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職稱英語(yǔ)理工類概括大意與理解句子真題分享
職稱英語(yǔ)考試的大多數(shù)題型都是閱讀理解，下面是小編整理的職稱英語(yǔ)概括大意與理解句子的真題，歡迎大家閱讀!
下面的短文后有2項(xiàng)測(cè)試任務(wù)：(1)第23~26題要求從所給的6個(gè)選項(xiàng)中為第2～5段每段選擇1個(gè)最佳標(biāo)題;(2)第27～30題要求從所給的6個(gè)選項(xiàng)中為每個(gè)句子確定1個(gè)最佳選項(xiàng)。
First Image-recognition Software
1. Dartmouth researchers and their colleagues have created an artificial intelligence software that uses photos to locate documents on the Internet with far greater accuracy than ever before.
2. The new system, which was tested on photos and is now being applied to videos, shows for the first time that a machine learning algorithm (運(yùn)算法則) for image recognition and retrieval is accurate and efficient enough to improve large-scale document searches online. The system uses pixel (像素) data in images and potentially video — rather than just text — to locate documents. It learns to recognize the pixels associated with a search phrase by studying the results from text-based image search engines. The knowledge gleaned (收集) from those results can then be applied to other photos without tags or captions (圖片說(shuō)明), making for more accurate document search results.
3. "Over the last 30 years," says Associate Professor Lorenzo Torresani, a co-author of the study, "the Web has evolved from a small collection of mostly text documents to a modern, massive, fast-growing multimedia data set, where nearly every page includes multiple pictures or videos. When a person looks at a Web page, he immediately gets the gist (主旨) of it by looking at the pictures in it. Yet, surprisingly, all existing popular search engines, such as Google or Bing, strip away the information contained in the photos and use exclusively the text of Web pages to perform the document retrieval. Our study is the first to show that modern machine vision systems are accurate and efficient enough to make effective use of the information contained in image pixels to improve document search."
4. The researchers designed and tested a machine vision system — a type of artificial intelligence that allows computers to learn without being explicitly programmed — that extracts semantic (語(yǔ)義的) information from the pixels of photos in Web pages. This information is used to enrich the description of the HTML page used by search engines for document retrieval. The researchers tested their approach using more than 600 search queries (查詢)on a database of 50 million Web pages. They selected the text-retrieval search engine with the best performance and modified it to make use of the additional semantic information extracted by their method from the pictures of the Web pages. They found that this produced a 30 percent improvement in precision over the original search engine purely based on text.
23. Paragraph 1 ____
24. Paragraph 2 ____
25. Paragraph 3 ____
26. Paragraph 4 ____
A. Function of the new system
B. Improvement in document retrieval
C. Publication of the new discovery
D. Problems of the existing search engines
E. Popularity of the new system
F. Artificial intelligence software created
27. The new system does document retrieval by ____.
28. The new system is expected to improve precision in ____.
29. When performing document retrieval the existing search engines ignore __ __
30. The new system was found more effective in document search than the ____
A. using photos
B. description of the HTML page
C. current popular search engines
D. document search
E. information in images
F. machine vision systems
First Image-recognitions software
1) Dartmouth researchers and their colleagues have created an artificial intelligence software that uses photos to locate documents on the Internet with far greater accuracy than ever before.
2)The new system, which was tested on photos and is now being applied to videos, shows for the first time that a machine learning algorithm(運(yùn)算法則)for image recognition and retrieval is accurate and efficient enough to improve large-scale document searches online. The system uses pixel(像素)data in images and potentially video—rather than just text—to locate documents. It learns to recognize the pixels associated with a search phrase by studying the results from text-based image search engines. The knowledge gleaned(收集)from those results can then be applied to other photos without tags or captions(圖片說(shuō)明),making for more accurate document search results.
3)“Over the last 30 years,” says Associate Professor Korenzo Torresani, a co-author of the study,” the web has evolved from a small collection of mostly text documents to a modern, massive, fast-growing multimedia datastet, where nearly every page includes multiple pictures of videos. When a person looks at a Web page, he immediately get the gist(主旨)of it by looking at the pictures in it. Yet, surprisingly, all existing popular search engine, such as Google or Bing, strip away the information contained in the photos and use exclusively the text of Wed pages to perform the document retrieval. Our study is the first to show that modern machine vision systems are accurate and efficient enough to make effective use of the information contained in image pixels to improve document search.”
4)The researchers designed and tested a machine vision system—a type of artificialintelligence that allows computers to learn without being explicitly programmed— that extracts semantic(語(yǔ)義的)information from pixels of photos in Web pages. This informationg is used to enrich the description of the HTML page used by search engines for document retrieval. The researchers tested their approach using more than 600 search queries(查詢)on a database of 50 million Wed pages. They selected the text-retrieval search engine with the best performance and modified it to make use of the additional semantic information extracted by their method from the pictures of the Web pages. They found tht this produced a 30 percent improvement in precision over the original search engine purely based on text.
23. Paragraph 1 _____
24. Paragraph 2 _____
25. Paragraph 3 _____
26 Paragraph 4 _____
A. Popularity of the new system
B. Publication of the new discovery
C .Function of the new system
D. Artificial intelligence software created
E. Problems of the existing search engines
F .Improvement in document retrieval
27. The new system does document retrieval by _____.
28. The new system is expected to improve precision in _____.
29. When performing document retrieval the existing search engines ignore _____.
30. The new system was found more effective in document search than the _____.
A. information in images
B. current popular search engines
C. using photos
D. machine vision systems
E. document search
F. description of the HTML page
New research lights the way to super-fast computers
1)New research published today in the journal Nature Communications, has demonstrated how glass can be manipulated to create a material that will allow computers to transfer information using light. This development could significantly increase computer processing speeds and power in the future.
2)The research by the University of Surrey, in collaboration with the University of Cambridge and the University of Southampton, has found it is possible to change the electronic properties of amorphous chalcogenides, a glass material integral to data technologies such as CDs and DVDs. By using a technique called ion doping, the team of researchers have discovered a material that could use light to bring together different computing functions into one component, leading to all-optical systems.
3) Computers currently use electrons to transfer information and process applications. On the other hand, data sources such as the internet rely on optical systems; the transfer of information using light. Optical fibres are used to send information around the world at the speed of light, but these signals then have to be converted to electrical signal sonce they reach a computer, causing a significant slowdown in processing.
4)"The challenge is to find a single material that can effectively use and control light to carry information around a computer. Much like how the web uses light to deliver information, we want to use light to both deliver and process computer data," said project leader, Dr Richard Curry of the University of Surrey.
5)"This has eluded researchers for decades, but now we have now shown how a widely used glass can be manipulated to conduct negative electrons, as well as positive charges, creating what are known as 'pn-junction' devices. This should enable the material to act as a light source, a light guide and a light detector - something that can carry and interpret optical information. In doing so, this could transform the computers of tomorrow, allowing them to effectively process information at much faster speeds."
6) The researchers expect that the results of this research will be integrated into computers within ten years. In the short term, the glass is already being developed and used in next-generation computer memory technology known as CRAM, which may ultimately be integrated with the advances reported.
23 Paragraph 2 _____
24 Paragraph 3 _____
25 Paragraph 4 _____
26 Paragraph 5 _____
A. Expectation of the discovery
B. the problem of current computers
C. A new finding
D. The purpose of the research
E. Public reaction to the discovery
F. The use of the new material
27.The result of the research can help computers to increase _____
28.Current computers transfer information using _____
29.The new glass material makes it possible to fulfill different computing function _____
30. Glass is used in the research to carry and process _____
A. optical information
B. processing speeds
C. electrons
D. positive charges
E. data technologies
F .all-optical systems
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