CTNF 18/945,594 CTNF 84771 DETAILED ACTION Notice of Pre-AIA or AIA Status 07-03-aia AIA 15-10-aia 1. The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA. 2. Claims 1-12 are pending in this application. Priority 3. Acknowledgement is made of applicant’s claim for foreign priority based on application JP 2023-202487 filed on 11/30/2023 under 35 U.S.C 119(a)-(d). Drawings 4. The drawing has been filed on 11/13/2024 are acceptable for examination purpose. Information Disclosure Statement 5. The information disclosure statement filed on 11/13/2024 is in compliance with the provision of the 37 CFR 1.97 and therefore has been considered. Claim Rejections - 35 USC § 101 07-04-01 AIA 07-04 6. 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. 7. The claimed invention is directed to a judicial exception (i.e., a law of nature, a natural phenomenon, or an abstract idea) without significantly more. Claims 1-12 are directed to a judicial exception (i.e., a law of nature, a natural phenomenon, or an abstract idea) without significantly more. Claims 1, 10-11 are rejected under 35 U.S.C. 101, because the claimed invention directed to abstract idea without significantly more. The claim recites “ an electrical component to generate a signal; and circuitry configured to determine, based on an operating status of the electronic apparatus, a type of noise indicating that the noise included in the signal is a normal noise not caused by an abnormality of the electronic apparatus or an abnormal noise caused by the abnormality of the electronic apparatus ”. The claim limitation of “ circuitry configured to determine, based on an operating status of the electronic apparatus, a type of noise indicating that the noise included in the signal is a normal noise not caused by an abnormality of the electronic apparatus or an abnormal noise caused by the abnormality of the electronic apparatus ”, as drafted, is a process that, under its broadest reasonable interpretation, covers performance of the limitation in the mind but for the recitation of generic computer component. That is, other than reciting “by a circuitry” nothing in the claim element precludes the step from practically being performed in the mind. For example, but for the “by a circuitry” language, “determine” in the context of this claim encompasses the user manually determine a type of noise whether the noise is normal or abnormal that is received from the electronic apparatus. Similarly, the limitations of “indicating” to identify an operating state of the electronic apparatus using machine learning model to find the type of noise as drafted, is a process that, under its broadest reasonable interpretation, covers performance of the limitation in the mind but for the recitation of generic computer component. For example, but for the “by a circuitry” language, “determine & indicating” in the context of this claim encompasses the user thinking that the computer or printer or electronic apparatus in connection with circuitry should be determining the type of noise using the machine learning. If a claim limitations, under its broadest reasonable interpretation, covers performance of the limitation in the mind but for the recitation of generic computer components, then it falls within the “Mental Processes” grouping of abstract ideas. Accordingly, the claim recites an abstract idea. This judicial exception is not integrated into a practical application. In particular, the claim doesn’t recite any additional element – using a circuitry to perform determine & indicating steps. The circuitry in last steps is recited at a high-level of generality ( i.e. , as a generic control unit performing a generic computer function of ranking information based on a determined amount of use) such that it amounts no more than mere instructions to apply the exception using a generic computer component. Accordingly, the claimed steps do not integrate the abstract idea into a practical application because it does not impose any meaningful limits on practicing the abstract idea. The claim is directed to an abstract idea. The claim does not include any additional elements that are sufficient to amount to significantly more than the judicial exception. As discussed above with respect to integration of the abstract idea into a practical application, the claimed steps of using a circuitry to perform determine & indicating steps amounts to no more than mere instructions to apply the exception using a generic computer component. Mere instructions to apply an exception using a generic computer component cannot provide an inventive concept. The claim is not patent eligible. Claim Rejections - 35 USC § 102 07-07-aia AIA 07-07 8. 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 9. Claim s 1, 11-12 are rejected under 35 U.S.C. 102( a)(1 ) as being anticipated by Nishimura, US Pub 2007/0070456 . As to claim 1[independent], Nishimura teaches an electronic apparatus comprising [ fig. 1, element 10; 0023-0024 ]: an electrical component to generate a signal [ figs. 6-8; abstract, 009-0010, 0041-0049 Nishimura teaches that the printer 10 has at least acquired or received a sound/noise signal, when the printer 10 is in printing process state ]; and circuitry configured to determine, based on an operating status of the electronic apparatus, a type of noise indicating that the noise included in the signal is a normal noise not caused by an abnormality of the electronic apparatus [ figs. 6-8; abstract, 009-0010, 0041-0049 Nishimura teaches that the printer 10 acquired or received a sound/noise signal, when the printer 10 is in printing process state, as a normal sound/noise information 301 that is not caused by an abnormality of the printer 10 ] or an abnormal noise caused by the abnormality of the electronic apparatus [ figs. 6-8; abstract, 009-0010, 0041-0049 Nishimura teaches that the printer 10 acquired or received a sound/noise signal when the printer 10 is in printing process state and determines/checks whether the sound information is abnormal, and when the difference between detected sound information 300 and normal sound information 301 is more than or equal to a predetermined value, processor (CPU) 200 of the printer 10 determines that a fault has occurred, and calculates abnormal sound times T1 and T2 on the basis of time information T ]. As to claim 11 [independent], However, the independent claim 11 essentially claimed same subject matter as claimed in the independent claim 1 for/and/with other claim limitations, and are therefore the independent claim 11 would be rejected based on same rationale as applied to the independent claim 1. As to claim 12 [dependent from claim 11], Nishimura teaches a non-transitory recording medium storing a plurality of instructions which, when executed by one or more processors, causes the one or more processors to perform the noise determination method of claim 11 [ fig. 2, element 201 or 202; 0024 Nishimura teaches that memory 201 or 202 of the printer 10’s stores a control program that implement to determine the state of the printer 10 ] . Claim Rejections - 35 USC § 103 07-20-aia AIA 10. 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. 07-21-aia AIA 11. Claim s 2-9 are rejected under 35 U.S.C. 103 as being unpatentable over in view of Nishimura, US Pub 2007/0070456 in view of Lee et al. [hereafter Lee], US Pub 2019/0178755 . As to claim 2 [dependent from claim 1], Nishimura teaches wherein the circuitry determines the type of noise by inferring the type of noise in the signal based on the signal and data indicating the operating status of the electronic apparatus, using a pre-trained machine learning model [ figs. 6-8; abstract, 009-0010, 0041-0049 Nishimura teaches that the printer 10 acquired or received a sound/noise signal when the printer 10 is in printing process state and determines/checks whether the sound information is abnormal, and when the difference between detected sound information 300 and normal sound information 301 is more than or equal to a predetermined value, processor (CPU) 200 of the printer 10 determines that a fault has occurred, and further calculates abnormal sound times T1 and T2 on the basis of time information T ], Nishimura doesn’t teach the pre-trained machine learning model being configured to input the signal and the data indicating the operating status of the electronic apparatus as input data and output the type of noise as output data. Lee teaches the pre-trained machine learning model being configured to input the signal and the data indicating the operating status of the electronic apparatus as input data and output the type of noise as output data [ 0010, 0020, 0063-0069 ]. Thus, it would have been obvious to one of the ordinary skill in the art before the effective filing date of the claimed invention to incorporate Lee teaching to determine states of the electronic apparatus based on the noise information using machine learning model to modify Nishimura’s teaching to collect at least one of acceleration data and sound data due to a movement of a 3D printer component during a 3D printing process as collection data for determining a normal state and an abnormal state of the 3D printer component by using at least one of the acceleration data and the sound data. The suggestion/motivation for doing so would have been benefitted to the user to conveniently find the failure of major components of a 3D printer, accurately diagnosed and predicted based on a health diagnosis result of the 3D printer. As to claim 3 [dependent from claim 2], Nishimura teaches wherein the operating status is one of a warm-up state, a standby state [ 0040-0049 Nishimura teaches that the printer 10’s operating states is standby or warmup or working printing state ], and an energy-saving state of the electronic apparatus. As to claim 4 [dependent from claim 2], Nishimura teaches wherein the one of the warm-up state, the standby state [ 0040-0049 Nishimura teaches that the printer 10’s operating states is standby or warmup or working printing state which further indicating the normal or abnormal operating state ], and the energy-saving state includes a plurality of different states. As to claim 5 [dependent from claim 3], Nishimura teaches wherein the electronic apparatus is an image forming apparatus, and the operating status further includes a printing state [ 0040-0049 Nishimura teaches that the printer 10’s operating states is standby or warmup or working printing state ]. As to claim 6 [dependent from claim 5], Nishimura teaches wherein the printing state includes a plurality of different states [ 0040-0049 Nishimura teaches that the printer 10’s operating states is standby or warmup or working printing state which further indicating the normal or abnormal operating state ]. As to claim 7 [dependent from claim 2], Nishimura teaches wherein the input data include ON timing data indicating when the electronic apparatus is turned on and circuit data indicating impedance of a circuit of the electrical component within the electronic apparatus [ figs. 6-8; abstract, 009-0010, 0040-0049 Nishimura teaches that the printer 10’s operating states is standby or warmup or working printing state, and determines/checks whether the sound information is abnormal, and when the difference between detected sound information 300 and normal sound information 301 is more than or equal to a predetermined value, processor (CPU) 200 of the printer 10 determines that a fault has occurred, and further calculates abnormal sound times T1 and T2 on the basis of time information T ], and wherein the circuitry infers the type of noise based on the ON timing data or the circuit data [ figs. 6-8; abstract, 009-0010, 0040-0049 Nishimura teaches that the printer 10’s operating states is standby or warmup or working printing state, and determines/checks whether the sound information is abnormal, and when the difference between detected sound information 300 and normal sound information 301 is more than or equal to a predetermined value, the processor (CPU) 200 of the printer 10 determines that a fault has occurred, and further calculates abnormal sound times T1 and T2 on the basis of time information T ]. As to claim 8 [dependent from claim 7], Nishimura teaches wherein the electronic apparatus is an image forming apparatus, and the input data includes passing-sheet position data indicating passing-sheet position within the image forming apparatus during printing [ figs. 6-8; abstract, 009-0010, 0040-0049 Nishimura teaches that a plurality of sheets formed by the printer 10. However, when the sensor 50 detects the leading edge of the sheet, the solenoid 40b is turned off, and the feeding rollers 40 come into contact with each other so as to nip the sheet. When the sensor 50 detects the trailing edge of the sheet after the leading edge reaches the discharging rollers 38, the solenoid 40b is turned on to separate the feeding rollers 40, and the sound or noise information about the printer 10 is detected during feeding of the sheet. The processor (CPU) 200 determines/checks whether the sound information is abnormal, and when the difference between detected sound information 300 and normal sound information 301 is more than or equal to a predetermined value, the processor (CPU) 200 determines that a fault has occurred, and further calculates abnormal sound times T1 and T2 on the basis of time information T ], and wherein the circuitry infers the type of noise based on the passing-sheet position data [ figs. 6-8; abstract, 009-0010, 0040-0049 Nishimura teaches that the processor (CPU) 200 determines/checks whether the sound information is abnormal, and when the difference between detected sound information 300 and normal sound information 301 is more than or equal to a predetermined value, the processor (CPU) 200 determines that a fault has occurred, and further calculates abnormal sound times T1 and T2 on the basis of time information T ]. As to claim 9 [dependent from claim 1], Nishimura teaches wherein the circuitry is further configured to count the number of times the noise is determined to be the abnormal noise [ figs. 6-8; abstract, 009-0010, 0040-0049 Nishimura teaches that the processor (CPU) 200 determines/checks whether the sound information is abnormal, and when the difference between detected sound information 300 and normal sound information 301 is more than or equal to a predetermined value, the processor (CPU) 200 determines that a fault has occurred, and further calculates abnormal sound times T1 and T2 on the basis of time information T ], and determine that the abnormality has occurred in the electronic apparatus when the number of times the noise is determined to be the abnormal noise for a predetermined period of time exceeds a threshold value [ figs. 6-8; abstract, 009-0010, 0040-0049 Nishimura teaches that the processor (CPU) 200 determines/checks whether the sound information is abnormal, and when the difference between detected sound information 300 and normal sound information 301 is more than or equal to a predetermined value, the processor (CPU) 200 determines that a fault has occurred, and further calculates abnormal sound times T1 and T2 on the basis of time information T ]. Allowable Subject Matter 12. Claim 10 would be allowable if rewritten or amended to overcome the rejection(s) under 35 U.S.C. 101 (abstract idea), set forth in this Office action. 13. The following is an examiner’s statement of reasons for allowance : The independent claim 10 is allowable over the prior arts of record since the cited references taken individually or in combination fails to particularly anticipate or disclose or suggest the claim limitations recited “ circuitry configured to determine a type of noise indicating that the noise included in the signal is a normal noise not caused by an abnormality of the electronic apparatus or an abnormal noise caused by the abnormality of the electronic apparatus, by inferring the type of noise in the signal based on the signal and data indicating an operating status of the electronic apparatus using a pre-trained machine learning model, the pre-trained machine learning model being configured to input the signal and the data indicating the operating status of the electronic apparatus as input data and output the type of noise as output data ”, in combination with all other limitations as claimed in independent claim 10. Conclusion 14. Any inquiry concerning this communication or earlier communications from the examiner should be directed to HARIS SABAH whose telephone number is (571)270-3917. The examiner can normally be reached on Monday/Friday from 9:00AM to 5:30PM EST. If attempts to reach the examiner by telephone are unsuccessful, the examiner's supervisor, Benny Tieu, can be reached on (571)272-7490. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300. The Examiner’s personal fax number is (571)270-4917. Information regarding the status of an application may be obtained from the Patent Application Information Retrieval (PAIR) system. Status information for published applications may be obtained from either Private PAIR or Public PAIR. Status information for unpublished applications is available through Private PAIR only. For more information about the PAIR system, see http://portal.uspto.gov/external/portal. Should you have questions on access to the Private PAIR system, contact the Electronic Business Center (EBC) at 866-217-9197 (toll-free). /HARIS SABAH/Examiner, Art Unit 2682 Application/Control Number: 18/945,594 Page 2 Art Unit: 2682 Application/Control Number: 18/945,594 Page 3 Art Unit: 2682 Application/Control Number: 18/945,594 Page 4 Art Unit: 2682
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