Question

    Listen carefully to the footsteps in the family home, especially if it has wooden floors, and you can probably work out who it is that is walking about. The features most commonly used to identify people are faces, voices, finger prints and retinal scans. But their “behavioural biometrics”, such as the way they walk, are also giveaways.

Researchers have, for several years, used video cameras and computers to analyse people’s gaits, and are now quite good at it. But translating such knowledge into a practical identification system can be tricky----especially if that system is supposed to be hidden. Cameras are often visible, are hard to set up, requi5re good lighting and may have their view blocked by other people. So a team led by Krikor Ozanyan of the University of Manchester, in England and Patricia Scully of the National University of Ireland,  in Galway have been looking for a better way to recognize gait. Their answer: pressure-sensitive mats.

In themselves, such mats are nothing new. They have been part of security systems for donkeys’ years. But Dr. Ozanyan And Dr. Scully use a complex version that can record the amount of pressure applied in different places as someone walks across it. These measurements form a pattern unique to the walker. Dr. Ozanyan and Dr. Scully therefore turned, as is now common for anything to do with pattern recognition, to an Artificial Intelligence system that uses machine learning to recognize such patterns.

It seems to work. In a study published earlier this year the two researchers tested their system on a database of footsteps trodden by 127 different people. They found that its error rate in identifying who was who was a mere 0.7%. And Dr. Scully says that even without a database of footsteps to work with the system can determine someone’s sex---women and men, with wide and narrow pelvises(骨盆) respectively, walk in different ways,---- and guess, with reasonable accuracy, a subject’s age.

A mat-based gait-recognition system has the advantage that it would work in any lighting conditions----even pitch-darkness. And though it might fail to identify someone if, say, she was wearing stilettos and had been entered into the database while wearing trainers, it would be very hard to fool it by imitating the gait of an individual who was allowed admission to a particular place.

The latest phase of Dr. Ozanyan’s and Dr. Scully’s project is a redesign of the mat. The old mats contained individual pressure sensors. The new ones contain optical fibres(光纤). Light-emitting diodes(二极管) distributed along two neighbouring edges of a mat transmit light into the fibres. Sensors on the opposite edges( and thus the opposite ends of the optical fibres) measure how much of that light is received. Any pressure applied to part of the mat causes a distortion(变形) in the fibres and a consequent change in the amount of light transmitted. Both the location and amount of change can be plotted and analyzed by the machine-learning system.

Dr. Ozanyan says that the team have built a demonstration fibre-optic mat, two meters long and a metre wide, using materials that cost ￡100($130). They are now talking to companies about commercializing it. One application might be in health care, particularly for the elderly. A fibre-optic mat installed in a nursing home or an old person’s own residence could monitor changes in an individual’s gait that warn certain illnesses. That would provide early warning of someone being at greater risk of falling over, say, or of their cognition becoming damaged.

Gait analysis might also be used ass a security measure in the workplace, monitoring access to restricted areas, such as parts of military bases, server farms or laboratories dealing with harmful materials. In these cases, employees would need to agree to their gaits being scanned, just as they would agree to the scanning of their faces or retinas for optical security systems.

Perhaps the most fascinating use of gait-recognition mats, though, would be in public places, such as airports. For that to work, the footsteps of those to be recognized would need to have been stored in a database, which would be harder to arrange than the collection of mugshots and fingerprints that existing airport security systems rely on. Some people, however, might volunteer for it. Many aircrew or pre-registered frequent flyers would welcome anything that speeded up one of the most tiresome parts of modern travel.

1.Camera-based gait recognition fails to come into wide use, because _____.

a. it’s not easy to find the cameras

b. finger print recognition is still popular

c. sometimes the cameras can be covered

d. it’s a waste of money to fix the equipment

e. good lighting conditions can’t be guaranteed

f. it’s difficult to set up the system.

A. acf B. bde

C. cdf D. cef

2.Which of the following statements is TRUE according to Paragraph 6-8?

A. The new mats function greatly with individual pressure sensors built in.

B. The new mats will be likely to work better with enough pressure.

C. The elderly are cured of their diseases with the monitor of the fibre-optic.

D. Restricted areas are accessible to those with their gaits scanned beforehand.

3.What does “it” refer to in Paragraph 5?

A. The mat-based gait-recognition system B. The gait stored in the database

C. The advantage of working in any light condition. D. The admission to a particular place.

4.What’s the best title of the passage?

A. Listen to your footsteps B. Applaud pattern recognition

C. Love the way you walk D. Better the mats you step on

Answer

1.D

2.D

3.A

4.C

【解析】

这是一篇说明文。主要说明了多年来，研究人员一直使用摄像机和电脑来分析人们的步态，爱尔兰国立大学的Galway团队一直在寻找一种更好的识别步态的方法，而他们的方法是:压敏垫。

1.细节理解题。

2.推理判断题。第六到八段在叙述目前有些最新的压力传感垫在里面植入了光纤，并举了一些应用的例子，新的垫子功能更好是因为里面的光纤，故A错误；因为植入了光纤，很微小的形变都能被发现，所以不需要足够的压力，故B选项错误；C错误，垫子不能治病；在一些特定的地方，人们被提前录入自己的行走习惯，就像指纹、面部识别一样来验证他们的身份。

3.词义猜测题。很难模仿某人的走路习惯来骗过“垫子步伐识别系统”。

4.主旨大意题。文章主要讲了我们每个人走路的习惯、方式都有所不同，并举了一些通过检测人们走路的方式来进行的应用。A选项“听你的脚步”只能概括文章第一段所讲的内容，而且文章主要在讲的不是听，而是通过压力测试；B选项文章没有提及，完全无关；D选项“把垫子变得更好”只能概括文章后半部分内容，不足以成为标题。综上故C选项最符合题意。