DETAILED ACTION
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 § 101
2. 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.
Claims 1-20 are rejected under 35 U.S.C. 101 because 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.
In view of the new 2019 Revised Patent Subject Matter Eligibility Guidance (Federal Register Vol. 84, No. 4, January 7, 2019), the Examiner has considered the claims and has determined that under step 1, claims 1-14 are to a process and claims 15-20 are to a machine.
Next under the new step 2A prong 1 analysis, the claims are considered to determine if they recite an abstract idea (judicial exception) under the following groupings: (a) mathematical concepts, (b) certain methods of organizing human activity, or (c) mental processes. The independent claims contain at least the following bolded limitations (see representative independent claims) that fall into the grouping of mathematical concepts and/or mental processes:
1. An inspecting method of a display panel, the method comprising:
training an artificial intelligence model based on age data of a test display panel for an aging characteristic; generating virtual age data of a virtual display panel from the aging characteristic using the artificial intelligence model; and
predicting an age of the display panel based on the virtual age data.
15. An inspecting device comprising:
a memory which stores an artificial intelligence model; and
a processor which predicts an age of a display panel by the artificial intelligence model stored in the memory; wherein the processor generates virtual age data of a virtual display panel from an aging characteristic by the artificial intelligence model and predicts the age of the display panel based on the virtual age data, and
the artificial intelligence model is trained based on age data of a test display panel for the aging characteristic.
It is important to note that a mathematical concept need not be expressed in mathematical symbols, because "[w]ords used in a claim operating on data to solve a problem can serve the same purpose as a formula."(see MPEP 2106.04(a)(2) I.). The limitations of “training an artificial intelligence model based on age data of a test display panel for an aging characteristic” or “an artificial intelligence model is trained based on age data of a test display panel for the aging characteristic,” when given their broadest reasonable interpretation in light of the background, amount to carrying out mathematical calculations to derive a trained artificial intelligence model as mathematically-based construct. Figure 10 and paragraph [0122] in the specification as originally filed describe the artificial intelligence model as one of many potential mathematical models (e.g., random forest regression model, extra tree regression model, gradient boosting regression model), which supports the plain meaning of the claim limitation terms as mathematical-based calculations to generate a trained artificial intelligence model (see similar Example 47 claim 2 from the July 2024 Subject Matter Eligibility Examples from the 2024 Guidance Update on Patent Subject Matter Eligibility, Including on Artificial Intelligence, 89 FR 58128). The limitations of “generating virtual age data of a virtual display panel from the aging characteristic using the artificial intelligence model” is just the mathematical action of using a function/model which takes input parameters and returns output parameters. The limitations of “predicting an age of the display panel based on the virtual age data” amounts to a mental process to form a judgment of a predicted age based on evaluating the virtual age, or a mathematical calculation to further calculate a numerical age value based on the virtual age if the derivation involves a more complex formulaic analysis.
Next in step 2A prong 2, the independent claims are analyzed to determine whether there are additional elements or combination of elements that apply, rely on, or use the judicial exception in a manner that imposes a meaningful limit on the judicial exception such that it is more than a drafting effort designed to monopolize the exception, in order to integrate the judicial exception into a practical application. These limitations have been identified and underlined above, and are not indicative of integration into a practical application because: (1) the recitations of “an inspecting device comprising a memory which stores...; and a processor” amount to mere instructions to implement an abstract idea on a computer or merely using a computer as a tool to perform an abstract idea (see MPEP 2106.05(f)).
Next in step 2B, the independent claims are considered to determine if they recite additional elements that amount to an inventive concept (“significantly more”) than the recited judicial exception. The recitations of an inspecting device comprising a memory which stores and a processor, do not add something significantly more because they amount to mere instructions to implement an abstract idea on a computer or merely using a computer as a tool to perform an abstract idea (see MPEP 2106.05(f)). The use of generic computer equipment is considered insignificant additional elements. As recited in the MPEP, 2106.07(b), merely adding a generic computer, generic computer components, or a programmed computer to perform generic computer functions does not automatically overcome an eligibility rejection (see Alice Corp. Pty. Ltd. v. CLS Bank Int'l, 134 S. Ct. 2347, 2359-60, 110 USPQ2d 1976, 1984 (2014). See also OIP Techs. v. Amazon.com, 788 F.3d 1359, 1364, 115 USPQ2d 1090, 1093-94).
Dependent claims 2-4, 8, 10-14, and 16-20 contain additional limitations that fall under the abstract idea grouping of mathematical concepts to describe variable definitions and mathematical models used in the calculations. Dependent claims 5-7 and 9 describe measuring the necessary data that goes into the calculations to build the mathematical model, and amount to insignificant extrasolution data which does not provide an integration into a practical application or significantly more (see MPEP 2106.05(g)).
3. An invention is not rendered ineligible for patent simply because it involves an abstract concept. Applications of such concepts "to a new and useful end" remain eligible for patent protection (see Alice Corp., 134 S. Ct. at 2354 (quoting Benson, 409 U.S. at 67)). However, "a claim for a new abstract idea is still an abstract idea" (see Synopsys v. Mentor Graphics Corp. _F.3d_, 120 U.S.P.Q. 2d1473 (Fed. Cir. 2016)). There needs to be additional elements or combination of additional elements in the claim to apply, rely on, or use the judicial exception in a manner that imposes a meaningful limit on the judicial exception or render the claim as a whole to be significantly more than the exception itself in order to demonstrate “integration into a practical application” or an “inventive concept.” For instance, particular physical arrangements for actively obtaining the sensor data, or further physical applications (beyond extrasolution data output displaying) using the calculated informational age of the display panel to drive a transformation, change in physical operation, or repair/maintenance of a technology or technical process could provide integration into a practical application to demonstrate an improvement to the technology or technical field.
Claim Rejections - 35 USC § 112
4. 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.
Claims 1-20 are 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.
a) Claim 1 on pg. 1 lines 9-10 recites “predicting an age of the display panel based on the virtual age data.” It is not clear whether “the display panel” is referring to the “test display panel” or “the virtual display panel,” as there are two previous recitations of a “display panel.” Appropriate correction/clarification is requested.
b) Claim 15 on pg. 6 lines 15-16 recites “and predicts the age of the display panel based on the virtual age data.” It is not clear whether “the display panel” is necessarily referring to “a display panel by the artificial intelligence model” or “a virtual display panel,” as there are two previous recitations of a “display panel.” Appropriate correction/clarification is requested.
5. Dependent claims 2-14 depend from claim 1 and are rejected for at least the same reasons as given for claim 1. Dependent claims 16-20 depend from claim 15 and are rejected for at least the same reasons as given for claim 15.
Claim Rejections - 35 USC § 102
6. 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 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.
7. Claim(s) 1-2, 4, 8, 10, 15, and 17-19 are rejected under 35 U.S.C. 102(a)(1) as being anticipated by Lee et al. (US Pat. Pub. 2017/0069261).
In regards to claim 1, Lee teaches an inspecting method of a display panel (Lee abstract teaches an inspection method of determining an estimated lifespan curve of a display panel) , the method comprising:
training an artificial intelligence model based on age data of a test display panel for an aging characteristic (Lee paragraph [0043]-[0044] teach an an aging controller carrying out aging on a test display panel to train an initial aging profile (artificial intelligence model) based on degradation age data of the display panel for a luminance value (aging characteristic) at a certain initial aging time point);
generating virtual age data of a virtual display panel from the aging characteristic using the artificial intelligence model (Lee Fig. 4 and paragraphs [0045]-[0046] teach generating virtual age data of predicted future lifespan curve data of a virtual future-modeled display panel at a latter period of time using the initial aging profile); and
predicting an age of the display panel based on the virtual age data (Lee abstract, paragraph [0005], paragraph [0040], and paragraph [0044] teach estimating a curve of lifetime (age) values of the display panel based on the virtual age data that models luminance reduction at a latter point in time).
In regards to claim 2, Lee teaches the inspecting method of the display panel wherein the age data of the test display panel is a luminance retention rate according to an aging time of the test display panel (Lee paragraphs [005] and [0044] teach where the age data follows a luminance reduction ratio (luminance ratio rate) according to an aging time of the test display panel).
In regards to claim 4, Lee teaches the inspecting method of the display panel wherein the aging characteristic includes at least one of an aging color, an aging grayscale, an initial aging luminance, an observation color, an observation grayscale, an initial observation luminance, an aging position, and a temperature (Lee paragraph [044] teaches where the aging characteristic includes at least one of an initial aging luminance (at a certain initial aging time point)).
In regards to claim 8, Lee teaches the inspecting method of the display panel wherein the aging characteristic includes at least one of an aging color, an aging grayscale, an initial aging luminance, an observation color, an observation grayscale, an initial observation luminance, an aging position, a temperature, an aging current, an observation current, and a light efficiency (Lee paragraph [044] teaches where the aging characteristic includes at least one of an initial aging luminance (at a certain initial aging time point)).
In regards to claim 10, Lee teaches the inspecting method of the display panel wherein the artificial intelligence model is a regression model (Lee paragraph [0045] and Eq. 1 teaches where the initial aging profile is expressed as an exponential regression model).
In regards to claim 15, Lee teaches an inspecting device (Lee abstract and paragraph [0065] teaches a computer as an inspecting device for carrying out an an inspection method of determining an estimated lifespan curve of a display panel) comprising:
a memory which stores an artificial intelligence model (Lee paragraph [0067] teaches a memory which stores the algorithms (including an artificial intelligence model, and Lee paragraphs [0043]-[0044] teach the use of an initial aging profile (artificial intelligence model) which is recorded and referred to for modeling a lifespan curve); and
a processor which predicts an age of a display panel by the artificial intelligence model stored in the memory (Lee abstract and paragraph [0065]-[0067] teach a processor or aging controller for carrying out the processing features of predicting a lifespan of a display panel using the initial aging profile (artificial intelligence model) stored in memory (see paragraph [0044])) ;
wherein the processor generates virtual age data of a virtual display panel from an aging characteristic by the artificial intelligence model (Lee Fig. 4 and paragraphs [0045]-[0046] teach the controller generating virtual age data of predicted future lifespan curve data of a virtual future-modeled display panel at a latter period of time using a luminance (aging characteristic) of the initial aging profile) and predicts the age of the display panel based on the virtual age data (Lee abstract, paragraph [0005], paragraph [0040], and paragraph [0044] teach estimating a curve of lifetime (age) values of the display panel based on the virtual age data that models luminance reduction at a latter point in time), and
the artificial intelligence model is trained based on age data of a test display panel for the aging characteristic (Lee paragraph [0043]-[0044] teach an an aging controller carrying out aging on a test display panel to train the initial aging profile (artificial intelligence model) based on degradation age data of the display panel for the luminance value (aging characteristic) at a certain initial aging time point).
In regards to claim 17, Lee teaches the inspecting device wherein the aging characteristic includes at least one of an aging color, an aging grayscale, an initial aging luminance, an observation color, an observation grayscale, an initial observation luminance, and a temperature (Lee paragraph [044] teaches where the aging characteristic includes at least one of an initial aging luminance (at a certain initial aging time point)).
In regards to claim 18, Lee teaches the inspecting device wherein the aging characteristic includes at least one of an aging color, an aging grayscale, an initial aging luminance, an observation color, an observation grayscale, an initial observation luminance, a temperature, an aging current, an observation current, and a light efficiency (Lee paragraph [044] teaches where the aging characteristic includes at least one of an initial aging luminance (at a certain initial aging time point)).
In regards to claim 19, Lee teaches the inspecting device wherein the artificial intelligence model is a regression model (Lee paragraph [0045] and Eq. 1 teaches where the initial aging profile is expressed as an exponential regression model).
Allowable Subject Matter
8. Claims 3, 5-7, 9, 11-14, 16, and 20 would be allowable if rewritten or amended to overcome the rejection(s) under 35 U.S.C. 101 and 35 U.S.C. 112(b), set forth in this Office action and to include all the limitations of the base claim and any intervening claim.
9. The following is a statement of reasons for the indication of allowable subject matter:
Claim 3 contains allowable subject matter because the closest prior art, Lee et al. (US Pat. Pub. 2017/0069261) fails to anticipate or render obvious the inspecting method of the display panel wherein the artificial intelligence model includes a first artificial intelligence model according to a first aging time and a second artificial intelligence model according to a second aging time different from the first aging time, in combination with the rest of the claim limitations as claimed and defined by the Applicant.
Claim 5 contains allowable subject matter because the closest prior art, Lee et al. (US Pat. Pub. 2017/0069261) fails to anticipate or render obvious the inspecting method of the display panel wherein the training the artificial intelligence model includes: displaying the aging color and the aging grayscale on a pattern of the test display panel; measuring the initial aging luminance of the pattern; displaying the observation color and the observation grayscale on the test display panel; measuring the initial observation luminance of the pattern; measuring the temperature of the test display panel; determining the age data of the test display panel; labeling the aging characteristic with the age data of the test display panel; and training the artificial intelligence model with the aging characteristic labeled with the age data of the test display panel, in combination with the rest of the claim limitations as claimed and defined by the Applicant.
Claim 9 contains allowable subject matter because the closest prior art, Lee et al. (US Pat. Pub. 2017/0069261) fails to anticipate or render obvious the inspecting method of the display panel wherein the training the artificial intelligence model includes: displaying the aging color and the aging grayscale on a pattern of the test display panel; measuring the initial aging luminance and the aging current of the pattern; displaying the observation color and the observation grayscale on the test display panel; measuring the initial observation luminance and the observation current of the pattern; measuring the temperature of the test display panel; determining the age data of the test display panel; labeling the aging characteristic with the age data of the test display panel; and training the artificial intelligence model with the aging characteristic labeled with the age data of the test display panel, in combination with the rest of the claim limitations as claimed and defined by the Applicant.
Claim 11 contains allowable subject matter because the closest prior art, Lee et al. (US Pat. Pub. 2017/0069261) fails to anticipate or render obvious the inspecting method of the display panel, wherein the artificial intelligence model is one of a random forest regression model, an extra tree regression model, and a gradient boosting regression model, in combination with the rest of the claim limitations as claimed and defined by the Applicant.
Claim 12 contains allowable subject matter because the closest prior art, Lee et al. (US Pat. Pub. 2017/0069261) fails to anticipate or render obvious the inspecting method of the display panel wherein the artificial intelligence model is generated by blending at least two regression models, in combination with the rest of the claim limitations as claimed and defined by the Applicant.
Claim 13 contains allowable subject matter because the closest prior art, Lee et al. (US Pat. Pub. 2017/0069261) fails to anticipate or render obvious the inspecting method of the display panel wherein the predicting the age of the display panel includes: normalizing the virtual age data and generating normal distribution data; and predicting the age of the display panel based on data corresponding to a predetermined ratio of the normal distribution data, in combination with the rest of the claim limitations claimed and defined by the Applicant.
Claim 14 contains allowable subject matter because the closest prior art, Lee et al. (US Pat. Pub. 2017/0069261) fails to anticipate or render obvious the inspecting method of the display panel wherein the predicting the age of the display panel includes: normalizing the virtual age data and the age data of the test display panel and generating normal distribution data; and predicting the age of the display panel based on data corresponding to a predetermined ratio of the normal distribution data, in combination with the rest of the claim limitations claimed and defined by the Applicant.
Claim 16 contains allowable subject matter because the closest prior art, Lee et al. (US Pat. Pub. 2017/0069261) fails to anticipate or render obvious the inspecting device, wherein the artificial intelligence model includes: a first artificial intelligence model according to a first aging time; and a second artificial intelligence model according to a second aging time different from the first aging time, in combination with the rest of the claim limitations as claimed and defined by the Applicant.
Claim 20 contains allowable subject matter because the closest prior art, Lee et al. (US Pat. Pub. 2017/0069261) fails to anticipate or render obvious the inspecting device wherein the artificial intelligence model is generated by blending at least two regression models, in combination with the rest of the claim limitations as claimed and defined by the Applicant.10. Dependent claims 6-7 depend from claim 5 and contain allowable subject matter for at least the same reasons as given for claim 5.
Pertinent Art
11. Applicants are directed to consider additional pertinent prior art included on the Notice of References Cited (PTOL 892) attached herewith. The Examiner has pointed out particular references contained in the prior art of record within the body of this action for the convenience of the Applicant. Although the specified citations are representative of the teachings in the art and are applied to the specific limitations within the individual claim, other passages and figures may apply. Applicant, in preparing the response, should consider fully the entire reference as potentially teaching all or part of the claimed invention, as well as the context of the of the passage as taught by the prior art or disclosed by the Examiner. The prior art made of record and not relied upon is considered pertinent to applicant's disclosure.
B. Tu et al. (US Pat. Pub. 2019/0013473) discloses Aging Test System for Display Panel and Aging Test Method for the Same.
C. Xu et al. (US Pat. Pub. 2020/0357336) discloses Method and System for Estimating and Compensating Aging of Light Emitting Elements in Display Panel.
D. Han et al. (US Pat. Pub. 2022/0036834) discloses Display Apparatus and Method of Compensating Image of Display Panel Using the Same.
Conclusion
12. Any inquiry concerning this communication or earlier communications from the examiner should be directed to PAUL D LEE whose telephone number is (571)270-1598. The examiner can normally be reached on M to F, 9:30 am to 6 pm.
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, Arleen Vazquez can be reached at 571-272-2619. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/PAUL D LEE/Primary Examiner, Art Unit 2857 9/14/2026
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