★★★ ＜第37回知的財産翻訳検定試験【第18回英文和訳】＞ ★★★
≪１級課題 -電気・電子工学-≫【解答にあたっての注意】
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問１．以下は、ハイブリッド電力飛行機の従来技術について記載された背景技術です。***START***から***END***までを訳してください。
As illustrated in FIG. 1, the large fraction of commercial aircraft
flights are less than 1,500 miles; in particular, more than 90% of high-traffic
scheduled flights are less than 1,500 nautical miles (nm) (see, G. K. W.
Kenway et al, Reducing Aviation's Environmental Impact Through Large
Aircraft For Short Ranges, 48th AIAA Aerospace Sciences Meeting, 2010).
This phenomenon extends to business jets as well; for example, nearly 70%of Gulfstream G450 domestic flights in the US in 2011 were to stages under
1,150 miles (Table 1).

*** START ***In spite of the foregoing, a majority of conventional commercial
aircraft are designed for considerably longer flight ranges, even though large
fractions of their flights are on stages less than 1,500 miles.

In particular,

driven by the range-independent performance of the gas turbines used inthese aircraft, conventional commercial aircraft are designed for optimal
performance at long ranges, typically over 3,500 miles.

The higher

maximum take-off weight and cruise speed requirements given aircraft
designed for longer ranges translate to a higher operating empty weight, andin turn, to a higher induced drag and fuel burn.

As a result, as illustrated

in FIG. 2, as much as 50% of global greenhouse gas emissions (“fuel burn”)
generated by conventional commercial aircraft arises from sub-1,500 mile
flight stages.
*** END ***The foregoing illustrates that, in the global mobilization to mitigate
the planetary threat of climate change, aviation has long been a prominent
outlier.

In view of the foregoing, in 2016 the National Academies ofSciences, Engineering and Medicine published recommendations on a30-year national research agenda to reduce emissions from commercialaviation (see “Commercial Aircraft Propulsion and Energy Systems
Research: Reducing Global Carbon Emissions,” National Academies ofSciences, Engineering and Medicine, 2016, hereafter “the NASEM report”).

問２．以下は、カメラのブレ補正に関する技術について記載された発明の実施の形態です。*** START ***から*** END ***までを翻訳してください。
数式は【数１】【数２】等と訳出し、式自体の貼付けは不要です。
Capturing and recording a photograph, for example by a camera,
involves gathering the light reflected or emanating from a subject, passing it
through an optical system, such as a series of lenses, and directing it onto alight sensitive recording medium.

A typical recording medium intraditional analog photography is a film that is coated with light sensitive
material.

During processing of the exposed film, the image is fixed andrecorded.

In digital cameras, the recording medium is typically a dense

arrangement of light sensors, such as a Charge-Coupled Device (CCD) or aCMOS sensor.
The recording medium continuously captures the impression of thelight that falls upon it as long as the camera shutter is open. Therefore, ifthe camera and the subject are moving with respect to each other (such as inthe case when the user is unsteady and is shaking the camera, or when thesubject is moving), the recorded image becomes blurred.

To reduce thiseffect, a fast shutter speed can be used, thereby reducing the amount ofmotion occurring while the shutter is open.

However, this reduces theamount of light from the subject captured on the recording medium, which
can adversely affect image quality.

In addition, increasing the shutter

speed beyond a certain point is not always practical.

Therefore, undesired

motion blur occurs in many pictures taken by both amateur and professional
photographers.
The nature of the blur is that the light reflected from a reference
point on the subject does not fall on a single point on the recording medium,but rather it ‘travels’ across the recording medium.

Thus, a spread-out, orsmudged, representation of the reference point is recorded.
Generally, all points of the subject move together, and the optics ofthe camera and the recording medium also move together.

For example, inthe case of a photograph of a moving car, wherein an image of the car isblurred due to uniform motion of all parts of the car.

In other words, theimage falling on the recording medium ‘travels’ uniformly across therecording medium, and all points of the subject blur in the same manner.
*** START ***The nature of the blur resulting from uniform relative motion can be
expressed mathematically.

In a 2-dimensional space with discrete

coordinate indices ‘n’ and ‘m’, the undistorted image of the subject can berepresented by s(n,m), and a transfer function h(n,m) can be used torepresent the blur. Note that h(n,m) describes the way the image ‘travels’on the recording medium while it is captured.

The resulting image that isrecorded, r(n,m), is given by:where ** represents 2-dimensional convolution.

The mathematicaloperation of convolution is well known to those skilled in the art anddescribes the operation:

In the sum operations in Equation (2), the summation limits areinfinite.

In practice, the summations are not infinite, since the support

region of the transfer function is finite.

In other words, the region wherethe function is non-zero is limited by the time the camera shutter is open andthe amount of motion.

Therefore, the summation is calculated for only theindices of the transfer function where the function itself is non-zero, forexample, from i = −N ... N and j = −M ... M.
If the transfer function h(n,m) is known, or its estimate is available,
the blur that it represents can be “undone” or compensated for in a processor
or in a computer program, and a corrected image can be obtained, as follows.
Represent the “reverse” of the transfer function h(n,m) as h−1(n,m) such that:

where δ(n,m) is the 2-dimensional Dirac delta function, which is:

The delta function has the property that when convolved withanother function, it does not change the nature of that function. Therefore,
once h(n,m) and hence h−1(n,m) are known, an image r(n,m) can be put
through a correcting filter, called a “deconvolution filter”, which implements
the inverse transfer function w(n,m) = h−1(n,m) and undoes the effect of blur.
Then:and the correct image data s(n,m) is recovered.
The deconvolution filter in this example is such that:*** END ***Because of the property that the deconvolution operation forces theoutput of the convolution to be zero for all but one index, this method iscalled the “zero-forcing algorithm”.

The zero-forcing algorithm itself is but

one method that can be used, but there are others possible also, such as theleast mean-square algorithm described in more detail below.

問３．以下は、スマートフォンなどの携帯端末における指紋認証に関する技術について記載された特許請求の範囲です。以下の全文を翻訳してください。
What is claimed is:1.

An apparatus, comprising:a display;a fingerprint sensor system; anda control system configured to:access a data structure that includes historical fingerprint location

data, the historical fingerprint location data including information
corresponding to prior instances of fingerprint image data obtained fromeach fingerprint sensor area of a plurality of fingerprint sensor areas of thefingerprint sensor system, wherein the historical fingerprint location data
indicates a success ratio S/T for each fingerprint sensor area of the pluralityof fingerprint sensor areas, S being a number of successful attempts toobtain prior fingerprint image data from each of the plurality of fingerprint
sensor areas and T being a total number of attempts to obtain priorfingerprint image data from each of the plurality of fingerprint sensor areas;
identify, based at least in part on the historical fingerprint location
data, a selected fingerprint sensor area of the plurality of fingerprint sensor
areas, wherein the control system is configured to identify the selectedfingerprint sensor area based, at least in part, on the success ratio;
control the display to prompt, via at least one visual notification on
the display, a user to place a digit within or on the selected fingerprint sensor
area; andobtain, via the fingerprint sensor system, current fingerprint image
data of the digit from the selected fingerprint sensor area.
2.

The apparatus of claim 1, wherein the historical fingerprint location

data indicates a number of prior instances during which prior fingerprint
image data has been obtained from each fingerprint sensor area of theplurality of fingerprint sensor areas and wherein the control system isconfigured to identify the selected fingerprint sensor area based, at least inpart, on the number of prior instances.
3.

The apparatus of claim 1, wherein the control system is configured

to identify the selected fingerprint sensor area based, at least in part, onwhether the success ratio corresponding to a fingerprint sensor area equals
or exceeds a success ratio threshold.