной области науки и техники. Реко11
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мендуется использовать общероссийскую стандартную терминологию там, где она принята. Описательный перевод допустим только
в случае отсутствия термина в языке перевода.
Прежде чем приступать к переводу, необходимо внимательно и
тщательным образом ознакомиться с основными моментами, важными для понимания материалов по данной специальности.
Перевод должен отличаться точностью передачи мысли, точностью в использовании терминологии, лаконичностью, отсутствием
длиннот.
Несколько практических советов:
1. Приступая непосредственно к переводу и знакомясь с текстом оригинала, подчеркните встретившиеся термины и подберите
переводы для них. Если есть варианты, продумайте, какой лучше.
Обратитесь к специальной литературе, справочникам, словарям.
Выверяйте термины. При выборе варианта перевода из нескольких
вариантов ориентируйтесь на контекст, который снимает полисемию (многозначность), позволяет точно понять и правильно передать содержание термина. При переводе может помочь латинское
название термина. В таком случае одной транслитерации будет недостаточно.
Внимание! Перевод терминов должен соответствовать значениям, принятым в среде специалистов данной отрасли. В качестве
терминов могут также выступать общеупотребительные слова в
специальных значениях. Термин должен иметь строго определенное значение, т. е. быть точным и не допускать неясности или
противоречивости толкования. Для уточнения варианта перевода
полезно выяснить, как этот термин переводится на другие языки и
с других языков на русский язык.
2. Если в тексте встретились иностранные собственные имена,
выясните их правописание. Транслитерировать их с русского недопустимо. Какие-то из этих имен можно найти в списке цитированной литературы. Имеет смысл внимательно прочесть иностранные
библиографические ссылки. Они могут помочь, например, в переводе заглавий статей, так как заглавия часто содержат термины,
которые могут оказаться полезными в процессе перевода.
3. Закончив работу с терминами, определив вариант перевода
термина, перечитайте текст еще раз, чтобы не осталось неясностей.
4. Все англо-американские меры веса, длины и т. д. должны
быть пересчитаны на метрические эквиваленты.
5. Если в тексте встретились чертежи, они полностью сохраняются в переводе. Надписи на чертежах делаются по-русски.
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6. Остерегайтесь буквализмов! Даже, если слово есть в словаре,
и этот вариант Вам кажется подходящим, проверьте этот вариант
перевода на сочетаемость с ближайшим лексическим окружением
в тексте перевода. Нередки случаи, когда Вам может понадобится
другой вариант перевода.
7. Помните про «ложных друзей переводчика», интернационализмы и «похожие» слова. Например, когда английский и русский
термины или их компоненты совпадают по форме, но отличаются
по значению и употреблению.
8. При переводе каждого предложения, подумайте, с какого слова, с какой части фразы начать. Далеко не всегда это будет первое
слово предложения исходного текста!
9. После окончания перевода – желательно не в тот же день –
перечитайте переведенный текст фразу за фразой и убедитесь, что
его смысл будет ясен читателю. Если предложение слишком громоздкое, если непонятно, что к чему относится, переделайте предложение.
10. Проверьте текст перевода на наличие смысловых ошибок,
орфографических и пунктуационных ошибок. Обязательно выверяйте таблицы, формулы, схемы, подписи под иллюстрациями,
надписи над схемами, библиографические списки.
11. Помните о способах и возможностях перевода средств выражения модальности.
12. Недопустимы выражения разговорного стиля. Стиль перевода должен соответствовать научному стилю изложения, принятому
в русской научной традиции.
13. Важно! Текст перевода должен быть понятным и написан
в строгом соответствии с нормой языка перевода. Предложения
должны быть четко и ясно сформулированы, не допускать двусмысленности толкования или непонимания смысла.
Помните! Нет ошибок «важных» и «несущественных». Любая ошибка, особенно, если она повторяется в тексте перевода несколько раз, снижает качество перевода. Это относится не только
к ошибкам в передаче смысла, но и к ошибкам в правописании,
чередовании однородных членов предложения, расстановке знаков
препинания.
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CHAPTER II
ТЕХНИКА ПЕРЕВОДА
Вводные замечания
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Стиль приведенных текстов – формально-логический и при
переводе его следует сохранять, так как данной литературе свойственно точное и четкое изложение материала, упор делается на логическую сторону повествования. Отступление от привычного способа изложения материала затрудняет понимание фактов. Именно
формально-логический стиль обеспечивает наиболее полную и эффективную информацию.
Данные тексты насыщены терминами и терминологическими
словосочетаниями, а также лексическими конструкциями и сокращениями. До начала работы над текстом не лишним будет уточнить вопросы терминологии и ознакомиться с аналогичной документацией.
Грамматической особенностью данных текстов является большое количество причастий, инфинитивов, герундиальных оборотов. Герундий может вступать в качестве дополнения и обстоятельства, а также подлежащего; причастие в предложении обладает
функциями определения и обстоятельства. Следует упомянуть про
независимый причастный оборот, который представляет собой сочетание существительного в общем падеже или местоимения в именительном падеже и причастия (причем существительное или местоимение не является подлежащим в предложении). В конструкции может использоваться как причастие I, так и причастие II.
Часто можно встретить эллиптическую (усеченную) форму независимого причастного оборота, в котором отсутствует причастие
being и который часто начинается с предлога with. Смысл такого
предложения можно передать при помощи деепричастного оборота, начинающегося со слов «имея/обладая/приобретя» или «не
имея». При наличии отрицания такую конструкцию можно также
перевести при помощи слов «хотя, несмотря на то, что...».
Стоит обратить внимание на то, что в английском тексте преобладают личные формы глагола, тогда как русскому научному стилю свойственны безличные или неопределенно-личные обороты.
Личные формы глагола часто употребляются в страдательном
залоге, поэтому при переводе нередко прибегают к замене их иными средствами выражения.
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Тема 1. Стратегии перевода
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Важную текстообразующую роль играют служебные слова, создающие логические связи между отдельными элементами высказывания.
Данным текстам присущи сложные и осложненные предложения. Для логического выделения отдельных смысловых элементов
используется инверсия.
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1. Способы перевода.
2. Текст как объект перевода: метод отражения действительности;
ведущая функция; тональность; тип мышления.
3. Типы информации.
4. Переведите следующий текст, используя семантический способ перевода с элементами коммуникативно-прагматического и
буквального перевода.
5. Частные языковые трудности.
Text 1. Development of Modern Mathematics
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Research in the structural (topological) aspect of the real number
system gave rise to one of the most fundamental concepts of modern
mathematics – a concept which itself forms one of the characterizing
features of modern mathematics, namely, the notion of ‘set’. That
the notion was about to come into full flower during the latter part
of the XIX century may be seen in the works of Riemann, Dedekind,
Weierstrass, and Cantor. Weierstrass gave an example of a function
continuous over the real numbers but having no derivative at any point.
Both Riemann and Cantor investigated properties of functions defined
by Fourier – series expansions which exhibited such curious properties
as to be given the epithet ‘pathological’ (although modern set theory
and topology have taught us that they are not deserving such a label).
It became clear that the lack of a more penetrating description of the
intuitively conceived structure of the real number system was a veritable
scandal in mathematics. Only by making a more precise analysis of the
structure as a whole – what might be termed a ‘global’ analysis like
that exemplified in Dedekind’s theory of ‘cuts’, as opposed to studying
the properties of individual numbers – could a better approximation be
achieved. And thus, out of sheer necessity, the theory of sets was born.
As one looks back it seems amazing that so much was accomplished by
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the analysts of the XVII–XIX centuries without any firm foundation in
a more clearly defined real number system.
The real power of the theory of sets, and the circumstances that gave
it ultimately its key position in modern mathematics, may be found in
the extension of G. Cantor’s researches into the real number continuum,
which carried him on into an investigation of the nature of number. It
is chiefly to elucidate the nature of number that the teacher uses the set
concept in modern systems of teaching arithmetic. For by a consideration
of sets and operations with them (union, intersection, etc.) one can
arrive at a much better intuitive understanding of the nature of the
natural numbers and operations with them. Even pioneering logicians
such as Russell, who (vainly) tried to establish that Mathematics is only
an extension of Logic, seized upon the set concept as the most suitable
tool for the definition of the cardinal and ordinal numbers.
With the foundational works of Dedekind, Weierstrass, Frege,
Peano and Cantor it seemed that the secure and definitive foundations
of Mathematics had been attained. This was not the case, however.
All seemed right in this ‘best of all possible (mathematical) worlds’.
However, the feeling of confidence in the new foundations and
mathematical rigour received a blow around the beginning of the
XX century – a blow that gradually assumed the proportions of a
crisis. Usually Mathematics has benefited from its crises; a classical
case is the crisis in Greek mathematics resulting from the discovery of
incommensurable line segments and the paradoxes of Zeno.
Since the philosophy of the Pythagorean School was that whole
numbers, or whole numbers in ratio, were the essence of all existing
things (Numbers rule the Universe!) the discovery of incommensurables
was regarded as a ‘logical scandal’. The Pythagoreans tried to suppress
the discovery but the truth cannot be suppressed. Zeno of Elea was
famous for his paradoxes. A paradox is a statement which seems
absurd but which is actually well founded. Zeno’s paradoxes concern
the structure of the continuum, infinite divisibility and the concept of
motion. Zeno’s paradoxes were not the only precedent in the history
of scientific thought. Paradoxes – the genuine ones – arise whenever
the conceptual apparatus of science is more or less radically revised.
They are brought about by 1) the new conceptual apparatus that is not
quite satisfactorily constituted; 2) by the use of old terminology not
sufficiently adopted to the new concepts. Paradoxes – mathematicians
claim – must be eliminated by any means: the reconstruction of the new
conceptual apparatus or by a revision of scientific terminology. The
mathematical concept of the infinite was the source of many paradoxes.
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The prospect of an infinite process disturbed ancient mathematicians
for here they were confronted with a crisis. They were unable to answer
the subtle paradoxes Zeno of Elea proposed at about the same time that
the devastating discovery of incommensurables was made. Aristotle
and other Greek philosophers sought to answer the paradoxes of Zeno,
but the replies were so unconvincing that mathematicians concluded
that it was best to avoid infinite processes altogether. An analogous
‘great crisis of foundations’ (1900–1930) occurred with the revelation
of contradictions in Cantor’s intuitive set theory. In 1897 Cantor
discovered a contradiction in his theory when he had failed to find
an infinite set with cardinality between No and C, that is, an infinite
set of points on a line segment that is not equivalent to the whole
segment, and also, not equivalent to the set of natural numbers. Cantor
conjectured that no such set exists and the problem acquired the title
the ‘continuum hypothesis’. As it had happened before the ‘continuum
hypothesis’ revealed to the mathematicians unsuspected complexities
in a seemingly rigorous Cantor’s set theory, they began to doubt
whether it could serve as a secure foundation for mathematics. The
discovery of contradictions in set theory by Russell and Burali-Forti
around 1900 precipitated more soul-searching than Zeno’s paradoxes.
The new foundations constructed by the XIX century mathematicians
had developed a fissure that raised a question as to how rigorous the
newly found rigour of the set theory really was.
As a response to ‘paradoxes’ in Cantor’s intuitive set theory, Ernst
Zermelo founded in 1908 the axiomatic set theory with a notion of a
set being regarded simply as an undefined object satisfying a given
list of axioms. Further developments of the axiomatic set theory by
the leading mathematicians and logicians resulted in the creation
of the abstract set theory in which the symbols for ‘set’, ‘union’,
‘intersection’ and so on may be rearranged only according to a given
list of axioms and rules of inference. The abstract set theory did not
solve the problem of sound foundations for mathematics. Although
analysts, algebraists, and geometers continued to develop their
theories, seemingly oblivious of the situation in the foundations, the
crisis began to claim the attention of more and more mathematicians.
The philosophy propounded by Kronecker (1823–1891) was recalled.
Kronecker had decried the ‘infinitistic’ methods underlying the work
of Weierstrass, Cantor, and the other creators of the new foundations.
He maintained that ‘real’ mathematics was only that which could be
derived from the natural numbers (‘intuitively given’), using only
constructive methods. Non-constructive existence proofs (for example,
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proving that every algebraic equation has a root by showing that
assumption of nonexistence of such a root leads to contradiction) were
to him worthless, and by his criteria only the rational numbers (or,
more generally, the algebraic numbers), not the general real numbers
were admissible. The controversy between Cantor and Kronecker was
clouded with personal animosity, but at its roots were sharply divergent
views on the philosophy of mathematics between constructivists
(Kronecker) and formalists (Hilbert). So severe were Kronecker’s
attacks on his work that Cantor began to doubt himself, became
depressed and suffered mental breakdown. After the contradictions in
set theory were found, the Dutch mathematician L. E. Brouwer took
up Kronecker’s philosophy and developed it further, gathering about
him a small but an influential group of co-believers. However, it soon
became evident that to adhere faithfully to this doctrine would result
in having to abandon most of the new foundations.
Leaders among those who refused to accept such an extreme ‘cure’
were Russell, Whitehead, and Hilbert. Taking their cue from the
late XIX-century logicians Russell and Whitehead sought a secure
foundation in the tautologies of elementary logic, together with
implication rules that seemed safe from error. Although their work
Principia Mathematica was never completed, it went far enough to
show the necessity for bringing in axioms, concerning the infinite and
the hierarchy of types. These axioms, if not of questionable validity at
least, could not be considered purely ‘logical’ in character.
Hilbert and his students did not begin actively carrying out their
programme (called ‘formalism’) until about the 1920s, and they were
obviously influenced by the findings of Russell and Whitehead as well
as the doctrines of Brouwer. They took the attitude that safety can
be secured by acting as though mathematics were developed purely
formally; the axioms and theorems were exhibited as pure formulas (in
much the same way as in Principia Mathematica) devoid of meaning
for the purposes of the investigation, while the methods of deriving
theorems (new formulas) were confined to such as are purely finitistic.
If a formula having the form ‘both F and ~ not-F hold’ (i.e., F~F) is
encountered, then one has contradiction; hence, the purpose was to
show that such a formula could not be derived. That this programme,
too, could not be carried to completion became evident in the 1930s,
following Gödel’s famous theorem of 1931.
It is characteristic of science that what may seem like failure often
turns out to be the opposite. It is as important to show what cannot be
done as to show what can be done. In the sense that their programmes
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could not be carried to successful completion, one may say that the
‘logistic’ school (Russell) and the ‘formalist’ school (Hilbert and his
students) were failures. But from the standpoint of their influence
on later development, they were quite successful, for they had given
the major impulse for the creation of modern Mathematical Logic,
now a recognized field of mathematics. The resulting impact on the
modern point of view on the nature of modern mathematics was to be
considerable. The crisis had not been resolved, but it had not stultified
mathematics any more than had the earlier crises; and, as before, the
ultimate influence was beneficial.
Тема 2. Единицы перевода и членения текста
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1. Правила сегментации текста для перевода.
2. Единицы перевода: контекстуальные и внетекстовые.
3. Лексико-синтаксические особенности текста, доминанты
перевода.
4. Переведите следующий текст, установите систему контекстуальных и внетекстовых зависимостей для единиц перевода и преобладающий принцип членения. Какие комментарии могут быть
полезны при переводе?
5. Частные языковые трудности.
Text 2. The Axiom of Choice
Systems of infinitely many simultaneous correspondences are a
matter of course in current mathematics, or may even be considered
as characteristic of mathematics. Within the framework of the logical
and mathematical procedures which were usual and recognized up to
the end of the XIX century, one is not permitted to take infinitely many
steps in choosing arbitrary elements which are not determined by a
definite law. This exclusion of infinity of choices was based by some
critics on the argument that any logical procedure must be brought to an
end within a finite length of time which would apparently be impossible
in this case. Yet, this argument is hardly tenable, for the process of
thinking should be regarded as instantaneous and not as taking a
definite length of time. A deeper analysis shows that procedures
involving infinitely many arbitrary steps have been avoided in the past
not for the reason mentioned above, but because these procedures were
considered to be meaningless, not merely non-constructive.
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Imagine a denumerable set whose elements are pairs of shoes: a first,
second,..., n-th,... pair for every positive integer n. Is the set of all these
pairs equivalent to the set of all shoes contained in the pairs? The answer
is, of course, in the affirmative. We may assign to the first pair the left
shoe of the first pair; to the second pair the right shoe of the first pair;
to the third pair the left shoe of the second pair, and so on. Then, the left
shoe of the п-th pair corresponds to the (2n-l)st pair, the right shoe of the
n-th pair to the (2n)th pair. Evidently this rule yields a mapping of the set
of all pairs onto the set of all shoes, hence the sets are equivalent; there
are No pairs and No shoes. However, the situation changes completely if
we consider infinitely many pairs of stockings instead of pairs of shoes.
The difference lies in the fact that manufactures produce identical
stockings for both feet. Certainly, we may start by assigning to the first
pair an arbitrary stocking of this pair and to the second pair the other
stocking of the first pair, etc. Yet, now we can continue this procedure
only finitely many times, unless we are prepared to admit an infinity of
arbitrary choices of stockings out of the pairs of stockings. So long as
we exclude this, in accordance with mathematical tradition throughout
history, we cannot determine whether the set of all stockings has the
same cardinal No as the set of all pairs.
Of course, the significance of this example is merely expositional,
not scientific. Nevertheless, this is an example in which an important
problem is unsolvable without the use of an infinity of choices. Thus there
emerges a new principle of logic and mathematics, which was discovered
only at the beginning of the XX century, and which is indispensable
for proving many important statements in various branches of modern
mathematics. This principle is called the Axiom of Choice (after Zermelo,
who first introduced it explicitly in 1904), or the multiplicative principle
(after Russell, who found a better formulation in 1906).
Axiom of Choice
If 5 is a disjoint set of nonempty sets, i. е. such that any two
members of S have no common element, then there exists at least one
set С which contains a single element out of each element of 5.
Any such set С is called a choice set of S. By means of this formulation
we have eliminated the function concept and arbitrary ‘choices’ and the
problem has been reduced to the existence of sets. The axioms of set
theory alone should determine what sets do actually exist. As shown by
Zermelo (1908), the general axiom of choice can be derived from the above
axiom by constructive procedures which are generally recognized in
Logic and Mathematics. The history of the axiom of choice is interesting
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and may in some respects be compared with the most famous axiom in
Mathematics, Euclid’s parallel axiom. In the 1880s and 1890s Cantor
had already in the proof of well-ordering theorem used an argument
which is logically equivalent to the axiom of choice; yet he had done so
implicitly and was not conscious of using a new principle.
Between 1904–1910 papers rejecting the axiom of choice were
published in many leading mathematical journals. Poincare (1910)
remarked: “This dispute about Zermelo’s ingenious axiom is rather
strange; one side rejects the axiom of choice but accepts its proof, the
other accepts the axiom but not the proof of the theorem”. Poincare
himself belonged to the ‘other’, who were a small minority. Many
mathematicians still take a negative attitude towards the axiom of
choice. Many objections against the axiom of choice are based on
misunderstanding and are therefore void, in as much as they ignore the
purely existential nature of its statement. Because of this existentiality
it is quite natural and to be expected that one cannot deduce from the
well-ordering theorem where in the series of cardinals the cardinal
N of the continuum is to be found. This question constitutes the
continuum hypothesis; to solve it, we need a constructive formation of
the corresponding choice set. As a matter of fact, except for a partial
(though profound) result of Gödel in 1938–1940, the attempts made
by outstanding mathematicians since the 1880s to solve this problem
remained unsuccessful until 1963. It is psychologically understandable
that the mistrust toward the axiom of choice has deepened, because it is
of no help in the solution of the continuum problem. In 1963 P. J. Cohen
showed in an ingenious proof that the problem is unsolvable; that is
to say, various positions in the series of alephs for the cardinal of the
continuum are compatible with the axioms of set theory.
Yet, only those mathematicians and philosophers who in principle
acknowledge only constructive, not existential, procedures are entitled
to reject the axiom of choice for such reasons; among these, in particular,
are intuitionistic and neo-intuitionistic schools. However, insofar as
they keep to their principles, they restrict the methods of mathematics
to such an extent that outside of arithmetic only narrow fields can
be investigated. Actually, psychological rather than logical reasons
played a leading part in the rejection of the axiom of choice. Prominent
among them was the aversion to the well-ordering theorem, which
was considered too strong a statement that yielded too few ‘practical’
results. On the other hand, most critics had to admit that if the axiom
of choice were accepted they could discover no shortcoming in Zermclo’s
proof. Hence the only way out is the rejection of the axiom of choice.
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It is a strange phenomenon, which rarely occurs in the exact
sciences, that discussions become stagnant over a period of many
decades. Yet, this is what happened to the axiom of choice, and hardly
any fundamentally new ideas have emerged in the discussions. On the
other hand, the fact that the axiom of choice is compatible with the
other principles of set theory was proved by Gödel in several profound
papers since 1938. The same papers also deal with the continuum
problem. Comparing G6-del’s result with the situation described,
we see that the main objective was either a proof that the negation
of the choice axiom is also compatible, or a proof that the negation
is contradictory. The situation is somewhat similar to that which
had existed in geometry with respect to the axiom of parallels. The
anologue of absolute geometry in the present case is that part of set
theory which can be treated without reference to the axiom of choice.
Finally, we should outline the significance and the applications of
the axiom of choice in various branches of mathematics. The axiom
is used throughout analysis especially in the theory of real functions
as well as in set theory and in wide domains of topology. As far as set
theory is concerned, the arithmetic of transfinite cardinals, ordinals,
and order types is essentially based upon the choice axiom. Its
indispensability in abstract algebra is obvious. It should be stressed
again that the axiom of choice is needed for a complete analysis of the
concepts of finite set and finite number (cardinal, ordinal). Only by
using the axiom of choice can we prove that any set or cardinal is either
finite or infinite. Hence any cardinal either equals No or is greater
than No. Thus although the axiom of choice has entered mathematics
only recently, it has proved indispensable for the structure and
development of Mathematics.
Тема 3. Лексические приемы перевода
1. Переводческая транскрипция.
2. Калькирование.
3. Лексико-семантические модификации.
4. Переведите следующий текст, обращая внимание на межалфавитные соответствия при передаче имен собственных. Составьте
для данного текста двуязычный терминологический словник, отметив в нем единицы, транскрипция и/или транслитерация которых неуместна.
5. Частные языковые трудности.
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Text 3. Number Continuum
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An infinite set is defined to be one that can be put into one-to-one
correspondence with a part of itself whereas a finite set cannot be.
Thus the set of positive integers is infinite because there is a one-to-one
correspondence between the whole class and the even numbers which
are only a part of that class. Can every infinite collection be put into
one-to-one correspondence with the positive integers? By no means.
The set of all numbers between 0 and 1, a collection that includes whole
numbers, fractions, and irrationals, cannot be put into one-to-one
correspondence with the positive integers. Hence the two collections
cannot be equal in number. The number of numbers between 0 and 1 is
represented by the transfinite number С. Accordingly, any collection
of objects in one-to-one correspondence with all the numbers between
0 and 1 must also contain С objects.
An example of a set of С objects is furnished by the points on a line
segment. Consider a line and a fixed point 0 on that line. Let us attach
to each point on the line the number that expresses the distance of that
point from 0, with the added condition that distances to the right of 0 are
to be positive and those to the left, negative. There is, then, a one-to-one
correspondence between the numbers from 0 to 1 and the points on the
line to which the numbers are attached. This implies that the number of
these points is C. Stated arithmetically, the set of positive real numbers
is in one-to-one correspondence with the real numbers between 0 and 1
and hence the number of positive real numbers is C. The number of points
on a line segment and the number of points on an entire half-line are the
same despite the fact that one is infinite in length and the other is just
one unit long. Actually a line segment could have been two units long or
any other finite length and our result would have been the same. Hence
the number of points on any line segment is always С. This conclusion,
like others, seems to violate our intuition. What right have we, however,
to expect more points on the larger of two line segments? What precise
knowledge about points and lines supports such an expectation? Euclidean
geometry does require that any line segment contain an infinite number
of points since any line segment, however small, can be bisected; but this
geometry says nothing about the number of points on a segment. Cantor’s
theory does, and it informs us that any two line segments, regardless of
their lengths, possess the same number of points. This conclusion is not
only logically sound but it also permits us to dispose of some perplexing
questions about the nature of space, time and motion that had bothered
philosophers for over two thousand years.
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Our intuitions of space and time suggest that any length and any
interval of time, no matter how small, may be further subdivided. The
mathematical formulation of these concepts takes into account this
property. For example, any line segment may be bisected by a precise
Euclidean construction. The mathematical line contains additional
properties. Any length consists of points, each of which has no length;
moreover, these points are related to each other as are the numbers of
the number system. Now between any two numbers there is an infinite
number of other numbers; for example, between 1 and 2 there are 1/2,
1/4, 1/8 and so on. Hence, between any two points on a line there is an
infinite number of other points. Similarly, the mathematical concept
of time regards time as consisting of instants each with no duration,
which follow each other as do the numbers of the number system. Thus
12 o’clock is an instant and there is an instant corresponding to any
number of seconds after 12 o’clock that we can name. It is true, then,
for instants as for points on a line that there is an infinite number of
instants between any two.
Тема 4. Грамматические (морфологические)
приемы перевода
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1. Различия грамматического строя английского и русского
языков.
2. Морфологические преобразования в условиях сходства форм.
3. Морфологические преобразования в условиях отличия форм.
4. Переведите текст, применяя полный или частичный перевод
английских форм, имеющих прямые соответствия в русском
языке, и употребляя соответствующие преобразования при их
несовпадении.
5. Частные языковые трудности.
Text 4. Zeno’s Paradoxes
There are difficulties in Maths concepts of length and time which
were first pointed out by the Greek philosopher Zeno, but which can
now be resolved by use of Cantor’s theory of infinite classes. We’ve
just considered a formulation by Betrand Russell of Zeno’s Achilles
and the tortoise paradox.
Part of this argument is sound. We must agree that from the start
of the race to the end the tortoise passes through as many points as
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Achilles does, because at each instant of time during which they run
each occupies exactly one position.
Hence, there is a one–to–one correspondence between the infinite
set of points run through by the tortoise and the infinite set of points
run through by Achilles. The assertion that because he must travel a
greater distance to win the race Achilles will have to pass through more
points than the tortoise is not correct, however, because as we know the
number of points on the line segment Achilles must traverse to win the
race is the same as the number of points on the line segment the tortoise
traverses. We must notice that the number of points on a line segment
has nothing to do with its length. It is Cantor’s theory of infinite classes
that solves the problems and saves our math theory of space and time.
For centuries mathematicians misunderstood the paradox. They
though it merely showed its poser Zeno was ignorant that infinite
series may have a finite sum. To suppose that Zeno did not recognize
it is absurd. The point of the paradox could not be appreciated until
Maths passed through the third crisis. Cantor holds that it does make
sense to talk of testing infinity of cases. The paradox is not that
Achilles doesn’t catch the tortoise, but that he does.
In his fight against the infinite divisibility of space and time Zeno
proposed other paradoxes that can be answered satisfactorily only
in terms of the modern Maths conceptions of space and time and the
theory of infinite classes. Consider an arrow in its flight. At any instant
it is in a definite position. At the very next instant, says Zeno, it is
in another position. There is no next instant, whereas the argument
assumes that there is. Instants follow each other as do numbers of the
number system, and just as there is not next larger number after 2
and 2:2, there is no next instant after a given one. Between any two
instants an infinite number of others intervene.
But this explanation merely exchanges one difficulty for another.
Before an arrow can get from one position to any nearby position, it
must pass through an infinite number of intermediate positions, one
position corresponding to each of the infinite intermediate instants.
To traverse one unit of length an object must pass through an infinite
number of positions but the time required to do this may be no more
than one second; for even one second contains an infinite number
of instants. There is, however, a greater difficulty about motion of
the arrow. At each instant of its flight the tip of the arrow occupies
a definite position. At that instant the arrow cannot move, for an
instant has no duration. Hence, at each instant the arrow is at rest.
Since this is true at each instant, the moving arrow is always at rest.
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This paradox is almost startling; it appears to defy logic itself. The
modern theory of infinite sets makes possible an equally startling
solution. Motion is a series of rests. Motion is nothing more than a
correspondence between positions and instants of time, the positions
and the instants each forming an infinite set. At each instant of the
interval during which an object is in “motion” it occupies a definite
position and may be said to be at rest.
The Maths theory of motion should be more satisfying to our
intuition for it allows for an infinite number of “rests” in any interval
of time. Since this concept of motion also resolves paradoxes, it should
be thoroughly acceptable. The basic concept in the study of infinite
quantities is that of a collection, a class, or a set of instants in time.
Unfortunately, this seeming simple and fundamental concept is beset
with difficulties that revealed themselves in Zeno’s paradoxes.
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Тема 5. Синтаксические приемы перевода
(на уровне словосочетаний)
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1. Особенности синтаксической сочетаемости в русском и английском языках.
2. Синтаксические преобразования на уровне словосочетаний.
3. Особенности перевода английских многочленных атрибутивных словосочетаний и русских субстантивных словосочетаний.
4. Особенности перевода заголовков.
5. Переведите текст, выделите словосочетания, которые подлежат преобразованию. Предложите разные варианты перевода.
6. Частные языковые трудности.
Text 5. Integral and Differential Calculus
Calculus is a branch of mathematics using the idea of a limit and
generally divided into two parts: integral and differential calculus.
Integral and differential calculus can be used for finding areas,
volumes, lengths of curves, centroids, and moments of inertia of curved
figures. It can be traced back to Eudoxus of Cnidus and his method
of exhaustion (c. 360 ВС). Archimedes (in The Method) developed a
way of finding the areas of curves by considering them to be divided
up by many parallel line segments, and extended it to determine the
volumes of certain solids; for this he is sometimes called the father of
the integral calculus.
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In the early 17th century interest again developed in measuring
volumes by integration methods. Kepler used a procedure for finding
the volumes of solids by taking them to be composed of an infinite set of
infinitesimally small elements (Measurement of the Volume of Barrels,
1615). These ideas were generalized by Cavalieri in his Geometria
Indivisibilibus Continuorum Nova (1635), in which he used the idea
that an area is made up of indivisible lines and a volume of indivisible
areas, i.e., the concept used by Archimedes in The Method. Cavalieri
thus developed what became known as his ‘method of indivisible’. John
Wallis, in Arithmetics Infmitorum (1655) arithmetized Cavalieri’s
ideas. In this period infinitesimal methods were extensively used to
find lengths and areas of curves.
Differential calculus is concerned with the rates of changes of
junctions with respect to changes in the independent variable. It came
out of problems of finding tangents to curves, and an account of the
method is published in Isaac Barrow’s Lectiones Geometricae (1670).
Newton had discovered the method (1665-66) and suggested that
Barrow include it in his book. In his original theory Newton regarded
a function as a changing quantity – a fluent – and the derivative or
rate of change he called a fluxion. The slope of a curve at a point was
found by taking a small element at the point and finding the gradient
of a straight line through this element. The binomial theorem was used
to find the limiting case, i.e., Newton’s calculus was an application of
infinite series. He used the notation x’ and y’ for fluxions and Xм and
y” for fluxions of fluxions. Thus, if x * f(t), where x is the distance and
t – the time for a moving body, then x’ is the instantaneous velocity
and x” – the instantaneous acceleration. Leibniz had also discovered
the method by 1676 publishing it in 1684. Newton did not publish until
1687. A bitter dispute arose over the priority for the discovery. In fact
it is now known that the two made their discoveries independently and
that Newton made his about ten years before Leibniz, although Leibniz
published first. The modern notation of dy/dx1 and the elongated s for
integration is due to Leibniz.
From about this time integration came to be regarded simply as
the inverse process of differentiation. In the 1820s Cauchy put the
differential and integral calculus on a more secure footing by using
the concept of a limit. Differentiation he defined by the limit of a ratio
and the integration by the limit of a type of sum. The limit definition
of integral was made more general by Riemann.
1 dx is read “differential of x”; dy/dx is read “derivative of y with respect to x”
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In the 20th century the idea of an integral has been extended.
Originally integration was concerned with elementary ideas of measure
(i.e., lengths, areas and volumes) and with continuous functions.
With the advent of set theory functions came to be regarded as oneto-one mappings, not necessarily continuous, and more general and
abstract concepts of measure were introduced. Lebesque put forward a
definition based on the Lebesque measure of a set: similar extensions
of the concept have been made by other mathematicians.
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calculus – исчисление;
centroid – центр массы (тяжести);
continuous function – непрерывная функция;
curve – кривая;
derivative – производная;
elongated – удлиненный;
fluent – переменная величина, функция;
fluxion[‘flΛk∫(ə)n] – флюксия, производная;
infinitesimal [,infini’tesim(ə)l] method – метод бесконечно малых
величин;
limit of a ratio – предел отношения;
limiting case – предельный случай;
one-to-one mapping – однозначное соответствие, отображение;
solid – твердое тело;
tangent [‘tændз(ə)nt]– касательная;
velocity [vi’losəti]– скорость, быстрота.
Тема 6. Синтаксические приемы перевода
(на уровне предложений)
1. Актуальное членение предложения и различия в порядке
слов русского и английского предложения.
2. Синтаксические преобразования на уровне предложений.
3. Функциональная замена как ведущая синтаксическая трансформация. Типы функциональной замены синтаксических единиц.
4. Переведите текст, проанализируйте взаимосвязь между синтаксическими преобразованиями и необходимостью лексико-семантических приемов.
5. Частные языковые трудности.
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Text 6. The Differential Calculus
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No elementary school child gets a chance of learning the differential
calculus, and very few secondary school children do so. Yet I know
from my own experience that children of twelve can learn it. As it is a
mathematical tool used in most branches of science, this forms a bar
between the workers and many kinds of scientific knowledge. I have no
intention of teaching the calculus, but it is quite easy to explain what it is
about, particularly to skilled workers. For a very large number of skilled
workers use it in practice without knowing that they are doing so.
The differential calculus is concerned with rates of change. In
practical life we constantly come across pairs of quantities which are
related, so that after both have been measured, when we know one, we
know the other. Thus if we know the distance along the road from a fixed
point we can find the height above sea level from a map with contour.
If we know a time of day we can determine the air temperature on any
particular day from a record of a thermometer made on that day. In such
cases we often want to know the rate of change of one relative to the other.
If x and у are the two quantities then the rate of change of у relative
to x is written dy/dx. For example, if x is the distance of a point on
a railway from London, measured in feet, and у the height above sea
level, dy/dx is the gradient of the railway. If the height increases by
1 foot while the distance x increases by 172 feet, the average value of
dy/dx is 1/172. We say that the gradient is 1 to 172. If x is the time
measured in hours and fractions of an hour, and v the number of miles
gone, then dy/dx is the speed in miles per hour. Of course, the rate of
change may be zero, as on level road, and negative when the height is
diminishing as the distance x increases. To take two more examples,
if x the temperature, and у the length of a metal bar, dy/dx–:–у is
the coefficient of expansion, that is to say the proportionate increase
in length per degree. And if x is the price of commodity, and у the
amount bought per day, then –dy/dx is called the elasticity of demand.
For example, people must buy bread, but cut down on jam, so the
demand for jam is more elastic than that for bread. This notion of
elasticity is very important in the academic economics taught in our
universities. Professors say that Marxism is out of date because Marx
did not calculate such things. This would be a serious criticism if the
economic ‘laws’ of 1900 were eternal truths. Of course Marx saw that
they were nothing of the kind and ‘elasticity of demand’ is out of date
in England today for the very good reason that most commodities arc
controlled or rationed.
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The mathematical part of the calculus is the art of calculating dy/
dx if y has some mathematical relations to x, for example is equal to
its square or logarithm. The rules have to be learned like those for the
area and volume of geometrical figures and have the same sort of value.
No area is absolutely square, and no volume is absolutely cylindrical.
But there are things in real life like enough to squares and cylinders to
make the rules about them worth learning. So with the calculus. It is not
exactly true that the speed of a falling body is proportional to the time it
has been falling. But it is close enough to the truth for many purposes.
The differential calculus goes a lot further. Think of a bus going up
a hill which gradually gets steeper. If x is the horizontal distance, and
у the height, this means that the slope dy/dx is increasing. The rate
of change of dy/dx with regard to y is written as d2y/dx2. In this case
it gives a measure of the curvature of the road surface. In the same
way if x is time and distance d2y/dx2, is the rate of change of speed
with time, or acceleration. This is a quantity which good drivers can
estimate pretty well, though they do not know they are using the basic
ideas of the differential calculus.
If one quantity depends on several others, the differential calculus
shows us how to measure this dependence. Thus the pressure of a gas
varies with the temperature and the volume. Both temperature and
volume vary during the stroke of a cylinder of a steam or petrol engine,
and the calculus is needed for accurate theory of their action.
Finally, the calculus is a fascinating study for its own sake. In
February 1917 I was one of a row wounded officers lying on stretchers
on a steamer going down the river Tigris in Mesopotamia. I was reading
a mathematical book on vectors, the man next to me was reading one on
the calculus. As anti-doles to pain we preferred them to novels. Some
parts of mathematics are beautiful, like good verse or painting. The
calculus is beautiful, but not because it is a product of ‘pure thought’.
It was invented as a tool to help men to calculate the movement of stars
and cannon balls. It has the beauty of really efficient machine.
Arthur Schopenhauer, The World as Will and Representation
Тема 6. Синтаксические приемы перевода
(на уровне предложений)
1. Актуальное членение предложения и различия в порядке
слов русского и английского предложения.
2. Синтаксические преобразования на уровне предложений.
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Text 6. The Derivative Defined
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3. Функциональная замена как ведущая синтаксическая трансформация. Типы функциональной замены синтаксических единиц.
4. Переведите текст, проанализируйте взаимосвязь между синтаксическими преобразованиями и необходимостью лексико-семантических приемов.
5. Частные языковые трудности.
Δy
f (x + Δx) - f (x)
= Δlim
x
®
0
Δx
Δx
(1)
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f ¢(x) = Δlim
x ®0
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The notion of the derivative, alongside with the notion of the
integral, is the most important in mathematical analysis.
The derivative of a function f at a point x is defined as the limit to
which tends the ratio of the increment Δy of the function at that point
to the corresponding increment Δx of the argument as Δx tends to zero.
The derivative is usually denoted in the following way:
df (x) dy
are also widely used.
dx dx
Δy
Δy
For any fixed x the quantity
is a function of Δx : ϕ(Δx) =
Δ
x
Δ
x
(where Δx is not equal to 0).
For the derivative of f at a point x to exist, it is necessary that the
function f be defined in certain neighborhood of the point x including
the point x itself. Then the function (Δx) is defined for all sufficiently
small Δx different from zero, i.e. satisfying an inequality 0 < Δx < δ
where δ is a sufficiently small positive number.
Of course limit (1) exists not for any function f defined in a
neighborhood of the point x. Usually, when we say that a function has
a derivative f’(x) at point x, it is implied that derivative is finite, i.e.
limit (1) is finite.
But it may occur that there exists an infinite limit (1) equal to +¥,-¥
or ¥. In such cases it is useful to say that the function f has at point x
an infinite derivative (1) (equal to +¥,-¥ or ¥ ) if in formula (1) it is
assumed that Δx tends to zero attaining only positive values Δx > 0, then
the corresponding limit (whenever it exists) is called the derivative on
the right of a function at a point x. We shall denote it as f’(x + ).
Analogously, limit (1), when x tends to zero running through
negative values (Δx > 0), is termed the derivative on the left of/at x
(denoted: f’(x-)).
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But other notations such as y ¢
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Of course to compute f’(x + ) (or f’(x-)) it is necessary that the
function f be defined at the point x and on the right of it in a certain
neighborhood (or at x and on the left of x).
Typical in this respect is the case when f is defined on a close interval
[a, b] and has a derivative at all interior points of this interval, i.e. at
the points of the open interval (a, b); as to the end points, it has a right
derivative at a, and a left derivative at b. In such cases we say that the
function f has both right and left derivatives at a point x and they are
equal to each other, then the function f is said to have a derivative at
x: f,(x + ) = f’(x-)s=f’(x).
But if right and left derivatives exist at x and they are not equal to
each other (f’(x + )≠f’(x-)), then the function f fails to have a derivative
at x.
Useful words:
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convergence – сходимость;
convergent series – сходящийся ряд;
convergent sequence – сходящаяся последовательность;
divergent series – расходящийся ряд;
domain – область;
finite sequence – конечная последовательность;
finite series – конечный ряд;
infinite sequence – бесконечная последовательность;
infinite series – бесконечный ряд;
limiting value – предельное значение;
lower limit – нижний предел;
upper limit – верхний предел.
Тема 7. Научный и технический функциональный стили.
Особенности, правила перевода
1. Типовые лингвистические характеристики и функциональные особенности научно-технического функционального стиля.
2. Основные расхождения языкового оформления текстов научно-технического функционального стиля в английском и русском
языках.
3. Жанры, составляющие информационное поле научно-технического функционального стиля.
4. Переведите текст. Проанализируйте, какие языковые средства, присущие научному стилю, присутствуют в нем?
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5. Примените прием транспозиции и превратите текст вашего
перевода в научно-популярный.
6. Частные языковые трудности.
Text 7. Topology
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We know that modern Maths is composed of many different
divisions. Despite its rigorousness topology is one of the most
appealing. Its study is today one of the largest and most important of
Maths activities. Although the study of polyhedron held a central place
in Greek geometry, it remained for Descartes and Euler to discover
the following fact: in a simple polyhedron let V denote the number of
vertices, E the number of edges, and F the number of faces; then always
V+F–E=2
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By a polyhedron is meant a solid, whose face consists of a number
of polygonal faces. In the case of regular solids all the polygons are
congruent and all the angles at vertices are equal. A polyhedron is
simple if there are no “holes” in it, so that its surface can be deformed
continuously into the surface of a sphere. There are of course, simple
polyhedra which are not regular and polyhedra which are not simple. It
is not difficult to check the fact that Euler’s formula holds for simple
polyhedra, but does not hold for non-simple polyhedra.
We must recall that elementary geometry deals with magnitudes
(lengths, angles and areas) that are unchanged by the rigid motions,
while projective geometry deals with the concepts (point, line,
incidence, and cross–ratio), which are unchanged by the still larger
group of projective transformations. But the rigid motions and the
projections are both very special cases of what are called topological
transformation: a topological transformation of one geometrical
figure A into another figure A’ is given by any correspondence P ↔
P’ between the points P of A and the points P’ of A’, which has the
following two properties:
1. The correspondence is biunique. This means to imply that to each
point P of A corresponds just one point P’ of A’ and conversely.
2. The correspondence is continuous in both directions. This
means that if we take any two point P, Q of A and move P so that the
distance between it and Q approaches zero (0), the distance between the
corresponding points P’, Q’ of A’ will also approach zero, and conversely.
The most intuitive examples of general topological transformations
are deformations. Imagine a figure such as a sphere or a triangle to
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be made from, or drawn upon, a thin sheet of rubber, which is then
stretched and twisted in any manner without tearing it and without
bringing distinct points into actual coincidence. The final position of
the figure will then be a topological image of the original. A triangle
can be deformed into any other triangle or into a circle or an ellipse,
and hence these figures have exactly the same topological properties.
But one cannot deform a circle into a line segment, nor the surface
of a sphere into the surface of an inner tube. The general concept of
topological transformation is wider than the concept of deformation.
For example, if a figure is cut during a deformation and the edges
of the cut sewn together after the deformation in exactly the same
way as before, the process still defines a topological transformation
of the original figure although it is not a deformation. Topological
properties (such as are given by Euler’s theorem) are of the greatest
interest and importance in many math investigations. They are, in a
sense, the deepest and most fundamental of all geometrical properties,
since they persist (continue to hold) under the most drastic changes of
shape. On the basis of Euler’s formula it is easy to show that there are
no more than five regular polyhedra.
Useful words:
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biunique correspondence – взаимнооднозначное соответствие;
drastic changes – значительные изменения;
edge – грань;
faces – края;
polyhedron – многогранник, подиэндроид;
rigid motions – движение жесткой структуры тела; движение неизменяемой системы;
solid – твердое тело;
vertex – вершина.
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CHAPTER III
ПРАКТИКА ПЕРЕВОДЧЕСКОГО АНАЛИЗА, ПЕРЕВОДА
И РЕДАКТИРОВАНИЯ БОЛЕЕ СЛОЖНЫХ ТЕКСТОВ
Text 1. OCR Technology
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Useful words:
ASCII – Американский стандартный код для обмена информацией.
GTK (Graphical Toolkit) сокращение от GIMP Toolkit (General
Image Manipulation Programme) – кроссплатформенная библиотека элементов интерфейса для создания графических оболочек.
GUI – Graphical User Interface.
ICR – Intelligent Character Recognition – интеллектуальное распознавание символов.
IDE – Integrated Development Environment – интегрированная
среда разработки ПО.
MDI – Multiple Document Interface – способ организации графического интерфейса пользователя, предполагающий использование оконного интерфейса, в котором большинство окон расположены внутри одного общего окна.
OPR – Optical Character Recognition – оптическое распознавание
символов.
RSS Bandit – RSS-канал бандит – сборщик новостей; приложение
для чтения каналов RSS и Usenet.
SDI – Single Document Interface – способ организации графического интерфейса приложений в отдельных окнах.
TDI – Tabbed Document Interface – многодокументный интерфейс с вкладками.
multiple fonts – шрифты различных типов;
proofread – исправлять, скорректировать; корректура.
Optical Character Recognition (OCR) – used extensively throughout
business and government – examines scanned bitmap images of
machine-printed text and translates the characters into ASCII text
files that can be edited. For instance, paper checks contain number
series written in machine print designed to minimize recognition
errors. These codes contain bank routing numbers, the holder’s
account numbers and other information required to process paper
transactions. Machine print conversion is largely a solved problem in
this application, as OCR software was included in the first commercial
systems that automated machine print text recognition.
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Optical Character Recognition (OCR) systems recognize only
machine print. Using pattern-matching technology, OCR translates the
shapes and patterns of machine-made characters into corresponding
computer codes. Though most advanced systems are able to recognize
multiple fonts, they can process only standard fonts such as Times
Roman and Arial. Once all characters in a given word are recognized,
the word is compared against a vocabulary of potential answers for the
final result.
Character recognition then segments lines of text or words into
separate characters that are recognized by the makeup of their
component shapes. Machine printed letters are evenly spaced across,
and up-and-down, a given page, allowing the OCR system to read the
text one character at a time. Segmentation into single characters
represents a critical recognition failure point for forms processing
organizations, because OCR recognition technology requires highquality images with excellent contrast, character and clarity. Any text
that is less than perfect will cause even the most sophisticated OCR
systems to return significant reductions in accuracy when processing
degraded images. For example, when characters break apart due to
poor image quality, or if multiple characters merge due to blurred or
dark backgrounds between them, recognition accuracy may be reduced
by as much as 20%.
The most commonly accepted OCR accuracy measurement is
represented by the percentage of characters correctly read on a given
page of text, and systems vary widely, achieving 95% to 99% accuracy.
But accuracy rates at anything below 100% can translate into huge
productivity losses. An entire application or verification process could
be compromised if even 5% of the data is either entered incorrectly or
misread. Therefore, OCR systems must have the ability to ‘proofread’
results, mark characters the system does not recognize, and send
rejected text to human operators for manual processing. It is needless
to say that such human intervention increases costs and delays.
Intelligent Character Recognition (ICR) converts hand printed
characters to their machine print (ASCII) equivalents, representing
a significant step forward in technology when compared to older
OCR systems that only read machine print. The ability to recognize
handprint significantly broadens the range of applications that benefit
from automated ICR solutions, saving time and increasing accuracy to
levels not attainable by OCR or human intervention.
ICR software is based on the science of neural networks that behave
like the human brain when processing information. Because ICR can
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handle variations in character shape, the term ‘intelligent’ is combined
with ‘character recognition’ to describe handprint recognition.
Principles of ICR Technology
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Hand printed characters are created by humans, so understanding
and interpreting the patterns of human writing is far more complicated
than converting simple machine print, because no two people ever
write identical characters. Factors such as mood, environment, or
stress all conspire to create variations in character writing, causing
individuals to form characters differently each time they write or
fill out a form. Variations will even appear within the same word,
depending on where a character appears. Also, keep in mind that hand
printed characters are never evenly spaced across the page, making
it difficult for recognition systems to reliably segment words into
their component characters. Like OCR engines, ICR engines execute
recognition character-by-character and start by segmenting words
into their component characters. Because ICR technology recognizes
separate words or word combinations, such as form fields, letters
cannot be written sloppily or stuck together.
Intelligent Recognition Technology
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The basic principle of Parascript® Intelligent Recognition states
that handwriting, when reduced to its most basic components, is
essentially motion, or a series of movements, made by a writing
instrument. According to this theory, any handwriting can be
described using elements of a special description language. The eight
elements that make up the trajectories of all cursive letters form a ring
that illustrates the possible transitions of neighbor elements.
The order of elements in the letter description follows the trajectory
of a pen. Horizontal lines show the vertical position on the image
associated with each element in the letter description.
Both OCR and ICR deliver high accuracy when analyzing
constrained text (OCR with machine print and ICR with handprint)
but are ineffective when dealing with cursive, where letters are linked
together, and may be poorly written or even illegible. Consider a
situation where the symbol segmentation of an image is ambiguous.
An OCR/ICR recognition system could determine that the first
symbol is a ‘d’ or a combination of a ‘c’ and an ‘l’. Depending on
the segmentation, the reading result produced by a letter-based
recognition technology may be completely different: ‘clear’ in the first
case and ‘dear’ in the second.
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As accurate character segmentation is critical, Intelligent
Recognition can often recognize poor-quality text that would be
impossible for OCR and ICR systems to recognize. Intelligent
Recognition dynamically uses context in a process similar to the one
humans employ when reading and interpreting text to compensate for
the inherent ambiguity of human handwriting. The context is used
during the recognition process rather than after recognition, when
results might already have been misinterpreted, thus improving the
accuracy of results. Again, it is not clear if the first symbol is a ‘d’ or
a combination of a ‘c’ and an ‘l’.
The dynamic vocabularies contained in Intelligent Recognition
systems do not analyze and store all possible hypotheses of segmentation.
If the dynamic vocabulary does not contain a combination of ‘c’ and
an ‘l’ at the beginning of the word, the only possible segmentation
solution is ‘d’. The dynamic usage of context eliminates all impossible
combinations from the solution set, enabling the evaluation of results
‘on the fly’ during the recognition process. Dynamic context, therefore,
provides the highest possible recognition accuracy, because it eliminates
the impossible results in real time, during the recognition process.
Intelligent Recognition technology often recognizes text that is
considered to be of poor quality or even completely unacceptable for OCR
and ICR technologies, therefore further improving the recognition rates
when compared to other systems. Working with high quality machine
print, OCR provides recognition accuracy of nearly 100% (99.9 %), a
level of accuracy acceptable for many forms processing applications. ICR
cannot guarantee the same levels of accuracy that OCR systems deliver
on machine print due to the inherent problems of reading handprint
spacing variations, diversity of human writing styles, etc. Instead,
state of the art ICR systems provide the same recognition accuracy for
a certain part of the data stream, while the data that cannot be reliably
read continue to be sent for visual verification. The following mechanism
is used by ICRs to ensure the accuracy required by the application. The
stream of images is divided into two parts: those that were recognized
reliably with a required accuracy (accepted), and those for which the
system does not guarantee the required accuracy (rejected).
Intelligent Recognition further improves recognition rates and
accuracy when compared to traditional machine print (OCR) and handprint
(ICR) engines through field recognition and cross-validation of results.
Intelligent Recognition recognizes a field not a character, and
consequently a whole field is either accepted or rejected. Conversely,
in the case of a rejected field Intelligent Recognition technology
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additionally provides information about unreliable characters.
Second, the reject mechanism is tuned so thoroughly that it allows
accuracy up to 0.1% for the texts of low quality.
Computing power alone is not able to deliver high recognition results
without a human-like recognition approach. Intelligent Recognition
employs the most advanced methods of single character recognition
while using sophisticated algorithms to cross-validate results during
the recognition process.
Intelligent Recognition advances the state of recognition technology,
exploiting the strengths and capabilities of its predecessors – OCR and
ICR systems, while eliminating their inherent limitations. Intelligent
Recognition technology delivers highly accurate machine print,
handprint and cursive recognition results, helps eliminate laborious
human data entry and has become a proven solution for a broad range
of the most demanding applications for government posts, commercial
mailers, banks, financial institutions and data processing centers.
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Text 2. From Databases to Dataspaces: A New Abstraction
for Information Management
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In this article we introduce dataspaces as a new abstraction for data
management and we propose the design and development of DataSpace
Support Platforms (DSSPs) as a key agenda item for the data management
field. In a nutshell, a DSSP offers a suite of interrelated services and
guarantees that enable developers to focus on the specific challenges of
their applications, rather than on the recurring challenges involved in
dealing consistently and efficiently with large amounts of interrelated
but disparately managed data. We begin our discussion of dataspaces
and DSSPs by placing them in the context of existing systems.
The distinguishing properties of dataspace systems are the following:
– A DSSP must deal with data and applications in a wide variety of
formats accessible through many systems with different interfaces.
A DSSP is required to support all the data in the dataspace rather than
leaving some out, as with a Database Management System (DBMS).
– Although a DSSP offers an integrated means of searching,
querying, updating, and administering the dataspace, often the same
data may also be accessible and modifiable through an interface native
to the system hosting the data. Thus, unlike a DBMS, a DSSP is not in
full control of its data.
– Queries to a DSSP may offer varying levels of service, and in some
cases may return best-effort or approximate answers. For example,
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when individual data sources are unavailable, a DSSP may be capable
of producing the best results it can, using the data accessible to it at
the time of the query.
– A DSSP must offer the tools to create tighter integration of data
in the space as necessary.
Logical Components of Dataspaces
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A dataspace should contain all of the information relevant to a
particular organization regardless of its format and location, and
model a rich collection of relationships between data repositories.
Hence, we model a dataspace as a set of participants and relationships.
The participants in a dataspace are the individual data sources:
they can be relational databases, XML repositories, text databases,
web services and software packages. They can be stored or streamed
(managed locally by data stream systems), or even sensor deployments.
Some participants may support expressive query languages, while
others are opaque and offer only limited interfaces for posing queries (e.g.,
structured files, web services, or other software packages). Participants
vary from being very structured (e.g., relational databases) to semistructured (XML, code collections) and completely unstructured. Some
sources will support traditional updates, while others may be appendonly (for archiving purposes), and still others may be immutable.
A dataspace should be able to model any kind of relationship
between two (or more) participants.
Dataspaces can be nested within each other (e.g., the dataspace
of the Computer Science Department is nested within the dataspace
of the University), and they may overlap (e.g., the dataspace of the
Computer Science Department may share some participants with the
Electrical Engineering Department). Hence, a dataspace must include
access rules between disparate dataspaces. In general, there will be
cases where the boundaries of a dataspace may be fluid, but we expect
that in most of the cases the boundaries will be natural to define.
Dataspace Systems
We now outline one possible set of components and architecture for
a dataspace system. A DSSP offers several interrelated services on the
dataspace, some of which are generalizations of components provided by
a traditional DBMS. It is important to keep in mind that unlike a DBMS,
a DSSP does not assume complete control over the data in the dataspace.
Instead, a DSSP allows the data to be managed by the participant
systems, but provides a new set of services over the aggregate of these
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systems, while remaining sensitive to the autonomy needs of the systems.
Furthermore, we may have several DSSPs serving the same dataspace –
in a sense, a DSSP can be a personal view on a particular dataspace.
Catalog and Browse
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The catalog contains information about all the participants in the
dataspace and the relationships among them. The catalog must be able to
accommodate a large variety of sources and support differing levels of
information about their structure and capabilities. Wherever possible,
the catalog should contain a basic inventory of the data elements at
each participant: identifier, type, creation date and so forth.
Search and Query
The component should offer the following capabilities: query
everything, structured query, meta-data queries, monitoring.
Local Store and Index
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A DSSP will have a storage and indexing component for the
following goals: (1) to create efficiently queryable associations between
data objects in different participants, (2) to improve accesses to data
sources that have limited access patterns, (3) to enable answering
certain queries without accessing the actual data source, and (4) to
support high availability and recovery.
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The Discovery Component
The goal of this component is to locate participants in a dataspace,
create relationships between them, and help administrators to refine
and tighten these relationships.
The Source Extension Component
Certain participants may lack significant data management
functions. A DSSP should be able to imbue such a participant with
additional capabilities, such as a schema, a catalog, keyword search
and update monitoring.
Useful words:
dataspace – область адресов данных;
Database Management System – система управления базами данных (СУБД);
DataSpace Support Platforms – опорная платформа области адресов данных;
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disparate – несравнимый; несопоставимый;
query – запрос; запрашивать информацию.
Text 3. Real-Time Operating System Kernel
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Real-time and embedded systems operate in constrained
environments in which computer memory and processing power are
limited. They often need to provide their services within strict time
deadlines to their users and to the surrounding world. It is these
memory, speed and timing constraints that dictate the use of real-time
operating systems in embedded software.
Basic kernel services
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The kernel is the part of an operating system that provides the most
basic services to application software running on a processor.
The kernel of a real-time operating system (RTOS) provides an
“abstraction layer” that hides from application software the hardware
details of the processor (or set of processors) upon which the application
software will run.
In providing this “abstraction layer” the RTOS kernel supplies five
main categories of basic services to application software.
The most basic category of kernel services is Task Management.
This set of services allows application software developers to design
their software as a number of separate “chunks” of software – each
handling a distinct topic, a distinct goal, and perhaps its own realtime deadline. Each separate “chunk” of software is called a “task”.
Services in this category include the ability to launch tasks and assign
priorities to them. The main RTOS service in this category is the
scheduling of tasks as the embedded system is in operation. The Task
Scheduler controls the execution of application software tasks, and
can make them run in a very timely and responsive fashion.
The second category of kernel services is Intertask Communication
and Synchronization. These services make it possible for tasks to pass
information from one to another, without danger of that information
ever being damaged. They also make it possible for tasks to coordinate,
so that they can productively cooperate with one another. Without the
help of these RTOS services, tasks might well communicate corrupted
information or otherwise interfere with each other.
Since many embedded systems have stringent timing requirements,
most RTOS kernels also provide some basic Timer services, such as
task delays and time-outs.
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Many (but not all) RTOS kernels provide Dynamic Memory
Allocation services. This category of services allows tasks to “borrow”
chunks of RAM memory for temporary use in application software.
Often these chunks of memory are then passed from task to task, as a
means of quickly communicating large amounts of data between tasks.
Many (but not all) RTOS kernels also provide a “Device I/O
Supervisor” category of services. These services, if available, provide
a uniform framework for organizing and accessing the many hardware
device drivers that are typical of an embedded system.
In addition to kernel services, many RTOSs offer a number of
optional add-on operating system components for such high-level
services as file system organization, network communication, network
management, database management, user-interface graphics, etc.
Although many of these add-on components are much larger and
much more complex than the RTOS kernel, they rely on the presence
of the RTOS kernel and take advantage of its basic services. Each of
these add-on components is included in an embedded system only if
its services are needed for implementing the embedded application, in
order to keep program memory consumption to a minimum.
Many non-real-time operating systems also provide similar kernel
services. The key difference between general-computing operating
systems and real-time operating systems is the need for “deterministic”
timing behavior in the real-time operating systems. Formally,
“deterministic” timing means that operating system services consume
only known and expected amounts of time.
Real-time and embedded systems are used in many applications
such as airborne computers, medical instruments and communication
systems. Embedded systems are characterized by limited processor
memory, limited processing power, and unusual interfaces to the
outside world. Real-time requirements impose stringent time deadlines
for delivering the results of embedded processing.
Useful words:
abstraction layer – уровень абстракции (1) соответствие уровня
описания задачи её наиболее общему представлению – чем выше
уровень абстракции ЯВУ, тем меньше усилий затрачивается
на кодирование; 2) способ скрыть физическую реализацию
аппаратных средств под некоторой логической структурой;
add-on – расширение;
airborne computer – бортовая ЭВМ;
kernel [‘kз:n(ə)l]– ядро операционной системы;
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RAM – запоминающее устройство с произвольным доступом
(ЗУПД);
real-time operating system – операционная система реального
времени;
stringent [‘strindзənt] – строгий.
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Text 4. Multiple Document Interface (MDI)
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Multiple Document Interface is considered an advanced interface
in computer sciences. Graphical computer applications with MDI are
those whose windows reside under a single parent window (usually
with the exception of modal windows), as opposed to all windows being
separate from each other (single document interface). The initialism
MDI is usually not expanded. In the usability community, there has
been much debate over which interface type is preferable. Generally
Single Document Interface (SDI) is seen as more useful in cases where
users work with more than one application. Companies have used both
interfaces with mixed responses. For example, Microsoft has changed its
Office applications from SDI to MDI mode and then back to SDI, although
the degree of implementation varies from one component to another.
The disadvantage of MDI usually cited is the lack of information
about the currently opened windows: In order to view a list of windows
open in MDI applications, the user typically has to select a specific
menu (‘window list’ or something similar), if this option is available
at all. With an SDI application, the window manager’s task bar or
task manager displays the currently opened windows. In recent years,
applications have increasingly added ‘task-bars’ and ‘tabs’ to show the
currently opened windows in an MDI application, which has made this
criticism somewhat obsolete. Some people use a different name for this
interface, Tabbed Document Interface (TDI). When tabs are used to
manage windows, individual ones can usually not be resized.
Nearly all graphical user interface toolkits provide at least one
solution for designing MDIs. The Java GUI toolkit, Swing, for instance,
provides the class javax.swing. JDesktopPane which serves as a
container for individual frames (class javax.swing.JInternalFrame).
GTK + lacks any standardized support for MDI.
Comparing it to Single Document Interface we can point out the
following advantages. With MDI (and also TDI), a single menu bar
and/or toolbar is shared between all child windows, reducing clutter
and increasing efficient use of screen space. An application’s child
windows can be hidden/shown/minimized/maximized as a whole.
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Features such as ‘Tile’ and ‘Cascade’ can be implemented for the
child windows. Possibly faster and more memory efficient, since the
application is shared, and only the document changes. The speed of
switching between the internal windows is usually faster than having
the OS switch between external windows. Usually much faster to work
with, from usability point of view, because you get a workspace of your
own for this application to concentrate on, without other applications
interfering. Moreover, there are less mouse clicks to get things done,
and less mental time for the user to seek the function (s)he needs.
Some applications have keyboard shortcuts to quickly jump to the
functionality you need (faster navigating), and this doesn’t need the
OS or window manager support, since it happens inside the application.
It cannot be used successfully on desktops using multiple monitors.
It also cannot be used successfully with multiple virtual desktops. MDI
can make it more difficult to work with several applications at once, by
restricting the ways in which windows from multiple applications can be
arranged together. Without an MDI frame window, floating toolbars from
one application can clutter the workspace of other applications, potentially
confusing users with the jumble of interfaces. Hand printed characters
are created by humans, so understanding and the shared menu changes,
which may cause confusion to some users. MDI child windows behave
differently from those in single document interface applications, requiring
users to learn two subtly different windowing concepts. Similarly, the
MDI parent window behaves like the desktop in many respects, but has
enough differences to confuse some users. Many window managers have
built-in support for manipulating groups of separate windows, which is
typically more flexible than MDI in that windows can be grouped and
ungrouped arbitrarily. A typical policy is to group automatically windows
that belong to the same application. This arguably makes MDI redundant
by providing a solution to the same problem.
1. Internet Explorer 6: This is a typical SDI application.
2. Visual Studio 6 development environment: This is a typical
modern implementation of MDI.
3. Visual Studio NET: MDI or TDI with ‘Window’ menu, but not both.
4. Firefox: TDI by default, can be SDI instead.
5. Opera: MDI combined with TDI.
6. GIMP: Floating windows (limited MDI is available via
‘Deweirdifier’ plugin).
7. GIMPshop: A fork of the GIMP edited to be more user-friendly
for Adobe Photoshop users. Note: the Windows version (still in beta
form) has the ‘Deweirdifier’ plug in built-in.
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8. Adobe Photoshop: Floating windows in Mac version; MDI in
Windows XP version. In newer versions of Photoshop, toolbars can
move outside the frame window. Child windows can be outside of the
frame unless they are minimized or maximized.
9. Adobe Acrobat: Purely MDI until version 7.0 ( Microsoft
Windows version only).
10. Microsoft Excel 2003: Excel is SDI if you start new instances
of the application, but classic MDI if you click the ‘File > New’ menu
(except the child windows appear on the OS taskbar).
11. Microsoft Word 2003: Up to Office 97, Word was MDI.
However, from 2000 onwards, Word is a Multiple Top-Level Windows
Interface application, thus exposing to shell as many individual SDI
instances while the operating system recognizes it as a single instance
of an MDI Application. MFC (which Microsoft Office is loosely based
upon) supports this metaphor from version 7.0, as a new Feature in
Visual Studio 2002.
12. UltraEdit: Combination of MDI & TDI (a true MDI interface
with a tab bar for quick access).
13. Notepad + +: TDI.
14. Macromedia Studio under Windows uses a hybrid interface. If
document windows are maximized, as they are by default, the program
presents a TDI, however, if the windows are un-maximized it presents
an MDI.
15. CorelWordperfect: MDI, although a user can open multiple
instances of WP with a single document in each, if they wish to. Recent
versions maintain a list of open documents for a given window on the
status bar at the bottom of the window, providing a variant of the TDI.
IDE-style interface in RSS Bandit
Graphical computer applications with an IDE-style interface (IDE)
are those whose child windows reside under a single parent window
(usually with the exception of modal windows). An IDE-style interface
is distinguishable form of Multiple Document Interface (MDI), because
all child windows in an IDE-style interface are enhanced with added
functionality not ordinarily available in MDI applications. Because of
this, IDE-style applications can be considered a functional superset
and descendant of MDI applications.
Examples of enhanced child-window functionality include:
1. Dockable child windows.
2. Collapsable child windows.
3. Tabbed document interface for sub-panes.
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4. Independent sub-panes of the parent window.
5. GUI splitters to resize sub-panes of the parent window.
Collapsable child windows are as follows: a common convention
for child windows in IDE-style applications is the ability to collapse
child windows, either when inactive, or when specified by the user.
Child windows that are collapsed will conform to one of the four outer
boundaries of the parent window, with some kind of label or indicator
that allows them to be expanded again.
In contrast to (MDI) applications, which ordinarily allow a single
tabbed interface for the parent window, applications with an IDEstyle interface allow tabs for organizing one or more subpanes of the
parent window. IDE-style application examples: Netbeans, Eclipse,
Visual Studio 6, Visual Studio.NET, RSS Bandit, JEdit, MATLAB.
This problem that MDI solves does not occur on Mac OS X, because
the Mac OS X GUI is application centric instead of window centric. As
opposed to Windows, all windows belonging to an application share
the same menu, they can be hidden and manipulated as a group, and
switching occurs between applications (i.e. groups of windows) instead
of between individual windows.
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ПРИЛОЖЕНИЕ
Фразовые глаголы, встречающиеся в текстах:
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allow for – 1) предусматривать, учитывать; 2) выделять, предоставлять;
bring in – вводить, вносить, привлекать, приглашать;
bring into – приводить что-либо в какое-то состояние;
build in – 1) встраивать; 2) включать в состав;
carry on – продолжать что-либо, делать что-либо;
carry out –осуществлять, выполнять;
come across – натолкнуться на что-либо, встретиться с чем-либо;
come out – 1) появляться, выходить; 2) раскрываться, становиться ясным/известным;
deal with – 1) иметь дело с чем-либо, кем-либо; справляться;
2) затрагивать, рассматривать что-либо, касаться;
go down – 1) снижаться, уменьшаться; 2) быть принятым с одобрением;
interfere with – мешать, вредить чему-либо;
keep in – поддерживать что-либо;
keep to – 1) придерживаться чего-либо, следовать чему-либо;
2) ограничивать что-либо чем-либо, сводить что-либо к чему либо;
3) заставлять кого-либо придерживаться чего-либо;
look back – оглядываться назад;
make up – составлять что-либо целое;
put forward – выдвигать, предлагать;
put into – вкладывать во что-либо;
take up – 1) заняться чем-либо, пристраститься к чему-либо;
2) занимать, отнимать;
think of – 1) иметь какое-либо мнение о чем –либо; 2) придумывать что-либо.
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Рекомендуемая литература
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1. Алексеева И. С. Профессиональный тренинг переводчика.
СПб.: Перспектива; Союз, 2008. 283 c.
2. Казакова Т. А. Практические основы перевода. English ↔
Russian: учеб. пособие. СПб.: Перспектива; Союз. 320 с.
3. Латышев Л. К., Федоров А. В. Учебное пособие по теории перевода. М., 2007. 230 с.
4. Нелюбин Л. Л. Введение в технику перевода: учеб. пособие.
М.: Флинта 2009. 127 c. (электронное издание).
5. Паршин А. Теория и практика перевода. URL: http://teneta.
rinet.ru/rus/pe/parshin-and_teoria-i-practika-perevoda.htm.
6. Цатурова И. А., Каширина Н. А. Переводческий анализ текста. Английский язык. СПб.: Перспектива; Союз, 2008. 295 c.
7. Переводческие решения: проблемы и поиски: сборник. Пенза, 1996. 145 c.
8. Тюленев С. В. Теория перевода. М.: Гардарики, 2004. 167 c.
9. URL: http://www.cs.wisc.edu/condor/description.html (дата
обращения 02.10.15).
10. URL: http://nssdc.gsfc.nasa.gov/image/planetary/jupiter/
europa close.jpg (дата обращения 21.10.15).
49
СОДЕРЖАНИЕ
П
3
Chapter I. Проблемы технического перевода и их решение................ 1. Лингвистические основы перевода........................................ 3
2. Перевод терминов и терминологических сочетаний.................. 7
3. Перевод многокомпонентных терминов.................................. 10
4. Рабочие источники информации........................................... 11
5. Практические рекомендации по научному и техническому
переводу................................................................................ 11
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Chapter II. Техника перевода........................................................ Тема 1. Стратегии перевода.......................................................... Text 1. Development of Modern Mathematics................................ Тема 2. Единицы перевода и членения текста.................................. Text 2. The Axiom of Choice...................................................... Тема 3. Лексические приемы перевода........................................... Text 3. Number Continuum....................................................... Тема 4. Грамматические (морфологические) приемы перевода........... Text 4. Zeno’s Paradoxes.......................................................... Тема 5. Синтаксические приемы перевода
(на уровне словосочетаний)........................................................... Text 5. Integral and Differential Calculus.................................... Тема 6. Синтаксические приемы перевода
(на уровне предложений).............................................................. Text 6. The Differential Calculus................................................ Тема 6. Синтаксические приемы перевода
(на уровне предложений).............................................................. Text 6. The Derivative Defined.................................................. Тема 7. Научный и технический функциональный стили.
Особенности, правила перевода..................................................... Text 7. Topology..................................................................... Chapter III. Практика переводческого анализа, перевода
и редактирования более сложных текстов....................................... Text 1. OCR Technology........................................................... Text 2. From Databases to Dataspaces: A New Abstraction
for Information Management..................................................... Text 3. Real-Time Operating System Kernel................................. Text 4. Multiple Document Interface (MDI).................................. Приложение............................................................................... Рекомендуемая литература.......................................................... 26
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Для заметок
ГУ
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Громовая Ирина Ивановна,
Злобина Ольга Владимировна,
Левченко Марина Владимировна,
Чиханова Марина Анатольевна
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Учебное издание
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ТЕХНИЧЕСКИЙ ПЕРЕВОД.
Information systems mathematical support
and administration
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Учебно-методическое пособие
Публикуется в авторской редакции.
Компьютерная верстка С. Б. Мацапуры
Сдано в набор 02.10.15. Подписано к печати 09.12.15.
Формат 60×84 1/16. Бумага офсетная. Усл. печ. л. 3,02.
Уч.-изд. л. 3,25. Тираж 100 экз. Заказ № 510.
Редакционно-издательский центр ГУАП
190000, Санкт-Петербург, Б. Морская ул., 67
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