DETAILED ACTION
Notice of Pre-AIA or AIA Status
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
Claim Rejections - 35 USC § 103
In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis (i.e., changing from AIA to pre-AIA ) for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status.
The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
The factual inquiries for establishing a background for determining obviousness under 35 U.S.C. 103 are summarized as follows:
1. Determining the scope and contents of the prior art.
2. Ascertaining the differences between the prior art and the claims at issue.
3. Resolving the level of ordinary skill in the pertinent art.
4. Considering objective evidence present in the application indicating obviousness or nonobviousness.
Claim(s) 1-2,4,6,9-10,13-22,25,28-32,34-37 and 39-47 are rejected under 35 U.S.C. 103 as being unpatentable over Non-Patent Literature titled, “Improvement of the cotton fiber length measurements using High Volume Instrument (HVI) fibrogram” (herein Sayeed) in view of Non-Patent Literature titled, “Smoothing” (herein Blobel).
Regarding claim 1, Sayeed teaches A computer-implemented method of reconstructing a fiber length distribution of a fiber from a fibrogram of the fiber, said method comprising:
receiving the fibrogram, wherein the fibrogram comprises a curve representing the number of fibers present at a given length from the base of the fiber (bundle of fibers is subsampled from the sample and placed in the fibrosampler… output of this optical system plotted as the function of distance is referred to as the fibrogram, p. 30);
determining an end of the fibrogram (analyze the whole fibrogram curve, p. 40; Fig. 1.15, p. 37 shows distribution);
and estimating the fiber length distribution of the fiber from the
Further regarding claim 1, Sayeed does not teach, “applying a windowed curve-fitting procedure to smoothen the fibrogram curve.” However, Blobel teaches it is known in the art to use a window size from a set for a smoothening operation (p. 4).
Regarding claim 2, Sayeed teaches reconstructing an initial and missing portion of the fibrogram (p. vi teaches curves are not reported [i.e. missing] and thus can be exported without loss of information), wherein the reconstructing occurs through the utilization of a convex function (Fig. 2.1 teaches UHML being convex function).
Regarding claim 4, Sayeed teaches a step of constructing the fibrogram, wherein the fibrogram is constructed through the utilization of a High Volume Instrument (HVI) (model contains HVI parameters, p. vii).
Regarding claim 6, Sayeed teaches wherein the end of the fibrogram represents a length value of the fibrogram that is zero, a first discrete difference of the fibrogram that is greater than or equal to zero, or a point at which the longest fibers have been scanned after which the remaining data is assumed to be zero (Fig. 1.15, p. 37 shows length of 0 in fibrogram).
Regarding claim 9, Sayeed does not teach, “wherein a polynomial curve fit procedure is utilized to determine the end of the fibrogram.” However, Blobel teaches it is known in the art to use polynomials to apply to the higher derivatives, for smoothing the final result (p. 13).
Regarding claim 10, Sayeed does not teach, “wherein the windowed curve-fitting procedure comprises polynomial smoothing through a sliding window method, wherein the sliding window method utilizes differentiable and parametric functions, and wherein when fit to underlying data in a given window, the function is convex within a domain of the window.” However, Blobel teaches parametric and differentiable polynomial functions for window smoothing (p. 10-13), with the function being convex (p. 11).
Regarding claim 13, Sayeed does not teach, “wherein the windowed curve-fitting procedure also removes slightly concave portions from the fibrogram curve.” However, Blobel teaches it is known in the art to fit a line to remove concave portions, as shown in Fig. 28-29.
Regarding claim 14, Sayeed does not teach, “wherein the windowed curve-fitting procedure also estimates derivatives of fibrogram equations.” However, Blobel teaches orthogonal polynomials is used to estimate the higher derivatives of the smooth signal from the data (p. 13).
Regarding claim 15, Sayeed teaches, “estimating of the underlying fiber length distribution” (p. 33-36). Sayeed does not teach, “applying of the windowed curve-fitting procedure.” However, Blobel teaches windowed curve fitting (p. 3-4). Neither Sayeed nor Blobel teach doing these steps simultaneously. However, in the absence of new or unexpected results it would have been obvious to one of ordinary skill in the art to accomplish these steps simultaneously. Based on MPEP 2144.04 IV C, changing a sequence of process steps is a matter of choice which a person of ordinary skill in the art would have found obvious absent persuasive evidence that the particular configuration of the claimed was significant. See Ex parte Rubin, 128 USPQ 440 (Bd. App. 1959), and In re Burhans, 154 F.2d 690, 69 USPQ 330 (CCPA 1946). Note that according to § MPEP 2144, “Office personnel may invoke legal precedent as a source of supporting rationale when warranted and appropriately supported.”
Regarding claim 16, Sayeed teaches wherein the estimating of the underlying fiber length distribution comprises estimating a cumulative distribution function and a probability function (cumulative distribution of AFIS length distribution, p. 82; cumulative distribution of fiber length histogram, p. 113).
Regarding claim 22, Sayeed teaches wherein the fiber is in the form of an aggregated fiber, and wherein the aggregated fiber is in the form of a fiber beard, a fiber bundle, a yarn, or combinations thereof (yarn, p. vii).
Regarding claim 25, Sayeed teaches wherein the fiber is selected from the group consisting of textile fibers, cotton fibers, hemp fibers, natural bast fibers, flax fibers, jute fibers, kenaf fibers, milkweed fibers, ramie fibers, artificial fibers, or combinations thereof (cotton fiber, p. vi).
Regarding claim 28, Sayeed teaches a step of assessing fiber quality based on the estimated fiber length distribution (p. 18 teaches fiber length is main contributor to quality).
Regarding claim 29, Sayeed teaches a step of adjusting one or more fiber-related conditions based on the estimated fiber length distribution (p. 56 teaches stability study of two distinct fibrograms with two study lengths after conditioning).
Regarding claim 30, Sayeed teaches wherein the adjusting comprises instructing a user to adjust the one or more fiber-related conditions based on the estimated fiber length distribution (p. 56-57 teach conditions were monitored to make sure there was no issue, for proper conditioning of the test).
Regarding claim 31, Sayeed teaches wherein the adjusting occurs manually by a user (micronaire needs to be entered manually as it is one of the variables used to determine the mass of the sample being broken, p. 77; p. 56-57 also teach conditions were monitored to make sure there was no issue with air conditioning).
Regarding claim 32, Sayeed teaches wherein the one or more fiber-related conditions are selected from the group consisting of fiber growth conditions, fiber storage conditions, fiber milling conditions, fiber transport conditions, fiber breeding conditions, or combinations thereof (weathering, harvesting, ginning, and storage conditions, impact fiber quality, p. 9; p. 56-57 teach air conditioning).
Regarding claim 34, Sayeed teaches A computing device for reconstructing a fiber length distribution of a fiber from a fibrogram of the fiber, wherein the computing device comprises one or more computer readable storage mediums having a program code embodied therewith (p. 56 teaches use of MATLAB which is a computing software platform run on a PC), wherein the program code comprises programming instructions for:
receiving the fibrogram, wherein the fibrogram comprises a curve representing the number of fibers present at a given length from the base of the fiber; determining an end of the fibrogram; applying a windowed curve-fitting procedure to smoothen the fibrogram curve; and estimating the fiber length distribution of the fiber from the smoothened fibrogram curve.
receiving the fibrogram, wherein the fibrogram comprises a curve representing the number of fibers present at a given length from the base of the fiber (bundle of fibers is subsampled from the sample and placed in the fibrosampler… output of this optical system plotted as the function of distance is referred to as the fibrogram, p. 30);
determining an end of the fibrogram (analyze the whole fibrogram curve, p. 40; Fig. 1.15, p. 37 shows distribution);
and estimating the fiber length distribution of the fiber from the
Further regarding claim 34, Sayeed does not teach, “applying a windowed curve-fitting procedure to smoothen the fibrogram curve.” However, Blobel teaches it is known in the art to use a window size from a set for a smoothening operation (p. 4).
Regarding claim 35, Sayeed teaches reconstructing an initial and missing portion of the fibrogram (p. vi teaches curves are not reported [i.e. missing] and thus can be exported without loss of information).
Regarding claim 36, Sayeed does not teach, “wherein the program code utilizes a polynomial curve fit procedure to determine the end of the fibrogram.” However, Blobel teaches it is known in the art to use polynomials to apply to the higher derivatives, for smoothing the final result (p. 13).
Regarding claim 37, Sayeed does not teach, “polynomial smoothing through a sliding window method, wherein the sliding window method utilizes differentiable and parametric functions, and wherein when fit to underlying data in a given window, the function is convex within a domain of the window.” However, Blobel teaches parametric and differentiable polynomial functions for window smoothing (p. 10-13), with the function being convex (p. 11).
Claims 39-42 and 46 recite the same limitations found in claims 13-16 and are rejected equivalently. See rejections of claims 13-16 and 28 above.
Regarding claim 47, Sayeed teaches programming instructions for instructing the adjustment of one or more fiber-related conditions based on the estimated fiber length distribution (p. 56 teaches stability study of two distinct fibrograms with two study lengths after conditioning), wherein the one or more fiber-related conditions are selected from the group consisting of fiber growth conditions, fiber storage conditions, fiber milling conditions, fiber transport conditions, fiber breeding conditions, or combinations thereof (weathering, harvesting, ginning, and storage conditions, impact fiber quality, p. 9; p. 56-57 teach air conditioning).
For the above claims 1-2,4,6,9-10,13-22,25,28-32,34-37 and 39-47, it would have been obvious to one of ordinary skill in the art before the time of filing to incorporate the smoothing functions of Blobel into the fiber length distribution calculations of Sayeed. One would have been motivated to do so for at least the purpose of aiding understanding of the distribution, and eliminating effects that are of no interest (p. 2, Blobel).
Allowable Subject Matter
Claims 17-21 and 43-45 are objected to as being dependent upon a rejected base claim, but would be allowable if rewritten in independent form including all of the limitations of the base claim and any intervening claims. Regarding independent claims 17 and 43 and dependents thereof, the prior art does not teach, “estimating of the underlying fiber length distribution is based on a given window size and a parametric curve.” Blobel teaches window sizes for a data set (p. 4) but does not teach estimating fiber length distribution of Sayeed based on a given window size.
Conclusion
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/WALTER L LINDSAY JR/Supervisory Patent Examiner, Art Unit 2852
/PHILIP T FADUL/Examiner, Art Unit 2852
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