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 .
Examiner's Note
The Examiner respectfully requests of the Applicant in preparing responses, to fully consider the entirety of the reference(s) as potentially teaching all or part of the claimed invention. It is noted, REFERENCES ARE RELEVANT AS PRIOR ART FOR ALL THEY CONTAIN. “The use of patents as references is not limited to what the patentees describe as their own inventions or to the problems with which they are concerned. They are part of the literature of the art, relevant for all they contain.” In re Heck, 699 F.2d 1331, 1332-33, 216 USPQ 1038, 1039 (Fed. Cir. 1983) (quoting In re Lemelson, 397 F.2d 1006, 1009, 158 USPQ 275, 277 (CCPA 1968)). A reference may be relied upon for all that it would have reasonably suggested to one having ordinary skill in the art, including non-preferred embodiments (see MPEP 2123). The Examiner has cited particular locations in the reference(s) as applied to the claim(s) above for the convenience of the Applicant. Although the specified citations are representative of the teachings of the art and are applied to the specific limitations within the individual claim(s), typically other passages and figures will apply as well.
Information Disclosure Statement
The information disclosure statement (IDS) was submitted on 09/29th/2023. The submission is in compliance with the provisions of 37 CFR 1.97. Accordingly, the information disclosure statement is being considered by the examiner.
Claim Rejections - 35 USC § 101
101 Rejection
35 U.S.C. 101 reads as follows:
Whoever invents or discovers any new and useful process, machine, manufacture, or composition of matter, or any new and useful improvement thereof, may obtain a patent therefor, subject to the conditions and requirements of this title.
Claim 1 is rejected under 35 USC § 101 because the claimed invention is directed to non-statutory subject matter
Step 1 Analysis:
Claims 1-5 are directed to a method which is directed to a process, one of the statutory categories. Claims 6-10 are directed to an apparatus, which is directed to a machine, one of the statutory categories. Claim 11 is directed to an electronic device which is directed to a machine, one of the statutory categories. Claim 12 is directed to a non-transitory computer readable storage medium which is directed to a product, one of the statutory categories.
Regarding Claim 1:
Claim 1 is rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more.
Step 2A Prong 1 Analysis:
Claim 1 recites in part process steps which, under the broadest reasonable interpretation, are a series of mental processes including an observation, evaluation, judgment or opinion that could be performed in the human mind or with the aid of pencil and paper. If a claim, under its broadest reasonable interpretation, covers a mental process or a mathematical concept but for the recitation of generic computer components, then it falls within the “Mental Process” grouping of abstract ideas. The claim recites in part:
summing intermediate data output by the plurality of operation units to acquire an operation result corresponding to each of the operation cycles Under the broadest reasonable interpretation, this limitation is a process step that covers a mental process including observation, evaluation, judgment or opinion that could be performed in the human mind or with the aid of pencil and paper (such as an operator adding numbers). If a claim, under its broadest reasonable interpretation, covers a mental process but for the recitation of generic computer components, then it falls within the “Mental Process” grouping of abstract ideas.
calculating a total number of operation cycles and an image matrix corresponding to each of the operation cycles from dimensions of a convolution kernel and dimensions of the original image Under the broadest reasonable interpretation, this limitation is a process step that covers a mental process including observation, evaluation, judgment or opinion that could be performed in the human mind or with the aid of pencil and paper (such as an operator calculating dimensions and determining a number of cycles based on those calculations). If a claim, under its broadest reasonable interpretation, covers a mental process but for the recitation of generic computer components, then it falls within the “Mental Process” grouping of abstract ideas.
Performing multiplication operations on pre-stored weight data and the image data to acquire intermediate data Under the broadest reasonable interpretation, this limitation is a process step that covers a mental process including observation, evaluation, judgment or opinion that could be performed in the human mind or with the aid of pencil and paper (such as an operator multiplying two numbers to obtain another). If a claim, under its broadest reasonable interpretation, covers a mental process but for the recitation of generic computer components, then it falls within the “Mental Process” grouping of abstract ideas.
Step 2A Prong 2 Analysis:
The judicial exception is not integrated into a practical application. In particular, the claim recites the additional element of:
A method of neural network-based operation is recited at a high-level of generality and amounts to no more than mere instructions to apply the exception using a generic computer component (See MPEP 2106.05(f)).
acquiring an original image is recited at a high-level of generality and amounts to extra-solution activity of gathering data (MPEP 2106.05(g): i.e. pre-solution activity of gathering data for use in the claimed process.
the image matrix comprising image data in multiple rows and columns amounts to no more than generally linking the use of a judicial exception to a particular technological environment or field of use. As explained by the Supreme Court, a claim directed to a judicial exception cannot be made eligible "simply by having the applicant acquiesce to limiting the reach of the patent for the formula to a particular technological use." Diamond v. Diehr, 450 U.S. 175, 192 n.14, 209 USPQ 1, 10 n. 14 (1981). Thus, limitations that amount to merely indicating a field of use or technological environment in which to apply a judicial exception do not amount to significantly more than the exception itself, and cannot integrate a judicial exception into a practical application.
acquiring, for the image matrix corresponding to each of the operation cycles, the image data by a plurality of operation units in parallel according to an operation instruction is recited at a high-level of generality and amounts to extra-solution activity of gathering data (MPEP 2106.05(g): i.e. pre-solution activity of gathering data for use in the claimed process.
gathering all operation results for the total number of operation cycles to acquire a target operation result is recited at a high-level of generality and amounts to extra-solution activity of gathering data (MPEP 2106.05(g): i.e. pre-solution activity of gathering data for use in the claimed process.
Step 2B Analysis:
Claim 1 does not include additional elements that are sufficient to amount to significantly more than the judicial exception. As discussed above, the additional elements of:
A method of neural network-based operation is recited at a high-level of generality and amounts to no more than mere instructions to apply the exception using a generic computer component (See MPEP 2106.05(f)).
acquiring an original image is recited at a high-level of generality and amounts to extra-solution activity of gathering data (MPEP 2106.05(g): i.e. pre-solution activity of gathering data for use in the claimed process. The courts have found limitations directed to obtaining information electronically, recited at a high level of generality, to be well-understood, routine, and conventional (see MPEP 2106.05(d)(II), “receiving or transmitting data over a network”, "electronic record keeping," and "storing and retrieving information in memory").
the image matrix comprising image data in multiple rows and columns amounts to no more than generally linking the use of a judicial exception to a particular technological environment or field of use. As explained by the Supreme Court, a claim directed to a judicial exception cannot be made eligible "simply by having the applicant acquiesce to limiting the reach of the patent for the formula to a particular technological use." Diamond v. Diehr, 450 U.S. 175, 192 n.14, 209 USPQ 1, 10 n. 14 (1981). Thus, limitations that amount to merely indicating a field of use or technological environment in which to apply a judicial exception do not amount to significantly more than the exception itself, and cannot integrate a judicial exception into a practical application.
acquiring, for the image matrix corresponding to each of the operation cycles, the image data by a plurality of operation units in parallel according to an operation instruction is recited at a high-level of generality and amounts to extra-solution activity of gathering data (MPEP 2106.05(g): i.e. pre-solution activity of gathering data for use in the claimed process. The courts have found limitations directed to obtaining information electronically, recited at a high level of generality, to be well-understood, routine, and conventional (see MPEP 2106.05(d)(II), “receiving or transmitting data over a network”, "electronic record keeping," and "storing and retrieving information in memory").
gathering all operation results for the total number of operation cycles to acquire a target operation result is recited at a high-level of generality and amounts to extra-solution activity of gathering data (MPEP 2106.05(g): i.e. pre-solution activity of gathering data for use in the claimed process. The courts have found limitations directed to obtaining information electronically, recited at a high level of generality, to be well-understood, routine, and conventional (see MPEP 2106.05(d)(II), “receiving or transmitting data over a network”, "electronic record keeping," and "storing and retrieving information in memory").
For the reasons above, claim 1 is rejected as being directed to non-patentable subject matter under §101.
The additional limitations of the dependent claims contain no additional elements that provide a practical application or amount to significantly more than the abstract idea and are addressed briefly below
Dependent claim 2 recites:
Step 2A Prong 1:
determining a weight matrix based on the dimensions of the convolution kernel, wherein the weight matrix comprises weight data in multiple rows and columns, and the convolution kernel has a height equal to the number of rows of the weight matrix and has a width equal to the number of columns of the weight matrix; and pre-storing by the plurality of operation units the weight data in corresponding rows of the weight matrix respectively under the broadest reasonable interpretation, this limitation is a process step that covers a mental process including observation, evaluation, judgment or opinion that could be performed in the human mind or with the aid of pencil and paper (such as an operator determining the numbers to enter in a first matrix based on different positions in a second matrix). If a claim, under its broadest reasonable interpretation, covers a mental process but for the recitation of generic computer components, then it falls within the “Mental Process” grouping of abstract ideas.
Step 2A Prong 2: The claim does not include additional elements that would integrate the judicial exception into a practical application.
Step 2B: The claim does not include additional elements that are sufficient to amount to significantly more that the judicial exception.
For the reasons above, claim 2 is rejected as being directed to non-patentable subject matter under §101.
Dependent claim 3 recites:
Step 2A Prong 1: The claim is directed to the same judicial exception (mental process) recited above.
Step 2A Prong 2: The judicial exception is not integrated into a practical application. In particular, the additional element of:
wherein acquiring, for the image matrix corresponding to each of the operation cycles, the image data by the plurality of operation units in parallel according to the operation instruction comprises: acquiring, for the image matrix corresponding to each of the operation cycles, the image data in corresponding rows of the image matrix according to the operation instruction by the plurality of operation units respectively is recited at a high-level of generality and amounts to extra-solution activity of gathering data (MPEP 2106.05(g): i.e. pre-solution activity of gathering data for use in the claimed process. The courts have found limitations directed to obtaining information electronically, recited at a high level of generality, to be well-understood, routine, and conventional (see MPEP 2106.05(d)(II), “receiving or transmitting data over a network”, "electronic record keeping," and "storing and retrieving information in memory").
Step 2B: In accordance with Step 2B, the claim does not include additional elements that are sufficient to amount to significantly more that the judicial exception. As discussed above, the additional elements of:
wherein acquiring, for the image matrix corresponding to each of the operation cycles, the image data by the plurality of operation units in parallel according to the operation instruction comprises: acquiring, for the image matrix corresponding to each of the operation cycles, the image data in corresponding rows of the image matrix according to the operation instruction by the plurality of operation units respectively is recited at a high-level of generality and amounts to extra-solution activity of gathering data (MPEP 2106.05(g): i.e. pre-solution activity of gathering data for use in the claimed process. The courts have found limitations directed to obtaining information electronically, recited at a high level of generality, to be well-understood, routine, and conventional (see MPEP 2106.05(d)(II), “receiving or transmitting data over a network”, "electronic record keeping," and "storing and retrieving information in memory").
For the reasons above, claim 3 is rejected as being directed to non-patentable subject matter under §101.
Dependent claim 4 recites:
Step 2A Prong 1:
wherein acquiring, for the image matrix corresponding to each of the operation cycles, the image data by the plurality of operation units in parallel according to the operation instruction comprises: changing, for the image matrix corresponding to a current operation cycle, one element of each row of the image data, with the changed image matrix serving as an image matrix corresponding to a next operation cycle; and acquiring, for the image matrix corresponding to the next operation cycle, changed image data in corresponding rows by the plurality of operation units, respectively under the broadest reasonable interpretation, this limitation is a process step that covers a mental process including observation, evaluation, judgment or opinion that could be performed in the human mind or with the aid of pencil and paper (such as an operator modifying the data in a matrix). If a claim, under its broadest reasonable interpretation, covers a mental process but for the recitation of generic computer components, then it falls within the “Mental Process” grouping of abstract ideas.
Step 2A Prong 2: The claim does not include additional elements that would integrate the judicial exception into a practical application.
Step 2B: The claim does not include additional elements that are sufficient to amount to significantly more that the judicial exception.
For the reasons above, claim 4 is rejected as being directed to non-patentable subject matter under §101.
Dependent claim 5 recites:
Step 2A Prong 1: The claim is directed to the same judicial exception (mental process) recited above.
Step 2A Prong 2: The judicial exception is not integrated into a practical application. In particular, the additional element of:
Wherein the plurality of operation units form operation unit groups, and the dimensions of the convolution kernel comprise the number of input channels which is same as the number of the operation unit groups amounts to no more than generally linking the use of a judicial exception to a particular technological environment or field of use. As explained by the Supreme Court, a claim directed to a judicial exception cannot be made eligible "simply by having the applicant acquiesce to limiting the reach of the patent for the formula to a particular technological use." Diamond v. Diehr, 450 U.S. 175, 192 n.14, 209 USPQ 1, 10 n. 14 (1981). Thus, limitations that amount to merely indicating a field of use or technological environment in which to apply a judicial exception do not amount to significantly more than the exception itself, and cannot integrate a judicial exception into a practical application.
Step 2B: In accordance with Step 2B, the claim does not include additional elements that are sufficient to amount to significantly more that the judicial exception. As discussed above, the additional elements of:
Wherein the plurality of operation units form operation unit groups, and the dimensions of the convolution kernel comprise the number of input channels which is same as the number of the operation unit groups amounts to no more than generally linking the use of a judicial exception to a particular technological environment or field of use. As explained by the Supreme Court, a claim directed to a judicial exception cannot be made eligible "simply by having the applicant acquiesce to limiting the reach of the patent for the formula to a particular technological use." Diamond v. Diehr, 450 U.S. 175, 192 n.14, 209 USPQ 1, 10 n. 14 (1981). Thus, limitations that amount to merely indicating a field of use or technological environment in which to apply a judicial exception do not amount to significantly more than the exception itself, and cannot integrate a judicial exception into a practical application.
For the reasons above, claim 5 is rejected as being directed to non-patentable subject matter under §101.
Claims 6-10 are rejected under 35 U.S.C 101 because the claimed invention is directed to an abstract idea without significantly more. The claims recite an apparatus with similar steps to claims 1-5, and thus are not patent eligible for the same reasons (see above).
Claim 11 is rejected under 35 U.S.C 101 because the claimed invention is directed to an abstract idea without significantly more. The claim recites an electronic device with similar steps to claim 1, and thus is not patent eligible for the same reasons (see above).
Claim 12 is rejected under 35 U.S.C 101 because the claimed invention is directed to an abstract idea without significantly more. The claim recites a non-transitory computer readable storage medium with similar steps to claim 1, and thus is not patent eligible for the same reasons (see above).
Claim Rejections - 35 USC § 102
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 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 the appropriate paragraphs of 35 U.S.C. 102 that form the basis for the rejections under this section made in this Office action:
A person shall be entitled to a patent unless –
(a)(1) the claimed invention was patented, described in a printed publication, or in public use, on sale, or otherwise available to the public before the effective filing date of the claimed invention.
Claims 1-4, 6-9, and 11-12 are rejected under 35 U.S.C. 103 as being unpatentable over BANNON (US20190026078A1).
Regarding claim 1, BANNON teaches acquiring an original image, and calculating a total number of operation cycles and an image matrix corresponding to each of the operation cycles from dimensions of a convolution kernel and dimensions of the original image, the image matrix comprising image data in multiple rows and columns ([0042] The state machine may be configured to determine how and where to shift data that is to be executed, e.g., based on inputs related to image size, filter size, stride, number of channels, and similar parameters. The examiner notes that BANNON [Fig. 10] teaches calculating a set of operands representative of a row in a data matrix (image matrix), and calculating the number of convolution cycles (operation cycles) based on how and where to shift data (the number of shifts is the number of operation cycles) based on inputs related to image size, filter size (convolution kernel dimensions), stride (operation cycle), number of channels, and similar parameters.).
acquiring, for the image matrix corresponding to each of the operation cycles, the image data by a plurality of operation units in parallel according to an operation instruction, and performing multiplication operations on pre-stored weight data and the image data to acquire intermediate data ([0033] Unlike common software implementations of formatting functions that are performed by a CPU or GPU to convert a convolution operation into a matrix-multiply by rearranging data to an alternate format that is suitable for a fast matrix multiplication, various hardware implementations of the present disclosure re-format data on the fly and make it available for execution, e.g., 96 pieces of data every cycle, in effect, allowing a very large number of elements of a matrix to be processed in parallel, thus efficiently mapping data to a matrix operation. In embodiments, for 2N fetched input data 2N2 compute data may be obtained in a single clock cycle. This architecture results in a meaningful improvement in processing speeds by effectively reducing the number of read or fetch operations employed in a typical processor architecture as well as providing a paralleled, efficient and synchronized process in performing a large number of mathematical operations across a plurality of data inputs. The examiner notes that BANNON teaches performing convolution processing (convolution kernel represents pre-stored weight data) on a large number of elements of a matrix in parallel in order to efficiently map data to a matrix operation).
summing intermediate data output by the plurality of operation units to acquire an operation result corresponding to each of the operation cycles; and gathering all operation results for the total number of operation cycles to acquire a target operation result ([0055-0056] In embodiments, convolution 500 multiplies a rectangular input matrix 504 with a rectangular weight matrix 532 to obtain partial dot products. The partial dot products may then be summed by adder 546 in order to generate an accumulated dot product 514 (i.e., an integer) that represents an output pixel 514 in the output image. In embodiments, each pixel in output channel OC is generated by multiplier 542 and adder 544. In embodiments, the value of the partial dot products correspond to the application of weight matrix 532 in its entirety to area 504 of the input image 502. In other words, each weight 532 is dot multiplied by multiplier 542 with area 504 to produce a partial dot product, then the partial dot products are accumulated in accumulator 540 to generate an accumulated output that represents the convolution. The examiner notes that BANNON teaches a multiplier and an adder (operation units) that sums the partial dot products of the multiplier (intermediate data outputs) to acquire an accumulated dot product (operation result) representing an output pixel in an output image, and an accumulator that accumulates the pixels to generate an output that represents the convolution).
Regarding claim 2, BANNON teaches determining a weight matrix based on the dimensions of the convolution kernel, wherein the weight matrix comprises weight data in multiple rows and columns, and the convolution kernel has a height equal to the number of rows of the weight matrix and has a width equal to the number of columns of the weight matrix ([0058] As depicted in FIG. 5, input matrix 504 is a KxxKy (i.e., 3x3) matrix that may be combined with a 3x3 weight matrix 532 across 3 input channels, i.e., 3x3xIC, such that the depths match and produce a single element, dot product 514, in the output plane. Each dot product 514 in output channel 512 is the result of a dot multiplication.).
pre-storing by the plurality of operation units the weight data in corresponding rows of the weight matrix respectively ([0063] In addition, in circumstances in which weight data matrix 604 is known then row 620 may be generated and stored in a vectorized format without the use of a formatter.).
Regarding claim 2, BANNON teaches determining a weight matrix based on the dimensions of the convolution kernel, wherein the weight matrix comprises weight data in multiple rows and columns, and the convolution kernel has a height equal to the number of rows of the weight matrix and has a width equal to the number of columns of the weight matrix ([0058] As depicted in FIG. 5, input matrix 504 is a KxxKy (i.e., 3x3) matrix that may be combined with a 3x3 weight matrix 532 across 3 input channels, i.e., 3x3xIC, such that the depths match and produce a single element, dot product 514, in the output plane. Each dot product 514 in output channel 512 is the result of a dot multiplication.).
pre-storing by the plurality of operation units the weight data in corresponding rows of the weight matrix respectively ([0063] In addition, in circumstances in which weight data matrix 604 is known then row 620 may be generated and stored in a vectorized format without the use of a formatter.).
Regarding claim 3, BANNON teaches wherein acquiring, for the image matrix corresponding to each of the operation cycles, the image data by the plurality of operation units in parallel according to the operation instruction comprises: acquiring, for the image matrix corresponding to each of the operation cycles, the image data in corresponding rows of the image matrix according to the operation instruction by the plurality of operation units respectively ([0028] Data formatter 210 converts two-dimensional or three-dimensional (e.g., a 3x3x3 cube) data comprising data input matrix 206 into a single vector or string that may be represented by a row or column, thereby, linearizing or vectorizing data input matrix 206).
Regarding claim 4, BANNON teaches wherein acquiring, for the image matrix corresponding to each of the operation cycles, the image data by the plurality of operation units in parallel according to the operation instruction comprises: changing, for the image matrix corresponding to a current operation cycle, one element of each row of the image data, with the changed image matrix serving as an image matrix corresponding to a next operation cycle ([0071-0072] At step 1006, the first set of operands is dot-multiplied with the second set of operands to obtain one or more dot-products. In certain embodiments, this set operation across the sets of operands is performed in a single clock cycle. At step 1008, the dot-products may be used to convolve an image with a filter to produce a convolution result.).
acquiring, for the image matrix corresponding to the next operation cycle, changed image data in corresponding rows by the plurality of operation units, respectively ([0073] At step 1010, the convolution result is further processed to enhance the image output. This further processing may occur using a non-linear function, a normalization operation or a pooling operation.).
Claims 6-9 are substantially similar to claims 1-4, and thus are rejection under 35 U.S.C 102 for the same reasons (see above).
Claims 11-12 are substantially similar to claim 1, and thus are rejection under 35 U.S.C 102 for the same reasons (see above).
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 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.
Claims 5, and 10 are rejected under 35 U.S.C. 103 as being unpatentable over BANNON (US20190026078A1), in view of LEE (US20210127135A1).
Regarding claim 5, BANNON teaches the method according to claim 1. However, BANNON is not relied upon to explicitly teach Wherein the plurality of operation units form operation unit groups, and the dimensions of the convolution kernel comprise the number of input channels which is same as the number of the operation unit groups. On the other hand, LEE teaches Wherein the plurality of operation units form operation unit groups, and the dimensions of the convolution kernel comprise the number of input channels which is same as the number of the operation unit groups ([0386] Because a depth of the filter kernel is equal to the number of input channels, each filter kernel includes a matrix of weights having a number corresponding to (number of rows )x(number of columns )x(number of input channels. The examiner notes that BANNON and LEE are both directed to convolutional neural networks and are thus considered to be reasonably analogous. Therefore, it would have been obvious to someone of ordinary skill in the art before the effective filing date of the claimed invention to have modified BANNON’s convolution operation to incorporate Wherein the plurality of operation units form operation unit groups, and the dimensions of the convolution kernel comprise the number of input channels which is same as the number of the operation unit groups as taught by LEE [0386] to improve the performance of AI up-scaling [0271]).
Claim 10 is substantially similar to claim 5, and thus is rejection under 35 U.S.C 103 for the same reasons (see above).
Conclusion
The following reference have been determined to be related to the application, but were not applied in any specific rejection. They are nonetheless listed below for reference.
AMTHOR (US20220382038A1)
“AMTHOR teaches a method for processing microscope images to generate an image processing result”
RUFF (US20210049463A1)
“RUFF teaches a computational device which performs the operation of a bank of convolutional filters commonly used in a convolutional neural network”
Any inquiry concerning this communication or earlier communications from the examiner should be directed to SHAMCY ALGHAZZY whose telephone number is (571)272-8824. The examiner can normally be reached Monday-Friday between 9AM and 6PM.
Examiner interviews are available via telephone, in-person, and video conferencing using a USPTO supplied web-based collaboration tool. To schedule an interview, applicant is encouraged to use the USPTO Automated Interview Request (AIR) at http://www.uspto.gov/interviewpractice.
If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, OMAR FERNANDEZ RIVAS can be reached on (571)272-2589. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
Information regarding the status of published or unpublished applications may be obtained from Patent Center. Unpublished application information in Patent Center is available to registered users. To file and manage patent submissions in Patent Center, visit: https://patentcenter.uspto.gov. Visit https://www.uspto.gov/patents/apply/patent-center for more information about Patent Center and https://www.uspto.gov/patents/docx for information about filing in DOCX format. For additional questions, contact the Electronic Business Center (EBC) at 866-217-9197 (toll-free). If you would like assistance from a USPTO Customer Service Representative, call 800-786-9199 (IN USA OR CANADA) or 571-272-1000.
/SHAMCY ALGHAZZY/Examiner, Art Unit 2128
/OMAR F FERNANDEZ RIVAS/Supervisory Patent Examiner, Art Unit 2128
Prosecution Insights