تر جمه -- Translation 2

[SCYTHE]

دوستان اينو شما چي ترجمه ميكنيد:
Gone Baby Gone
تلويزيون اينو از دست رفته معني كرده

من ندیدم، ولی میشه این طوری ترجمه کرد:
عزیز رفته، رفته====gone baby, gone
رفته عزیز رفته====gone, baby gone

[ehsan_1987]

اون قبلی که ترجمه نشد.اونو ترجمه کردید این را هم ترجمه کنید.

In an increasing number of scienti_c disciplines, large data collections are emerging as important
community resources. In domains as diverse as global climate change, high energy physics, and
computational genomics, the volume of interesting data is already measured in terabytes and will soon
total petabytes. The communities of researchers that need to access and analyze this data (often
using sophisticated and computationally expensive techniques) are often large and are almost always
geographically distributed, as are the computing and storage resources that these communities rely
upon to store and analyze their data [17].This combination of large dataset size, geographic distribution of users and resources, and com-
putationally intensive analysis results in complex and stringent performance demands that are not
satis_ed by any existing data management infrastructure. A large scienti_c collaboration may gen-
erate many queries, each involving access to|or supercomputer-class computations on|gigabytes or
terabytes of data. Ecient and reliable execution of these queries may require careful management
of terabyte caches, gigabit/s data transfer over wide area networks, coscheduling of data transfers
and supercomputer computation, accurate performance estimations to guide the selection of dataset
replicas, and other advanced techniques that collectively maximize use of scarce storage, networking,
and computing resources.The literature oers numerous point solutions that address these issues (e.g., see [17, 14, 19, 3]).
But no integrating architecture exists that allows us to identify requirements and components common
to dierent systems and hence apply dierent technologies in a coordinated fashion to a range of data-
intensive petabyte-scale application domains.Motivated by these considerations, we have launched a collaborative eort to design and produce
such an integrating architecture. We call this architecture the data grid, to emphasize its role as a
specialization and extension of the \Grid" that has emerged recently as an integrating infrastructure




for distributed computation [10, 20, 15]. Our goal in this eort is to de_ne the requirements that a
data grid must satisfy and the components and APIs that will be required in its implementation. We
hope that the de_nition of such an architecture will accelerate progress on petascale data-intensive
computing by enabling the integration of currently disjoint approaches, encouraging the deployment
of basic enabling technologies, and revealing technology gaps that require further research and devel-
opment. In addition, we plan to construct a reference implementation for this architecture so as to
enable large-scale experimentation.This work complements other activities in data-intensive computing. Work on high-speed disk
caches [21] and on tertiary storage and cache management [5, 19] provides basic building blocks.
Work within the digital library community is developing relevant metadata standards and metadata-
driven retrieval mechanisms [16, 6, 1] but has focused less on high-speed movement of large data
objects, a particular focus of our work. The Storage Resource Broker (SRB) [2] shows how diverse
storage systems can be integrated under uniform metadata-driven access mechanisms; it provides a
valuable building block for our architecture but should also bene_t from the basic services described
here. The High Performance Storage System (HPSS) [24] addresses enterprise-level concerns (e.g., it
assumes that all accesses occur within the same DCE cell); our work addresses new issues associated
with wide area access from multiple administrative domains.
In this paper, we _rst review the principles that we are following in developing a design for a
data grid architecture. Then, we describe two basic services that we believe are fundamental to the
design of a data grid, namely, storage systems and metadata management. Next, we explain how
these services can be used to develop various higher-level services for replica management and replica
selection. We conclude by describing our initial implementation of data grid functionality.

[Sha7ab]

اون قبلی که ترجمه نشد.اونو ترجمه کردید این را هم ترجمه کنید.

in an increasing number of scienti_c disciplines, large data collections are emerging as important
community resources. In domains as diverse as global climate change, high energy physics, and
computational genomics, the volume of interesting data is already measured in terabytes and will soon
total petabytes. The communities of researchers that need to access and analyze this data (often
using sophisticated and computationally expensive techniques) are often large and are almost always
geographically distributed, as are the computing and storage resources that these communities rely
upon to store and analyze their data [17].this combination of large dataset size, geographic distribution of users and resources, and com-
putationally intensive analysis results in complex and stringent performance demands that are not
satis_ed by any existing data management infrastructure. A large scienti_c collaboration may gen-
erate many queries, each involving access to|or supercomputer-class computations on|gigabytes or
terabytes of data. Ecient and reliable execution of these queries may require careful management
of terabyte caches, gigabit/s data transfer over wide area networks, coscheduling of data transfers
and supercomputer computation, accurate performance estimations to guide the selection of dataset
replicas, and other advanced techniques that collectively maximize use of scarce storage, networking,
and computing resources.the literature oers numerous point solutions that address these issues (e.g., see [17, 14, 19, 3]).
But no integrating architecture exists that allows us to identify requirements and components common
to dierent systems and hence apply dierent technologies in a coordinated fashion to a range of data-
intensive petabyte-scale application domains.motivated by these considerations, we have launched a collaborative eort to design and produce
such an integrating architecture. We call this architecture the data grid, to emphasize its role as a
specialization and extension of the \grid" that has emerged recently as an integrating infrastructure




for distributed computation [10, 20, 15]. Our goal in this eort is to de_ne the requirements that a
data grid must satisfy and the components and apis that will be required in its implementation. We
hope that the de_nition of such an architecture will accelerate progress on petascale data-intensive
computing by enabling the integration of currently disjoint approaches, encouraging the deployment
of basic enabling technologies, and revealing technology gaps that require further research and devel-
opment. In addition, we plan to construct a reference implementation for this architecture so as to
enable large-scale experimentation.this work complements other activities in data-intensive computing. Work on high-speed disk
caches [21] and on tertiary storage and cache management [5, 19] provides basic building blocks.
Work within the digital library community is developing relevant metadata standards and metadata-
driven retrieval mechanisms [16, 6, 1] but has focused less on high-speed movement of large data
objects, a particular focus of our work. The storage resource broker (srb) [2] shows how diverse
storage systems can be integrated under uniform metadata-driven access mechanisms; it provides a
valuable building block for our architecture but should also bene_t from the basic services described
here. The high performance storage system (hpss) [24] addresses enterprise-level concerns (e.g., it
assumes that all accesses occur within the same dce cell); our work addresses new issues associated
with wide area access from multiple administrative domains.
In this paper, we _rst review the principles that we are following in developing a design for a
data grid architecture. Then, we describe two basic services that we believe are fundamental to the
design of a data grid, namely, storage systems and metadata management. Next, we explain how
these services can be used to develop various higher-level services for replica management and replica
selection. We conclude by describing our initial implementation of data grid functionality.

دوست عزیز این متن خیلی زیاده و مطمئنا هیچکی این قدر وقت نداره که اینارو ترجمه کنه . من خودم چند تا متن طولانی (به اندازه همین متن شما ) دارم که هنوز وقت نکردم ترجمشون کنم .
حداکثر 3-4 خط باشه میشه کاری کرد اما ...

[C. Breezy]

بی زحمت اینو فعلا ترجمه کنین:

اینطور که معلومه فعلا سر مترجمان شلوغه و منم بخوام ترجمه کنم یه کم طول می کشه و چون فعلا در بحران امتحانات هستم باید صبر کنی حداکثر تا دو سه روز دیگه ترجمه میشه ( امیدوارم )

[C. Breezy]

He came at them right as they were frisking his teammate's pockets. There were three sitting at the victim’s backpack and sharing the booty, while another one was rummaging the pockets. Blood rushed to the stalker’s face making him blind with anger. He opened fire kill-thirsty. Bullets were a Zone currency, but he
did not spare it this time, bestowing killers and marauders with his lavish gifts.
Representatives of criminal world who came into the Zone for different reasons: earn from selling the
artefacts, hide from the law, buy or sell weapons. The Zone has quite a few of this element, ranging from
hoodlums to hardened criminals.
Most of the time they are united into gangs, however there is still no unified bandit organization in the Zone.
Bandits pose a big trouble to rank-and-file stalkers

اینم همچین کم نیست ... تا اونجایی رو که Bold کردم رو برات ترجمه کردم :

" او موقعی که آنها داشتن جیبهای هم تیمیشان را می گشتند پیششان آمد. سه نفر کنار کوله پشتی مقتول نشسته بودند و داشتن غنیمت ها را تقسیم می کردند ، هنگامی که دیگری داشت جیب ها رو زیر و رو می کرد . خون بر روی صورت خرامنده ( نفهمیدم این یعنی چی ، کسی که می خرامد ) می پاشید و او را از عصبانیت کور می کرد . "

یه چیزی تو این مایه ها میشه .... بقیه اش هم باشه واسه بعدا

[saber57]

بی زحمت اینو فعلا ترجمه کنین:

برای مشاهده محتوا ، لطفا وارد شوید یا ثبت نام کنید

ممنون.

او در حالیکه اونا جیبای رفیق هم تیمیشو با چالاکی میگشتند ، به سمت راستشون رسید . سه نفر روی کوله پشتی قربانی چنبره زده بورند و غنائم رو بین خودشون تقسیم میکردند در حالیکه یکی دیگه جیبا رو زیر و رو میکرد . خون جلوی چشمای استالکر رو گرفت و باعث شد که کنترلش رو از دست بده .او شروع به تیر اندازی به سمت قاتل کرد . گلوله هاش(منظور دست به تیرش) توی منطقه تک بود، ولی ایندفعه بدون معطلی ،قاتلا و غارتگرا رو با گلوله هاش بدرقه کرد(به اونا رحم نکرد)

از اساتید خواهش دارم اگه پارگراف بالا اشکال داشت ،تصحیح کنند

پاراگراف دوم:

نمایندگان دنیای نبهکاران ، به چند دلیل وارد منطقه شدند:
بدست آوردن سود حاصل از فروش مصنوعات ،فرار از قانون،خرید یا فروش اسلحه. منظقه تقریبا تعدادی از این عوامل داشت از اوباش گرفته تا جانیان سر سخت .
خیلی وقتا ،اونا بصورت یک دسته با هم متحد میشدند ،به هر حال هنوزتوی منطقه سازمان متحدی از راهزنان تشکیل نشده بود . راهزنان دردسر بزرگی برای سربازان(جوخه) استالکر به حساب میومدن

[ali_gamer]

سلام
این متنو یکی برا من ترجمه کنه البته یکم تونستم ولی کامل نه
ممنون

"For an Angel" is a 1994 trance track by German DJ Paul van Dyk. It is his most famous track, it was initially released in 1994 as a track on 45 RPM on the MFS record label, and was van Dyk's first album. It was later reworked and re-released in 1998 as "E-Werk Remix" on Deviant Records, a homage to the E-Werk nightclub where van Dyk used to be the resident DJ, charted around the world, reaching #28 in the UK Singles Chart and #26 in the Irish Singles Chart.

Two videos exist for the track, one from 1994, filmed in the Riviera Maya in Mexico; and one from 1998, featuring footage from the Love Parade in Berlin. The first video is available on

[behnam_tr]

اينو لطفا برام ترجكه كنيد....دقيقا...

EEPROM stands for Electrically Erasable Programmable Read Only Memory

[saber57]

اينو لطفا برام ترجكه كنيد....دقيقا...

Eeprom stands for electrically erasable programmable read only memory

eeprom به حافظه فقط خواندنی قابل برنامه ریزی پاک شدنی توسط الکتریسیته اطلاق میگردد

[roya_2003]

سلام.
لطفا متن زیر را ترجمه نمایید.

A proximity sensor detects an object when the object approaches within the detection boundary of the sensor. Proximity sensors are used in various facets of manufacturing for detecting the approach of metal objects. Various types of proximity sensors are used for detecting the presence or absence of an object. The design of a proximity sensor can be based on a number of principles of operation, some examples include: variable reluctance, eddy current loss, saturated core, and Hall effect. Depending on the principle of operation, each type of sensor will have different performance levels for sensing different types of objects.