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 .
This communication is responsive to application filed on 12/19/2022.
Claims 13-14 have been added.
Claims 1-14 are presented for examination.
Priority
Acknowledgment is made of applicant’s claim for foreign priority under 35 U.S.C. 119 (a)-(d). The certified copy has been filed on 12/19/2022.
Information Disclosure Statement
The information disclosure statement (IDS) submitted on 12/19/2022 is in compliance with the provisions of 37 CFR 1.97. Accordingly, the information disclosure statement is being considered by the examiner.
Specification
The following guidelines illustrate the preferred layout for the specification of a utility application. These guidelines are suggested for the applicant’s use.
Arrangement of the Specification
As provided in 37 CFR 1.77(b), the specification of a utility application should include the following sections in order. Each of the lettered items should appear in upper case, without underlining or bold type, as a section heading. If no text follows the section heading, the phrase “Not Applicable” should follow the section heading:
(a) TITLE OF THE INVENTION.
(b) CROSS-REFERENCE TO RELATED APPLICATIONS.
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(d) THE NAMES OF THE PARTIES TO A JOINT RESEARCH AGREEMENT.
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(f) STATEMENT REGARDING PRIOR DISCLOSURES BY THE INVENTOR OR A JOINT INVENTOR.
(g) BACKGROUND OF THE INVENTION.
(1) Field of the Invention.
(2) Description of Related Art including information disclosed under 37 CFR 1.97 and 1.98.
(h) BRIEF SUMMARY OF THE INVENTION.
(i) BRIEF DESCRIPTION OF THE SEVERAL VIEWS OF THE DRAWING(S).
(j) DETAILED DESCRIPTION OF THE INVENTION.
(k) CLAIM OR CLAIMS (commencing on a separate sheet).
(l) ABSTRACT OF THE DISCLOSURE (commencing on a separate sheet).
(m) SEQUENCE LISTING. (See MPEP § 2422.03 and 37 CFR 1.821 - 1.825). A “Sequence Listing” is required on paper if the application discloses a nucleotide or amino acid sequence as defined in 37 CFR 1.821(a) and if the required “Sequence Listing” is not submitted as an electronic document either on read-only optical disc or as a text file via the patent electronic system.
Claim Objections
Claim 1 is objected to because of the following informalities: The variables (N, Af, Mf, etc) recited in claim 1 may need to be defined. Appropriate correction is required.
Claim Rejections - 35 USC § 101
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 1-14 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more.
Step 1 (Does this claim fall within at least one statutory category?):
Claims 1-11 and 13-14 are directed to a method.
Claim 12 is directed to a system.
Therefore, claims 1-14 fall into at least one of the four statutory categories.
Step 2A, Prong 1: ((a) identify the specific limitation(s) in the claim that recites an abstract idea: and (b) determine whether the identified limitation(s) falls within at least one of the groups of abstract ideas enumerates in MPEP 2106.04(a)(2)):
Claim 1:
A computer-implemented method for determining a state evolution of a real system with a plurality N of degrees of freedom, comprising the following steps:
a) determining states for each of the plurality N of degrees of freedom up to a time to, wherein, in particular, the determining of states for each of the plurality N of degrees of freedom is carried out by measuring corresponding state variables of the real system “mental process i.e. concepts performed in the human mind or with pen and paper (including an observation, evaluation judgement, opinion) and/or mathematical concepts”;
b) selecting a degree of freedom f from the plurality N of degrees of freedom “mental process i.e. concepts performed in the human mind or with pen and paper (including an observation, evaluation judgement, opinion) and/or mathematical concepts”;
c) determining a similarity Af between the at least one selected degree of freedom f and plurality of other degrees of freedom of the plurality N of degrees of freedom of the real system for the determined states “mental process i.e. concepts performed in the human mind or with pen and paper (including an observation, evaluation judgement, opinion) and/or mathematical concepts”;
d) determining a selection Mf of degrees of freedom from the plurality N of degrees of freedom based on the similarity Af “mental process i.e. concepts performed in the human mind or with pen and paper (including an observation, evaluation judgement, opinion) and/or mathematical concepts”; and
e) determining the state evolution for the at least one selected degree of freedom f based on the selection Mf of degrees of freedom “mental process i.e. concepts performed in the human mind or with pen and paper (including an observation, evaluation judgement, opinion) and/or mathematical concepts”.
Step 2A, Prong 2 (1. Identifying whether there are any additional elements recited in the claim beyond the judicial exception; and 2. Evaluating those additional elements individually and in combination to determine whether the claim as a whole integrates the exception into a practical application): The claim is directed to the judicial exception.
Claim 1 has no additional limitations that integrate the abstract idea into a practical application.
Step 2B: (Does the claim recite additional elements that amount to significantly more than the judicial exception? No):
Claim 1 has no additional limitations that integrate the abstract idea into an inventive concept.
As per claims 2-11, and 13-14, the claims fall into “mental process i.e. concepts performed in the human mind or with pen and paper (including an observation, evaluation judgement, opinion) and/or mathematical concepts”.
As per claim 12, independent claim 12 recites limitations analogous in scope to those of independent claim 1, and as such are similar rejected. Further, claim 12 recites additional elements of “a processor” and “a storage medium”. The components recited at a high level of generality (e.g. a generic computer element for performing a generic computer functions) such that it amounts to no more than mere application of the judicial exception using generic computer component(s). Accordingly, the additional element(s) of each of these claims do not integrate the abstract idea into a practical application because they do not impose any meaningful limits on practicing the abstract idea. Further, as discussed above with respect to the integration of the abstract into a practical application, the additional elements of “a processor” and “a storage medium” amount to no more than mere instructions to apply the judicial exception using generic computer component(s). Mere instructions to apply an exception using a generic computer component cannot provide an inventive concept.
Claim Rejections - 35 USC § 103
The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
The factual inquiries for establishing a background for determining obviousness under 35 U.S.C. 103 are summarized as follows:
1. Determining the scope and contents of the prior art.
2. Ascertaining the differences between the prior art and the claims at issue.
3. Resolving the level of ordinary skill in the pertinent art.
4. Considering objective evidence present in the application indicating obviousness or nonobviousness.
Claims 1-7, and 10-14 are rejected under 35 U.S.C. 103 as being unpatentable over Tang et al, (D. Tang, X. Sun, Q. Yue, Z. Shi, J. Feng, “Research of complex modal parameters extraction of a multi-degree-of freedom structure based on similarity search” pgs. 307-314, 2015) in view of Montesinos et al (M. Montesinos, “Relational Evolution of the Degrees of Freedom of Generally Covariant Quantum Theories”, pgs. 1-28, 2001).
1. Tang et al discloses a computer-implemented method for determining a state evolution of a real system with a plurality N of degrees of freedom, comprising the following steps:
a) determining states for each of the plurality N of degrees of freedom up to a time to, wherein, in particular, the determining of states for each of the plurality N of degrees of freedom is carried out by measuring corresponding state variables of the real system (See: pg. 309, left side column, “3. The modal parameters extraction based on similarity search” Assuming that the time series of the free response in each structure can be obtained by actual monitoring….. Eq. (17) has the specific physical meaning and ζn describes the attenuation characteristics of the vibration system, which is the damping ratio of the system. ωn corresponds to the natural frequency of the system and θn corresponds to the initial phase of the system. For a system which has N-DOF,φi and γji in Eq. (13) can be separated when extracting parameters for n-times. Because of the existence of γji each physical coordinate cannot reach equilibrium position and maximum position at the same time when vibrating;);
b) selecting a degree of freedom f from the plurality N of degrees of freedom (See: Abstract, a method for the extraction of modal parameters that could be useful for the parameter identification of complex structural dynamic modes of multi degree of freedom systems that may be subject to environmental load excitations; pg. 311, right side column, paragraph 1, The normalized time-domain wave forms and spectrums of the 1st,2nd and 3rd free vibration functions of the degree of freedom areshowninFig.2.);
c) determining a similarity Af between the at least one selected degree of freedom f and plurality of other degrees of freedom of the plurality N of degrees of freedom of the real system for the determined states (See: pg. 308, left side column, In consideration of the identified problem mentioned above, a method of Multi-DOF structure complex modal parameter extraction based on similarity search is proposed in this paper. This method is based on the Multi-DOF complex modal theory of the general viscous system in which the most similar atoms with a free response structure are selected from the constructed dictionary so that the goal of identifying the modal parameters of the Multi-DOF structure has been achieved. The complex modal frequency, damping ratio and modal shape can be globally extracted by using this method with the measurement data of the Multi-DOF displacement. Furthermore, the initial phase has practical meaning for this method. The MP and the GA are borrowed into the method to perform the similarity comparison and reduce the time complexity of the search process. Simulation and experiment results show that the method proposed in this paper can identify the complex modal frequency, damping ratio and modal shape with high precision; pg. 309, left side column, “3. The modal parameters extraction based on similarity search”, .For as ystem which has N-DOF,φi and γji in Eq. (13) can be separated when extracting parameters for n-times. Because of the existence of γji each physical coordinate cannot reach equilibrium position and maximum position at the same time when vibrating. Principle mode is no longer a standing wave, but a traveling wave. Therefore, it may probably lead to modal deformation and associated distortions. The free response functions vary when ζn, ωn, and θn have different values. The modal parameters extraction based on similarity search is to search ζn, ωn and θn to let gnðt; ωn; ζn; θnÞ be the most similar atom with the signal acquired by RDT. The most similar gnðt;ωn;ζn;θnÞ is one free vibration attenuation function separated from the dictionary. The gnðt;ωn;ζn;θnÞ is removed from the RDT signal, the process is repeated, and the modal parameters are extracted. The MP is applied to the RDT sequence δxkxk ðtÞ for searching and extracting parameters. The principle of the most similar atoms is based on the dot product between atoms in the dictionary and δxkxk ðtÞ).
Tang et al does not specify but Montesinos et al discloses d) determining a selection Mf of degrees of freedom from the plurality N of degrees of freedom (See: Abstract, We study the classical and quantum dynamics of generally covariant theories with vanishing Hamiltonian and with a finite number of degrees of freedom. In particular, the geometric meaning of the full solution of the relational evolution of the degrees of freedom is displayed, which means the determination of the total number of evolving constants of motion required. Also a method to find evolving constants is proposed. The generalized Heisenberg picture needs M time variables, as opposed to the Heisenberg picture of standard quantum mechanics where one time variable t is enough); and e) determining the state evolution for the at least one selected degree of freedom f based on the selection Mf of degrees of freedom (See: pg. 7, First, they give the relational evolution of the coordinates qi and the momenta pi for any fixed point (˜qa, ˜ pa) of the physical phase space, i.e., it is possible to choose M coordinates denoted by qm (or momenta pm; or a combination of both) as ‘clocks’ and describe the evolution of the remaining set of coordinates and momenta as functions of the qm for any physical state (˜qa, ˜ pa) of the system. Second, if we fix the values of this M coordinates, say qm c q*m then, the before mentioned expressions of coordinates and momenta give M-parameter families of physical observables defined on gph, q*m being the parameters; pgs. 26-27, “5. Concluding Remarks”, We have displayed the full solution of the relational evolution of the degrees of freedom of fully constrained theories with a finite number of degrees of free dom (see Eqs. (19), and (20)). Our procedure follows from the embedding equations of the coordinates and momenta in the unconstrained phase space (see Eqs. (6), and (7)) plus the expressions of the M internal time variables (see Eqs. (6), and (7)) plus the expressions of the M internal time variables (see Eq. (10)). The form of the solution contains all the evolving constants of motion needed in the description of the classical dynamics of fully constrained theories,….. Combining the expressions of this evolving constants with the expressions of the physical observables the full relational evolution of the coordinates and momenta is obtained. Finally, we have also ana lysed on a general setting the quantum version of the relational evolution of the degrees of freedom of fully constrained theories).
It would have been obvious before the effective filing date to combine relational evolution of the degree of freedom of covariant quantum theories as taught by Montesinos et al to multi-degree of freedom structure based on similarity search of Tang et al would be to minimize the uncertainty relations of position and momentum (Montesinos et al, pg. 26).
2. Tang et al discloses the computer-implemented method according to claim 1, wherein the steps b) to d) are repeated for each degree of freedom of the plurality N of degrees of freedom for determining the degrees of freedom to be considered in determining the state evolution for the entire real system (See: pg. 311, left side column, 6. Judgement of the end of the iteration condition: Processes (2) through (4)are repeated until the modal parameters of all of the orders of the system are extracted).
3. Montesinos et al discloses the computer-implemented method according to claim 1, wherein for the plurality N of the degrees of freedom N is larger than 10, preferably larger than 100 and, particularly preferred, larger than 1000 (See: Abstract, We study the classical and quantum dynamics of generally covariant theories with vanishing Hamiltonian and with a finite number of degrees of freedom; pg. 2 third paragraph, we analyse the ‘problem of time’ in generally covariant theories with vanishing Hamiltonian and with a finite number D of degrees of freedom; pg. 8 second paragraph, Thus, Eqs. (19), and (20) constitute the full set of evolving constants needed in the relational description of the dynamics of generally covariant theories with a finite number D of degrees of freedom).
4. Montesinos et al discloses the computer-implemented method according to any one of claim 1, wherein for the selection Mf is less than 1000, preferably less than 100 (See: Abstract, We study the classical and quantum dynamics of generally covariant theories with vanishing Hamiltonian and with a finite number of degrees of freedom; pg. 2 third paragraph, we analyse the ‘problem of time’ in generally covariant theories with vanishing Hamiltonian and with a finite number D of degrees of freedom; pg. 8 second paragraph, Thus, Eqs. (19), and (20) constitute the full set of evolving constants needed in the relational description of the dynamics of generally covariant theories with a finite number D of degrees of freedom).
5. Tang et al discloses the computer-implemented method according to any one of claim 1, wherein the number of the degrees of freedom in the selection Mf is determined by a predefined limit value for the similarity (See: pg. 308, left side column, In consideration of the identified problem mentioned above, a method of Multi-DOF structure complex modal parameter extraction based on similarity search is proposed in this paper. This method is based on the Multi-DOF complex modal theory of the general viscous system in which the most similar atoms with a free response structure are selected from the constructed dictionary so that the goal of identifying the modal parameters of the Multi-DOF structure has been achieved. The complex modal frequency, damping ratio and modal shape can be globally extracted by using this method with the measurement data of the Multi-DOF displacement. Furthermore, the initial phase has practical meaning for this method. The MP and the GA are borrowed into the method to perform the similarity comparison and reduce the time complexity of the search process. Simulation and experiment results show that the method proposed in this paper can identify the complex modal frequency, damping ratio and modal shape with high precision; pg. 309, left side column, “3. The modal parameters extraction based on similarity search”, .For as ystem which has N-DOF,φi and γji in Eq. (13) can be separated when extracting parameters for n-times. Because of the existence of γji each physical coordinate cannot reach equilibrium position and maximum position at the same time when vibrating. Principle mode is no longer a standing wave, but a traveling wave. Therefore, it may probably lead to modal deformation and associated distortions. The free response functions vary when ζn, ωn, and θn have different values. The modal parameters extraction based on similarity search is to search ζn, ωn and θn to let gnðt; ωn; ζn; θnÞ be the most similar atom with the signal acquired by RDT. The most similar gnðt;ωn;ζn;θnÞ is one free vibration attenuation function separated from the dictionary. The gnðt;ωn;ζn;θnÞ is removed from the RDT signal, the process is repeated, and the modal parameters are extracted. The MP is applied to the RDT sequence δxkxk ðtÞ for searching and extracting parameters. The principle of the most similar atoms is based on the dot product between atoms in the dictionary and δxkxk ðtÞ).
6. Montesinos et al discloses the computer-implemented method according to any one of claim 1, wherein the number of the degrees of freedom in the selection Mf is predefined (See: Abstract, We study the classical and quantum dynamics of generally covariant theories with vanishing Hamiltonian and with a finite number of degrees of freedom; pg. 2 third paragraph, we analyse the ‘problem of time’ in generally covariant theories with vanishing Hamiltonian and with a finite number D of degrees of freedom; pg. 8 second paragraph, Thus, Eqs. (19), and (20) constitute the full set of evolving constants needed in the relational description of the dynamics of generally covariant theories with a finite number D of degrees of freedom).
7. Tang et al discloses the computer-implemented method according to any one of claim 1, wherein the similarity is given by a cross correlation or transinformation (See: pg. 312, left side column, “5. Analysis of an FPSO single point mooring system”, Considering that the searching atoms are attenuation functions, the Multi-DOF response data of the tilt sensors are obtained for the self-correlation and cross-correlation, assuming that the response).
10. Tang et al discloses the computer-implemented method according to claim 1, wherein the real system is a thermodynamic system, EEG currents, a fluidic system, a movement system or a flow system (See: Fig. 1, the vibration system in 3DOF).
11. Montesinos et al discloses the computer-implemented method according to any one of claim 1, wherein a control variable is determined to control the real system, depending on the determined state evolution (See: pg. 2, third paragraph, By plugging the expressions of the time variables tm in terms the original canonical variables into the expressions of coordinates and momenta, we get the full relational evolution of the phase space degrees of freedom for any physical state of gph. This way of expressing the full solution of the dynamics of generally covariant theories constitutes the full set of evolving constants of motion required in their dynamics, and is displayed in Sect. 2).
As per Claim 12: The instant claim recites substantially same limitation as the above rejected claim 1, and therefore rejected under the same rationale.
13. Montesinos et al discloses the computer-implemented method according to claim 4, wherein the selection Mf is less than 100 (See: Abstract, We study the classical and quantum dynamics of generally covariant theories with vanishing Hamiltonian and with a finite number of degrees of freedom; pg. 2 third paragraph, we analyse the ‘problem of time’ in generally covariant theories with vanishing Hamiltonian and with a finite number D of degrees of freedom; pg. 8 second paragraph, Thus, Eqs. (19), and (20) constitute the full set of evolving constants needed in the relational description of the dynamics of generally covariant theories with a finite number D of degrees of freedom).
14.Montesinos et al discloses the computer implemented method according to claim 13, wherein the selection Mf is less than 10 (See: Abstract, We study the classical and quantum dynamics of generally covariant theories with vanishing Hamiltonian and with a finite number of degrees of freedom; pg. 2 third paragraph, we analyse the ‘problem of time’ in generally covariant theories with vanishing Hamiltonian and with a finite number D of degrees of freedom; pg. 8 second paragraph, Thus, Eqs. (19), and (20) constitute the full set of evolving constants needed in the relational description of the dynamics of generally covariant theories with a finite number D of degrees of freedom).
Claims 8 and 9 are rejected under 35 U.S.C. 103 as being unpatentable over Tang et al & Montesinos et al as applied to claim 1 above, and further in view of Pathak et al, (J. Pathak, B. Hunt, M. Girvan, Z. Lu, E. Ott, “Model-free Prediction of Large Spatiotemporally Chaotic Systems from Data: A Reservoir Computing Approach”, pgs. 1-5, 2018).
8. Tang et al and Montesinos et al discloses the computer-implemented method according to claim 1.
However, none of the references disclose but Pathak et al discloses wherein the determination of the state evolution is performed using a recurrent neural network, in particular using reservoir computing (See: Abstract, demonstrate the effectiveness of using machine learning for model-free prediction of spatiotemporally chaotic systems of arbitrarily large spatial extent and attractor dimension purely from observations of the system’s past evolution. We present a parallel scheme with an example implementation based on the reservoir computing paradigm and demonstrate the scalability of our scheme using the Kuramoto Sivashinsky equation as an example of a spatiotemporally chaotic system; pg. 024102-1, we speculate that, because of their essential dynamical character (see below), artificial neural networks with recurrent connections [11–13], such as reservoir computers, may be inherently well suited for tasks which are themselves dynamical in character, such as prediction or inference of unmeasured state variables of a deterministic system).
It would have been obvious before the effective filing date to combine a reservoir computing approach as taught by Montesinos et al to multi-degree of freedom structure based on similarity search of Tang et al would be to minimize the uncertainty relations of position and momentum (Montesinos et al, pg. 26).
9. Pathak et al discloses the computer-implemented method according to claim 8, wherein the recurrent neural network is trained on the basis of the determined states for each of the plurality of N degrees of freedom up to a time to (pg. 024102-1, we speculate that, because of their essential dynamical character (see below), artificial neural networks with recurrent connections [11–13], such as reservoir computers, may be inherently well suited for tasks which are themselves dynamical in character, such as prediction or inference of unmeasured state variables of a deterministic system).
It would have been obvious before the effective filing date to combine a reservoir computing approach as taught by Montesinos et al to multi-degree of freedom structure based on similarity search of Tang et al would be to minimize the uncertainty relations of position and momentum (Montesinos et al, pg. 26).
Conclusion
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KIBROM K. GEBRESILASSIE
Primary Examiner
Art Unit 2189
/KIBROM K GEBRESILASSIE/
Primary Examiner, Art Unit 2189 02/13/2026