CTNF 19/232,869 CTNF 100003 Notice of Pre-AIA or AIA Status 07-03-aia AIA 15-10-aia The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA. DETAILED ACTION Priority 02-26 AIA Receipt is acknowledged of certified copies of papers required by 37 CFR 1.55. Information Disclosure Statement The information disclosure statements (IDS) submitted on 06/10/2025 and 01/12/2026 were filed. The submissions are in compliance with the provisions of 37 CFR 1.97. Accordingly, the information disclosure statements are being considered by the examiner. 12-151 AIA 26-51 12-51 Status of Claims The following is a non-final office action in response to the preliminary amendment filed on 06/10/2025. Claims 1-6 are pending and have been examined. Claim 1-6 are amended. Claims 1-6 are rejected. Claim Objections 07-29-01 AIA Claim s 1-6 are objected to because of the following informalities: Claim 1, Line 5 reads, “according to time series,” when it would read clearer as, “according to a time series,” for grammatical clarity. Claim 1, Line 13 reads, “that the moving object which is moving by the predetermined amount or more ,” when it should read, “that a the moving object which is moving by a the predetermined amount or more,” to properly refer back to the limitation’s introduction in Claim 1, Lines 10-11. Claim 2, Lines 2-3 read, “that a moving object which will reach the opening before the predetermined timing,” when they should read, “that a the moving object which will reach the opening before the predetermined timing,” in order to properly refer back to the limitation’s introduction in Claim 1, Lines 14-15. Claim 3, Line 14, reads, “whether a moving object which is moving by a predetermined amount or more,” when it should read, “whether a the moving object which is moving by a the predetermined amount or more,” in order to properly refer back to the limitation’s introduction in Claim 1, Lines 10-11. Claim 4, Line 3, reads, “that a moving object which is moving by a predetermined amount or more,” when it should read, “that a the moving object which is moving by a the predetermined amount or more,” to properly refer back to the limitations introduction in Claim 1, Lines 10-11. Claim 5 is objected to based upon its dependency on Claim 1. Claim 6, Line 6 reads, “according to time series,” when it would read clearer as, “according to a time series,” for grammatical clarity. Claim 6, Line 14, reads, “that a moving object which is moving by a predetermined amount or more,” when it should read, “that a the moving object which is moving by a the predetermined amount or more,” to properly refer back to the limitations introduction in Claim 6, Lines 10-11 . Appropriate correction is required. Examiner Note: Copending Reference Application 19/235,578 (US 2026/0004,434 A1) comprises substantially similar claims to that of the current application 19/232,869 (US 2026/0002,402 A1). However, Examiner believes the similarity does not surmount to a statutory/ nonstatuatory double patenting rejection, particularly due to the “restrict a closing operation” limitation present in the independent claims. Examiner and Applicant should take note/monitor the status of the claims during prosecution to ensure no double patenting rejection arises. The first independent claim of both applications has been posted below for reference. Copending Reference Application 19/235,578 US 2026/0004,434 A1 Current Office Action Application 19/232,869 US 2026/0002,402 A1 Claim 1: [A door control device comprising one or more processors configured to: control opening and closing of a door provided in an opening based on imaging data of a predetermined imaging range in an external region of the opening;] [analyze the imaging data in chronological order; from a predetermined region of the imaging data, extract one or more moving objects that move toward the opening; before at least one of the extracted moving objects reaches the opening, determine whether each of the extracted moving objects reaches the opening by a predetermined timing; ] [and execute a closing action of the door when it is determined that there is no moving object that reaches the opening by the predetermined timing.] Claim 1: [A door controller, comprising a processor for executing opening/closing control of a door provided in an opening based on image data in which there is captured a predetermined imaging range of an external area relative to the opening,] wherein the processor is configured to execute the following processing:] [analyze the image data according to time series, extract one or more moving objects which are moving toward the opening from within a predetermined area included in the imaging range, evaluate movement amounts of the moving objects toward the opening, restrict a closing operation of the door when it is determined that a moving object which is moving by a predetermined amount or more is present based on evaluation results of the movement amounts,] [and execute a closing operation of the door at a preset predetermined timing when it is determined that a moving object which is moving by a predetermined amount or more is not present and a moving object which will reach the opening before the predetermined timing is not present based on the evaluation results of the movement amounts.] Claim Rejections - 35 USC § 112 07-30-02 AIA The following is a quotation of 35 U.S.C. 112(b): (b) CONCLUSION.—The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the inventor or a joint inventor regards as the invention. The following is a quotation of 35 U.S.C. 112 (pre-AIA), second paragraph: The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the applicant regards as his invention. 07-34-01 Claim 3 is rejected under 35 U.S.C. 112(b) or 35 U.S.C. 112 (pre-AIA), second paragraph, as being indefinite for failing to particularly point out and distinctly claim the subject matter which the inventor or a joint inventor (or for applications subject to pre-AIA 35 U.S.C. 112, the applicant), regards as the invention. Claim 3 recites the limitation, " in the direction toward the door " in Line 6. There is insufficient antecedent basis for this limitation in the claim. Claims 4-5 are rejected based upon their dependency on claim 3. For the purposes of examination, the “direction toward the door,” will be interpreted as intending to refer to the (Claim1, Line 5) “moving toward the opening with a predetermined area.” Claim 3 recites the limitation, “recognizes an aggregate of adjacent blocks the scalar components of which are equal to or greater than a threshold as a moving object,” in Lines 5-6. The claim language makes it unclear whether the scalar components being greater than a threshold is necessary for a moving object to be identified. Claims 4-5 are rejected based upon their dependency on claim 3. For the purposes of examination, the language will be interpreted as if written as, “recognizes an aggregate of adjacent blocks , the scalar components of which are equal to or greater than a threshold , as a moving object,” the introduction of commas of which would make the feature explicitly clear. Claim Rejections - 35 USC § 102 07-06 AIA 15-10-15 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. 07-07-aia AIA 07-07 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 – 07-08-aia AIA (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. 07-15 AIA Claim s 1, 2, and 6 are rejected under 35 U.S.C. 102( a)(1 ) as being anticipated by Russo et al. (US 10,977,826 B1, hereinafter Russo) Claim 1 Discloses: (Currently Amended) “A door controller, comprising a processor for executing opening/closing control of a door provided in an opening based on image data in which there is captured a predetermined imaging range of an external area relative to the opening, wherein the processor is configured to execute the following processing:” Russo teaches, (Page 9, Column 1, Lines 66-67) “a safety detection camera system for door closure and associated method,” wherein, (Page, 9, Column 2, Lines 55-62) “computer program instructions may be provided to a processor … such that the instructions … create means for implementing the functions/acts specified in the flowchart and/or block diagram block or blocks,” wherein, (Page 13, Column 10, Lines 41-45) “An area of interest 450 may be defined relative to each door 430. The area of interest 450 may be an area in front of respective door 430 or may be a line, for example a line in front of or running across the threshold of door 430.” “analyze the image data according to time series, extract one or more moving objects which are moving toward the opening from within a predetermined area included in the imaging range, evaluate movement amounts of the moving objects toward the opening, restrict a closing operation of the door when it is determined that a moving object which is moving by a predetermined amount or more is present based on evaluation results of the movement amounts,” Russo teaches, (Page 14, Column 11, Lines 58-65) “With reference to FIG. 7, a flowchart illustrating an embodiment is illustrated. The process 700 begins at a certain time , for example as part of the door 430 closing sequence (step 710). Image capture device 108 then captures and analyzes the scene (step 720) . A determination is then made if objects of interest, such as people and passengers 440, are detected (step 730). If no people are detected the door 430 can close as normal (step 760),” and that, (Page 14, Column 12, Lines 23-25) “The next determination is as to what is the likelihood that the object of interest may impede closing of the automatic door and thereby possibly cause an injury (step 750),” wherein, (Page 14, Column 12, Lines 29-32) “Such other factors may include comparing the movement vectors 510, 520 to similar past movement vectors, or obtaining a predicted path of motion from a neural network,” and further that, (Page 12, Column 12, Lines 33-37) “The determined likelihood is then compared to a threshold value … If the likelihood is equal to or greater than the threshold value, then door 430 is maintained in an open position (step 770).” “and execute a closing operation of the door at a preset predetermined timing when it is determined that a moving object which is moving by a predetermined amount or more is not present and a moving object which will reach the opening before the predetermined timing is not present based on the evaluation results of the movement amounts.” Russo teaches, (Page 13, Column 10, Lines 51-67) “With reference to passenger 440 a , in a first time segment , video analytics module 224 determines 440 a moves along the path shown by vector 510 a . The first time segment may be as little as the time needed to record the next frame of video, or may represent a number of frames over a certain time period, for example one second. In the second time segment , as determined by video analytics module 224, passenger 440 a moves along the path shown by vector 520 a . While this still leaves passenger 440 a outside of area of interest 450 a at the end of the second time segment, the system uses vectors 510 a and 520 a to project the anticipated path of movement along vector 540 a . This anticipated path of movement may be represented by a vector anticipating the location of passenger 440 a at the end of the next time segment, or the projected path of movement may be calculated for the remaining length of time until the doors 430 begin closing or doors 430 close .” Russo additionally teaches, (Page 14, Column 12, Lines 33-35) “The determined likelihood is then compared to a threshold value. If the likelihood is less than the threshold value, then the door 430 can close normally (step 760).” Claim 2 Discloses: (Currently Amended) “The door controller according to claim 1, wherein the processor: restricts a closing operation of the door when it is determined that a moving object which will reach the opening before the predetermined timing is present based on the evaluation of the movement amounts.” Russo teaches, (Page 14, Column 12, Lines 23-25) “The next determination is as to what is the likelihood that the object of interest may impede closing of the automatic door and thereby possibly cause an injury (step 750),” wherein, (Page 14, Column 12, Lines 29-32) “Such other factors may include comparing the movement vectors 510, 520 to similar past movement vectors, or obtaining a predicted path of motion from a neural network,” and further that, (Page 14, Column 12, Lines 33-35) “The determined likelihood is then compared to a threshold value. If the likelihood is less than the threshold value, then the door 430 can close normally (step 760).” Claim 6 Discloses: (Currently Amended) “A non-transitory storage medium installed on a computer provided in a door controller for executing opening/closing control of a door provided in an opening based on image data in which there is captured a predetermined imaging range of an external area relative to the opening, Russo teaches, (Page 9, Column 1, Lines 66-67) “a safety detection camera system for door closure and associated method,” wherein, (Page, 9, Column 2, Lines 55-62) “computer program instructions may be provided to a processor … such that the instructions … create means for implementing the functions/acts specified in the flowchart and/or block diagram block or blocks,” wherein, (Page 13, Column 10, Lines 41-45) “An area of interest 450 may be defined relative to each door 430. The area of interest 450 may be an area in front of respective door 430 or may be a line, for example a line in front of or running across the threshold of door 430.” Russo additionally teaches, (Pag 15, Column 13 Lines 57-67, and Column 14, Lines 1-2) “an embodiment can be implemented as a computer-readable storage medium having computer readable code stored thereon for programming a computer (e.g., comprising a processor) to perform a method as described and claimed herein. Any suitable computer-usable or computer readable medium may be utilized. Examples of such computer-readable storage mediums include, but are not limited to, a hard disk , a CD-ROM, an optical storage device, a magnetic storage device, a ROM (Read Only Memory), a PROM (Programmable Read Only Memory), an EPROM (Erasable Programmable Read Only Memory), an EEPROM (Electrically Erasable Programmable Read Only Memory) and a Flash memory.” “wherein the non-transitory storage medium causes the computer to execute the following processing based on an installed computer program: analyze the image data according to time series, extract one or more moving objects which are moving toward the opening from within a predetermined area included in the imaging range, evaluate movement amounts of the moving objects toward the opening, restrict a closing operation of the door when it is determined that a moving object which is moving by a predetermined amount or more is present based on evaluation results of the movement amounts,” Russo teaches, (Page 14, Column 11, Lines 58-65) “With reference to FIG. 7, a flowchart illustrating an embodiment is illustrated. The process 700 begins at a certain time , for example as part of the door 430 closing sequence (step 710). Image capture device 108 then captures and analyzes the scene (step 720) . A determination is then made if objects of interest, such as people and passengers 440, are detected (step 730). If no people are detected the door 430 can close as normal (step 760),” and that, (Page 14, Column 12, Lines 23-25) “The next determination is as to what is the likelihood that the object of interest may impede closing of the automatic door and thereby possibly cause an injury (step 750),” wherein, (Page 14, Column 12, Lines 29-32) “Such other factors may include comparing the movement vectors 510, 520 to similar past movement vectors, or obtaining a predicted path of motion from a neural network,” and further that, (Page 12, Column 12, Lines 33-37) “The determined likelihood is then compared to a threshold value … If the likelihood is equal to or greater than the threshold value, then door 430 is maintained in an open position (step 770).” “and execute a closing operation of the door at a preset predetermined timing when it is determined that a moving object which is moving by a predetermined amount or more is not present and a moving object which will reach the opening before the predetermined timing is not present based on the evaluation results of the movement amounts.” Russo teaches, (Page 13, Column 10, Lines 51-67) “With reference to passenger 440 a , in a first time segment , video analytics module 224 determines 440 a moves along the path shown by vector 510 a . The first time segment may be as little as the time needed to record the next frame of video, or may represent a number of frames over a certain time period, for example one second. In the second time segment , as determined by video analytics module 224, passenger 440 a moves along the path shown by vector 520 a . While this still leaves passenger 440 a outside of area of interest 450 a at the end of the second time segment, the system uses vectors 510 a and 520 a to project the anticipated path of movement along vector 540 a . This anticipated path of movement may be represented by a vector anticipating the location of passenger 440 a at the end of the next time segment, or the projected path of movement may be calculated for the remaining length of time until the doors 430 begin closing or doors 430 close .” Russo additionally teaches, (Page 14, Column 12, Lines 33-35) “The determined likelihood is then compared to a threshold value. If the likelihood is less than the threshold value, then the door 430 can close normally (step 760).” Claim Rejections - 35 USC § 103 07-06 AIA 15-10-15 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. 07-20-aia AIA 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. 07-23-aia AIA 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. 07-21-aia AIA Claim s 3-5 are rejected under 35 U.S.C. 103 as being unpatentable over Russo in view of Kamijo. (JP2012084056A, hereinafter Kamijo) Claim 3 Discloses: (Currently Amended) Russo does not teach the totality of limitations with regards to claim 3. However Russo does comprise the following teachings with regards to the following limitations. “converts the movement vector in the direction toward the door … and determines whether the moving object will arrive before the predetermined timing based on a second comparison result between the movement amount evaluation parameter and a second threshold.” Russo teaches, (Abstract, Lines 3-6) “determining that the object of interest is moving towards an automatic door that is configured to close within a predetermined time period … when the likelihood exceeds a threshold value , maintaining the automatic door in an open position,” wherein the, (Page 14, Column 12, Lines 26-29) “ likelihood may be based on factors such as vector 540 predicting the movement of the target of interest as well as other factors, such as entry of the passenger into the area of interest 450.” “The door controller according to claim 1 or 2 , wherein the processor: divides the predetermined area included in the image data into image components of a plurality of blocks, calculates a movement vector of the image components that move in the time series in the block, converts the movement vector in the direction … into scalar components,” Russo does not teach the preceding limitations; however, Kamijo does teach the preceding limitations. Kamijo teaches, (Paragraph [0005], Lines 2-3) “object detection device that can accurately detect objects captured in time-series images taken from a moving vehicle,” wherein, (Paragraph [0006], Lines 2-5) “a motion vector calculation unit that calculates a motion vector for at least one of the horizontal and vertical directional components for each block into which the image is divided in the horizontal and vertical directions.” “recognizes an aggregate of adjacent blocks the scalar components of which are equal to or greater than a threshold as a moving object,” Kamijo teaches, (Paragraph [0006], Lines 17-21) “The unit determines for each block whether the motion amount difference is equal to or greater than a first threshold , and if the motion amount difference is equal to or greater than the first threshold, the sum of the pixel values of the pixels constituting the block and the direction of the directional component for which the amount of motion was calculated,” wherein, (Paragraph [0053], Line 1) “Figure 7 shows an example of adjacent correlation along the spatial axis,” and further wherein, “Figure 8 shows an example of motion vector correlation along the spatial axis.” PNG media_image1.png 430 311 media_image1.png Greyscale Kamijo additionally teaches, (Paragraph [0027], Lines 1-6) “The motion difference calculation unit 124 calculates the motion difference for each block , which is the absolute value of the difference between the amount of motion M and the regression line L. Furthermore, the pixel value difference calculation unit 125 determines for each block whether the motion difference calculated by the motion difference calculation unit 124 is equal to or greater than a predetermined first threshold .” “calculates corrected scalar components in which the scalar components are corrected in accordance with a relationship between a position of the block included in the aggregate and a lower limit position of the aggregate,” Kamijo teaches, (Paragraph [0006], Lines 24-27) “A movement amount correction unit determines whether the pixel value difference is less than or equal to a second threshold, and if so, corrects the amount of movement of the block to the amount of movement represented by the regression line .” Kamijo additionally teaches, (Paragraph [0082]) “the region search unit 170 determines, based on HOG features, that a region in which a person (pedestrian) has been imaged is an area where the person's feet were imaged. In this region, the region search unit 170 estimates the coordinates (vertical lower limit coordinates) indicating the position where the person's feet were imaged and outputs the estimated coordinates to the region correction unit 150 .” “calculates a movement amount evaluation parameter of the moving object by averaging the corrected scalar components included in the aggregate, determines whether a moving object moving by a predetermined amount or more is present based on a first comparison result between the movement amount evaluation parameter and a first threshold,” Applicant’s disclose teaches a non-limiting embodiment wherein, (Specification, Paragraph [0019], Lines 5-6) “The control unit 11 averages the movement trajectories of the coordinates of all pixels to calculate the movement vector Cmn in each block Qmn.” Therefore, Kamijo teaches, (Paragraph [0009]) “the present invention is an object detection device characterized in that the region division unit optimizes the motion vectors so that the similarity between adjacent blocks of motion vectors is high , outputs the optimized motion vectors to the motion vector calculation unit, and the motion vector calculation unit calculates motion vectors using a block matching method based on the motion vectors optimized by the region division unit,” wherein, (Paragraph [0006], Lines 17-21) “The unit determines for each block whether the motion amount difference is equal to or greater than a first threshold, and if the motion amount difference is equal to or greater than the first threshold, the sum of the pixel values of the pixels constituting the block and the direction of the directional component for which the amount of motion was calculated .” Kamijo additionally teaches, (Paragraph [0006], Lines 24-27) “A movement amount correction unit determines whether the pixel value difference is less than or equal to a second threshold, and if so, corrects the amount of movement of the block to the amount of movement represented by the regression line.” Therefore, it would have been obvious to a person of ordinary skill in the art before the effective filling date of the claimed invention to combine safety detection camera system for door closure which is capable of interpreting movement vectors associated with approaching objects, with the methodology of aggregating adjacent blocks, the scalar components of which are associated with a moving object upon comparison to a threshold as taught by Kamijo, in order to yield predictable results. Combining the references would yield the accuracy benefits of detecting/predicting the motion of an object. As Kamijo describes, (Paragraph [0087]) “the object detection device can detect objects captured in time-series images taken from moving vehicles, etc., based on motion values optimized by a regression line, thus enabling accurate detection of captured objects.” Claim 4 Discloses: (Currently Amended) “The door controller according to claim 3 or 4 , wherein the processor: stops a closing operation of the door and executes an opening operation when it is determined that a moving object which is moving by a predetermined amount or more is present based on the first comparison result.” Russo teaches, (Page 14, Column 12, Lines 29-32) “Such other factors may include comparing the movement vectors 510, 520 to similar past movement vectors, or obtaining a predicted path of motion from a neural network,” and further that, (Page 12, Column 12, Lines 33-37) “The determined likelihood is then compared to a threshold value … If the likelihood is equal to or greater than the threshold value, then door 430 is maintained in an open position (step 770).” Claim 5 Discloses: (Currently Amended) “The door controller according to claim 3 or 4 , wherein the processor: stops a closing operation of the door when it is determined that the moving object will arrive before the predetermined timing based on the second comparison result.” Russo teaches, (Abstract, Lines 3-6) “determining that the object of interest is moving towards an automatic door that is configured to close within a predetermined time period … when the likelihood exceeds a threshold value , maintaining the automatic door in an open position,” wherein the, (Page 14, Column 12, Lines 26-29) “ likelihood may be based on factors such as vector 540 predicting the movement of the target of interest as well as other factors, such as entry of the passenger into the area of interest 450.” RELEVANT, BUT NOT CITED PRIOR ART 07-96 AIA The prior art made of record and not relied upon is considered pertinent to applicant’s disclosure. Murakami et al. (US 2022/0281485 A1) discloses, (Paragraph [0094], Lines 1-12) “ In step s1022, the controller 21 of the control apparatus 20 determines whether the probability calculated in step S1021 is lower than a first threshold value. In step S1023, the controller 21 of the control apparatus 20 determines whether the probability calculated in step S1021 is equal to or higher than a second threshold value, which is lower than the first threshold value. For example, the first threshold value is 70% and the second threshold value is 30%. When the probability is 70%, it is considered certain that the user U1 will board the vehicle. On the other hand, when the probability is lower than 30%, it is considered certain that the user U1 will not board the vehicle.” Kang et al. (US 2024/0200387 A1) discloses, (Abstract) “an autonomous vehicle control apparatus including a sensor that obtains sensing information associated with an entity around a vehicle, a camera that obtains an image of the entity, and one or more processor that determine whether the entity is estimated to reach the vehicle at least a predetermined time after a door of the vehicle opens, and control a position of the door.” Conclusion Any inquiry concerning this communication or earlier communications from the examiner should be directed to ALEXANDER V. GENTILE whose telephone number is (703)756-1501. The examiner can normally be reached Monday - Friday 9-5. 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, Kito R. Robinson can be reached at (571)270-3921. 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. /ALEXANDER V GENTILE/Examiner, Art Unit 3664 /KITO R ROBINSON/Supervisory Patent Examiner, Art Unit 3664 Application/Control Number: 19/232,869 Page 2 Art Unit: 3664 Application/Control Number: 19/232,869 Page 3 Art Unit: 3664 Application/Control Number: 19/232,869 Page 4 Art Unit: 3664 Application/Control Number: 19/232,869 Page 5 Art Unit: 3664 Application/Control Number: 19/232,869 Page 6 Art Unit: 3664 Application/Control Number: 19/232,869 Page 7 Art Unit: 3664 Application/Control Number: 19/232,869 Page 9 Art Unit: 3664 Application/Control Number: 19/232,869 Page 10 Art Unit: 3664 Application/Control Number: 19/232,869 Page 11 Art Unit: 3664 Application/Control Number: 19/232,869 Page 12 Art Unit: 3664 Application/Control Number: 19/232,869 Page 13 Art Unit: 3664 Application/Control Number: 19/232,869 Page 14 Art Unit: 3664 Application/Control Number: 19/232,869 Page 15 Art Unit: 3664 Application/Control Number: 19/232,869 Page 16 Art Unit: 3664 Application/Control Number: 19/232,869 Page 17 Art Unit: 3664 Application/Control Number: 19/232,869 Page 18 Art Unit: 3664 Application/Control Number: 19/232,869 Page 19 Art Unit: 3664 Application/Control Number: 19/232,869 Page 20 Art Unit: 3664 Application/Control Number: 19/232,869 Page 21 Art Unit: 3664
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