DETAILED ACTION
The present application, filed on 6/6/2024 is being examined under the AIA first inventor to file provisions.
The following is a non-final First Office Action on the Merits. Claims 1-20 are pending and have been considered below.
Information Disclosure Statement (IDS)
The information disclosure statement (IDS) submitted on 12/3/2024; 12/3/2024; 12/3/2024; 12/3/2024; 3/20/2025; 3/9/2025; 3/26/2025; 7/20/2026 is in compliance with the provisions of 37 CFR 1.97. Accordingly, such IDS is being considered by Examiner.
Claim Rejections - 35 USC § 101
35 USC 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 USC 101 because the claimed invention is not directed to patent eligible subject matter. The claimed matter is directed to a judicial exception, i.e. an abstract idea, not integrated into a practical application, and without significantly more.
Per Step 1 of the multi-step eligibility analysis, claims 1-12 are directed to a system, claims 13-18 are directed to a system, claim 19 is directed to a computer implemented method, and claim 20 is directed to a computer implemented method.
Thus, on its face, each independent claim and the associated dependent claims are directed to a statutory category of invention.
[INDEPENDENT CLAIMS]
Per Step 2A.1. Independent claim 1, (which is representative of independent claims 19-20) is rejected under 35 USC 101 because the independent claim is directed to an abstract idea, a judicial exception, without reciting additional elements that integrate the judicial exception into a practical application.
The limitations of the independent claim 1 (which is representative of independent claims 19-20) recite an abstract idea, shown in bold below:
[A] A system, comprising:
[B] clock circuitry to generate a local clock signal, the clock circuitry including an oscillator;
[C] clock synchronization circuitry to adjust the local clock signal based on a remote clock; and
[D] a processor to train a machine learning model to predict a frequency or a frequency adjustment for applying to the local clock signal during clock holdover.
Independent claim 1 (which is representative of independent claims 19-20) recites: generating and adjusting a local clock signal ([B], [C]); and training a machine learning model ([D]), which, based on the claim language and in view of the application disclosure, represents a process aimed at: adjusting a parameter in general, particularly the frequency of a clock.
This is a combination that, under its broadest reasonable interpretation, covers performance of limitations expressing following rules or instructions. These fall under the Certain Methods of Organizing Human Activity, i.e., Managing Personal Behavior or Relationships, or Interactions Between People grouping of abstract ideas (see MPEP 2106.04(a)(2)).
Accordingly, it is concluded that independent claim 1 (which is representative of independent claims 13, 19-20) recites an abstract idea that corresponds to a judicial exception.
In addition, or alternatively, this is a combination that, under its broadest reasonable interpretation, covers reasonable performance of limitations expressing observation, evaluation in the human mind. Nothing in the claim elements precludes the steps from being practically performed in the human mind. For example, the step “generate a local clock signal”, as drafted in the context of this claim, encompasses the user manually or mentally generating a signal to measure time, without physical aid. Further, the step “adjust the local clock signal based on a remote clock”, as drafted in the context of this claim, encompasses the user manually or mentally adjusting the signal to measure time, without physical aid. Further, the step “train a machine learning model to predict a frequency or a frequency adjustment”, as drafted in the context of this claim, encompasses the user manually or mentally training a model, without physical aid. These limitations fall under the Mental Processes, i.e., Concepts Performed in the Human Mind grouping of abstract ideas (see MPEP 2106.04(a)(2)). The use of a physical aid would not negate the mental nature of this limitation (see MPEP 2106.04(a)(2) iii B)
Accordingly, it is concluded that independent claim 1 (which is representative of independent claims 13, 19-20) recites an abstract idea that corresponds to a judicial exception.
[INDEPENDENT CLAIMS – Additional Elements]
Per Step 2A.2. The identified abstract idea is not integrated into a practical application because the additional elements in the independent claims only amount to instructions to apply the judicial exception to a computer, or are a general link to a technological environment (see MPEP 2106.05(f); MPEP 2106.05(h)).
For example, the added elements “clock circuitry,” “clock synchronization circuitry,” and “processor” recite computing elements at a high level of generality, generally linking the use of a judicial exception to a particular technological environment (see MPEP 2106.05(h)), or merely using a computer as a tool to perform an abstract idea (MPEP 2106.05(f)).
These additional elements of the independent claims do not preclude from carrying out the identified abstract idea adjusting a parameter in general, particularly the frequency of a clock., and do not serve to integrate the identified abstract idea into a practical application.
Therefore, the additional claim elements of independent claim 1, (which is representative of independent claims 19-20), evaluated individually, as well as a whole, as an ordered combination, do not integrate the identified abstract idea into a practical application and the claims are directed to the recited judicial exception.
Per Step 2B. Independent claim 1 (which is representative of claims independent 19-20) does not include additional elements that are sufficient to amount to significantly more than the judicial exception because, when the independent claim is reevaluated as a whole, as an ordered combination under the considerations of Step 2B, the outcome is the same like under Step 2A.2.
Overall, it is concluded that independent claims 1, 19-20 are deemed ineligible.
Per Step 2A.1. Independent claim 13 is rejected under 35 USC 101 because the independent claim is directed to an abstract idea, a judicial exception, without reciting additional elements that integrate the judicial exception into a practical application.
[A] A system, comprising
[B] a processor to execute a trained machine learning model to predict a frequency or a frequency adjustment for applying to a local clock signal during the clock holdover; and
[C] a memory to store data used by the processor.
Independent claim 13 recites: training a machine learning model ([B]); and storing the data ([C]), which, based on the claim language and in view of the application disclosure, represents a process aimed at: adjusting a parameter in general, particularly the frequency of a clock..
This is a combination that, under its broadest reasonable interpretation, covers performance of limitations expressing following rules or instructions. These fall under the Certain Methods of Organizing Human Activity, i.e., Managing Personal Behavior or Relationships, or Interactions Between People grouping of abstract ideas (see MPEP 2106.04(a)(2)).
Accordingly, it is concluded that independent claim 13 recites an abstract idea that corresponds to a judicial exception.
In addition, or alternatively, this is a combination that, under its broadest reasonable interpretation, covers reasonable performance of limitations expressing observation, evaluation in the human mind. Nothing in the claim elements precludes the steps from being practically performed in the human mind. For example, the step “execute a trained machine learning model to predict a frequency or a frequency adjustment”, as drafted in the context of this claim, encompasses the user manually or mentally training a model, without physical aid. Further, the step “store data used by the processor”, as drafted in the context of this claim, encompasses the user manually or mentally preserving data, without physical aid. These limitations fall under the Mental Processes, i.e., Concepts Performed in the Human Mind grouping of abstract ideas (see MPEP 2106.04(a)(2)). The use of a physical aid would not negate the mental nature of this limitation (see MPEP 2106.04(a)(2) iii B)
Accordingly, it is concluded that independent claim 13 recites an abstract idea that corresponds to a judicial exception.
[INDEPENDENT CLAIMS – Additional Elements]
Per Step 2A.2. The identified abstract idea is not integrated into a practical application because the additional elements in the independent claims only amount to instructions to apply the judicial exception to a computer, or are a general link to a technological environment (see MPEP 2106.05(f); MPEP 2106.05(h)).
For example, the added elements “a processor,” and “a memory” recite computing elements at a high level of generality, generally linking the use of a judicial exception to a particular technological environment (see MPEP 2106.05(h)), or merely using a computer as a tool to perform an abstract idea (MPEP 2106.05(f)).
These additional elements of the independent claims do not preclude from carrying out the identified abstract idea adjusting a parameter in general, particularly the frequency of a clock., and do not serve to integrate the identified abstract idea into a practical application.
Therefore, the additional claim elements of independent claim 13, evaluated individually, as well as a whole, as an ordered combination, do not integrate the identified abstract idea into a practical application and the claims are directed to the recited judicial exception.
Per Step 2B. Independent claim 13 does not include additional elements that are sufficient to amount to significantly more than the judicial exception because, when the independent claim is reevaluated as a whole, as an ordered combination under the considerations of Step 2B, the outcome is the same like under Step 2A.2.
Overall, it is concluded that independent claims 13 are deemed ineligible.
[DEPENDENT CLAIMS]
Dependent claim 3 recites:
train the machine learning model based on data collected during at least one period in which the remote clock is available to the system for clock synchronization purposes.
The elements in these dependent claims are comparable to receiving/transmitting data, processing data, storing results or transmitting data that serves merely to implement the abstract idea using computing components for performing computer functions (corresponding to the words “apply it” or an equivalent), or merely uses a computer as a tool to perform the identified abstract idea. Thus, it is concluded that these claim elements do not integrate the identified abstract idea (adjusting a parameter in general, particularly the frequency of a clock.) into a practical application (see MPEP 2106.05(f)(2)). When considered individually, these added claim elements further elaborate on the abstract idea identified in the independent claims, because the dependent claims continue to recite the identified abstract idea.
The dependent claims elements have the same relationship to the underlying abstract idea as outlined in the independent claims analysis above. It is readily clear that the dependent claim elements are not directed to any specific improvements of the independent claims and do not practically or significantly alter how the identified abstract idea would be performed. When considered as a whole, as an ordered combination, the dependent claims further elaborate on the previously identified abstract idea (adjusting a parameter in general, particularly the frequency of a clock.).
Therefore, dependent claim 3 is deemed ineligible. As a result, it is concluded that the dependent claim elements do not integrate the identified abstract idea into a practical application (see MPEP 2106.05(f)(2)).
Dependent claim 4, which is representative of dependent claims 5, 9-10, 16-17, recites:
predict the frequency or the frequency adjustment based on any one or more of the following:
at least one measurement of an environmental parameter taken during the clock holdover;
at least one measurement of temperature of the oscillator taken during the clock holdover;
at least one measurement of vibration of the oscillator taken during the clock holdover;
an age of the oscillator during the clock holdover;
a measurement of humidity taken during the clock holdover;
prior frequency adjustments to the local clock signal during the clock holdover;
a current frequency of the local clock signal during the clock holdover; or
when the clock holdover started.
The elements in these dependent claims are comparable to receiving/transmitting data, processing data, storing results or transmitting data that serves merely to implement the abstract idea using computing components for performing computer functions (corresponding to the words “apply it” or an equivalent), or merely uses a computer as a tool to perform the identified abstract idea. Thus, it is concluded that these claim elements do not integrate the identified abstract idea (adjusting a parameter in general, particularly the frequency of a clock.) into a practical application (see MPEP 2106.05(f)(2)). When considered individually, these added claim elements further elaborate on the abstract idea identified in the independent claims, because the dependent claims continue to recite the identified abstract idea.
The dependent claims elements have the same relationship to the underlying abstract idea as outlined in the independent claims analysis above. It is readily clear that the dependent claim elements are not directed to any specific improvements of the independent claims and do not practically or significantly alter how the identified abstract idea would be performed. When considered as a whole, as an ordered combination, the dependent claims further elaborate on the previously identified abstract idea (adjusting a parameter in general, particularly the frequency of a clock.).
Therefore, dependent claim 4 (which is representative of dependent claims 5, 9-10, 16-17) is deemed ineligible. As a result, it is concluded that the dependent claim elements do not integrate the identified abstract idea into a practical application (see MPEP 2106.05(f)(2)).
Dependent claim 6 recites:
filter data used to train the machine learning model or to
filter prediction data output by the trained machine learning model based on data derived from a technical specification of the oscillator.
The elements in these dependent claims are comparable to receiving/transmitting data, processing data, storing results or transmitting data that serves merely to implement the abstract idea using computing components for performing computer functions (corresponding to the words “apply it” or an equivalent), or merely uses a computer as a tool to perform the identified abstract idea. Thus, it is concluded that these claim elements do not integrate the identified abstract idea (adjusting a parameter in general, particularly the frequency of a clock.) into a practical application (see MPEP 2106.05(f)(2)). When considered individually, these added claim elements further elaborate on the abstract idea identified in the independent claims, because the dependent claims continue to recite the identified abstract idea.
The dependent claims elements have the same relationship to the underlying abstract idea as outlined in the independent claims analysis above. It is readily clear that the dependent claim elements are not directed to any specific improvements of the independent claims and do not practically or significantly alter how the identified abstract idea would be performed. When considered as a whole, as an ordered combination, the dependent claims further elaborate on the previously identified abstract idea (adjusting a parameter in general, particularly the frequency of a clock.).
Therefore, dependent claim 6 is deemed ineligible. As a result, it is concluded that the dependent claim elements do not integrate the identified abstract idea into a practical application (see MPEP 2106.05(f)(2)).
Dependent claim 7 recites:
predict the frequency or the frequency adjustment for applying to the local clock signal during the clock holdover.
The elements in these dependent claims are comparable to receiving/transmitting data, processing data, storing results or transmitting data that serves merely to implement the abstract idea using computing components for performing computer functions (corresponding to the words “apply it” or an equivalent), or merely uses a computer as a tool to perform the identified abstract idea. Thus, it is concluded that these claim elements do not integrate the identified abstract idea (adjusting a parameter in general, particularly the frequency of a clock.) into a practical application (see MPEP 2106.05(f)(2)). When considered individually, these added claim elements further elaborate on the abstract idea identified in the independent claims, because the dependent claims continue to recite the identified abstract idea.
The dependent claims elements have the same relationship to the underlying abstract idea as outlined in the independent claims analysis above. It is readily clear that the dependent claim elements are not directed to any specific improvements of the independent claims and do not practically or significantly alter how the identified abstract idea would be performed. When considered as a whole, as an ordered combination, the dependent claims further elaborate on the previously identified abstract idea (adjusting a parameter in general, particularly the frequency of a clock.).
Therefore, dependent claim 7 is deemed ineligible. As a result, it is concluded that the dependent claim elements do not integrate the identified abstract idea into a practical application (see MPEP 2106.05(f)(2)).
Dependent claim 8, which is representative of dependent claims 15, recites:
apply the predicted frequency or the predicted frequency adjustment to adjust the local clock signal.
The elements in these dependent claims are comparable to receiving/transmitting data, processing data, storing results or transmitting data that serves merely to implement the abstract idea using computing components for performing computer functions (corresponding to the words “apply it” or an equivalent), or merely uses a computer as a tool to perform the identified abstract idea. Thus, it is concluded that these claim elements do not integrate the identified abstract idea (adjusting a parameter in general, particularly the frequency of a clock.) into a practical application (see MPEP 2106.05(f)(2)). When considered individually, these added claim elements further elaborate on the abstract idea identified in the independent claims, because the dependent claims continue to recite the identified abstract idea.
The dependent claims elements have the same relationship to the underlying abstract idea as outlined in the independent claims analysis above. It is readily clear that the dependent claim elements are not directed to any specific improvements of the independent claims and do not practically or significantly alter how the identified abstract idea would be performed. When considered as a whole, as an ordered combination, the dependent claims further elaborate on the previously identified abstract idea (adjusting a parameter in general, particularly the frequency of a clock.).
Therefore, dependent claim 8 (which is representative of dependent claims 15) is deemed ineligible. As a result, it is concluded that the dependent claim elements do not integrate the identified abstract idea into a practical application (see MPEP 2106.05(f)(2)).
Dependent claim 11, which is representative of dependent claims 18, recites:
provide a confidence level associated with the prediction of the frequency or the frequency adjustment.
The elements in these dependent claims are comparable to receiving/transmitting data, processing data, storing results or transmitting data that serves merely to implement the abstract idea using computing components for performing computer functions (corresponding to the words “apply it” or an equivalent), or merely uses a computer as a tool to perform the identified abstract idea. Thus, it is concluded that these claim elements do not integrate the identified abstract idea (adjusting a parameter in general, particularly the frequency of a clock.) into a practical application (see MPEP 2106.05(f)(2)). When considered individually, these added claim elements further elaborate on the abstract idea identified in the independent claims, because the dependent claims continue to recite the identified abstract idea.
The dependent claims elements have the same relationship to the underlying abstract idea as outlined in the independent claims analysis above. It is readily clear that the dependent claim elements are not directed to any specific improvements of the independent claims and do not practically or significantly alter how the identified abstract idea would be performed. When considered as a whole, as an ordered combination, the dependent claims further elaborate on the previously identified abstract idea (adjusting a parameter in general, particularly the frequency of a clock.).
Therefore, dependent claim 11 (which is representative of dependent claims 18) is deemed ineligible. As a result, it is concluded that the dependent claim elements do not integrate the identified abstract idea into a practical application (see MPEP 2106.05(f)(2)).
Dependent claims 2, 12 recite:
wherein the clock circuitry includes a hardware clock driven by the local clock signal.
wherein the machine learning model may be trained in accordance with any one or more of the following machine learning models: a time series prediction model; an ARIMA model; an autoregressive model; a moving average model; a recurrent neural network (RNN); a long short-term memory (LSTM), a gated recurrent unit (GRU); or a transformer model.
These further elements in the dependent claims do not perform any claimed method steps. They describe the nature, structure and/or content of other claim elements (in this instance – the clock circuitry) and as such, cannot change the nature of the identified abstract idea (see MPEP 2106.07). The nature, form or structure of the other claim elements themselves do not practically or significantly alter how the identified abstract idea would be performed and do not provide more than a general link to a technological environment.
Therefore, dependent claims 2, 12 are deemed ineligible.
When the dependent claims are considered as a whole, as an ordered combination, the claim elements noted above appear to merely apply the abstract concept to a technical environment in a very general sense. The most significant elements, which form the abstract concept, are set forth in the independent claims. The fact that the computing devices and the dependent claims are facilitating the abstract concept is not enough to confer statutory subject matter eligibility, since their individual and combined significance do not transform the identified abstract concept at the core of the claimed invention into eligible subject matter. Therefore, it is concluded that the dependent claims of the instant application, considered individually, or as a as a whole, as an ordered combination, do not amount to significantly more (see MPEP 2106.07(a)II).
In sum, claims 1-20 are rejected under 35 USC 101 as being directed to non-statutory subject matter.
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 difference 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 the invention was made.
The factual inquiries set forth in Graham v. John Deere Co., 383 U.S. 1, 148 USPQ 459 (1966), that are applied for establishing a background for determining obviousness under 35 U.S.C. 103(a) are summarized as follows:
i. Determining the scope and contents of the prior art.
ii. Ascertaining the differences between the prior art and the claims at issue.
iii. Resolving the level of ordinary skill in the pertinent art.
iv. Considering objective evidence present in the application indicating obviousness or nonobviousness.
Claims 1-10, 12-17, 19-20 are rejected under 35 U.S.C. 103 as being unpatentable over Melanson et al (US 2015/0372681), in view of Satoh et al (US 2021/0329164).
Regarding Claims 1, 7, 14, 19-20: Melanson discloses: A system, comprising:
clock circuitry to
generate a local clock signal, the clock circuitry including an oscillator; {see at least fig1, rc106, [0018] clock generation circuitry}
clock synchronization circuitry to
adjust the local clock signal based on a remote clock; and {see at least [0004] synchronization to an accurate clock; [0010] synchronization to a reference clock; [0020]; fig1, fig3, [0027]-[0028]}
a processor to
… to predict the frequency or the frequency adjustment for applying to the local clock signal during clock holdover. {see at least [0024] predict error based on sensed temperature. The claim element “to predict a frequency or a frequency adjustment for applying to the local clock signal during clock holdover” consists entirely of language disclosing at most a reason to have performed earlier method steps (intended use or field of use), but does not affect the functions in a manipulative sense (see MPEP 2103 I C) and imparts neither structure nor functionality to the claimed method (see MPEP 2111.05, MPEP 2114 and authorities cited therein), so it is considered but given no patentable weight. The reference is provided for the purpose of compact prosecution.}
Melanson does not disclose, however, Satoh discloses:
train a machine learning model … {see at least [0134] learning using training training data; fig14, [0182] CNN has been trained}
It would have been obvious to one of ordinary skill in the art, at the time of filing, to modify Melanson to include the elements of Satoh. One would have been motivated to do so, in order to improve adjustment accuracy. Furthermore, the Supreme Court has supported that combining well known prior art elements, in a well-known manner, to obtain predictable results is sufficient to determine an invention obvious over such combination (see KSR International Co. v. Teleflex Inc. (KSR), 550 U.S.,82 USPQ2d 1385 (2007) & MPEP 2143). In the instant case, Melanson evidently discloses adjusting the clock frequency. Satoh is merely relied upon to illustrate the functionality of training a machine learning model in the same or similar context. Since both adjusting the clock frequency, as well as training a machine learning model are implemented through well-known computer technologies in the same or similar context, combining their features as outlined above using such well-known computer technologies (i.e., conventional software/hardware configurations), would be reasonable, according to one of ordinary skill in the art. Moreover, since the elements disclosed by Melanson, as well as Satoh would function in the same manner in combination as they do in their separate embodiments, it is concluded that their resulting combination would be predictable. Accordingly, the claimed subject matter is obvious over Melanson / Satoh.
Regarding Claims 2: Melanson, Satoh discloses the limitations of Claims 1. Melanson further discloses:
wherein the clock circuitry includes a hardware clock driven by the local clock signal. {see at least fig1, rc104, rc112, [0019], [0022]-[0025] oscillator}
Regarding Claims 3: Melanson, Satoh discloses the limitations of Claims 1. Melanson further discloses: wherein the processor is to
… in which the remote clock is available to the system for clock synchronization purposes. {see at least [0003]-[0004] synchronization purpose}
Satoh further discloses:
train the machine learning model based on data collected during at least one period … {see at least fig11, rc52, [0182] CNN trained}
It would have been obvious to one of ordinary skill in the art, at the time of filing, to modify Melanson, Satoh to include additional elements of Satoh. One would have been motivated to do so, in order to improve adjustment accuracy. Furthermore, the Supreme Court has supported that combining well known prior art elements, in a well-known manner, to obtain predictable results is sufficient to determine an invention obvious over such combination (see KSR International Co. v. Teleflex Inc. (KSR), 550 U.S.,82 USPQ2d 1385 (2007) & MPEP 2143). In the instant case, Melanson, Satoh evidently discloses adjusting the clock frequency. Satoh is merely relied upon to illustrate the additional functionality of training a machine learning model in the same or similar context. Since the subject matter is merely a combination of old elements, and in the combination each element would have performed the same function it performed separately, one having ordinary skill in the art before the effective filing date would have recognized that the results of the combination were predictable.
Regarding Claims 4-5, 9-10, 16-17: Melanson, Satoh discloses the limitations of Claims 3, 7, 13. Melanson further discloses: wherein the machine learning model is to
predict the frequency or the frequency adjustment based on any one or more of the following:
at least one measurement of an environmental parameter taken during the clock holdover;
at least one measurement of temperature of the oscillator taken during the clock holdover; {see at least [abstract], [0024] predict error based on sensed temperature; temperature based on compensation,}
at least one measurement of vibration of the oscillator taken during the clock holdover;
an age of the oscillator during the clock holdover;
a measurement of humidity taken during the clock holdover;
prior frequency adjustments to the local clock signal during the clock holdover;
a current frequency of the local clock signal during the clock holdover; or
when the clock holdover started.
Regarding Claims 6: Melanson, Satoh discloses the limitations of Claims 3. Satoh further discloses: wherein processor is to
filter data used to train the machine learning model or to filter prediction data output by the trained machine learning model based on data derived from a technical specification of the oscillator. {see at least [0229]-[0231] size of filter (based on the BRI (MPEP 2111), reads on filtering the input data). The claim element “used to train the machine learning model or to filter prediction data output by the trained machine learning model based on data derived from a technical specification of the oscillator” consists entirely of language disclosing at most a reason to have performed earlier method steps (intended use or field of use), but does not affect the functions in a manipulative sense (see MPEP 2103 I C) and imparts neither structure nor functionality to the claimed method (see MPEP 2111.05, MPEP 2114 and authorities cited therein), so it is considered but given no patentable weight. The reference is provided for the purpose of compact prosecution.}
It would have been obvious to one of ordinary skill in the art, at the time of filing, to modify Melanson, Satoh to include additional elements of Satoh. One would have been motivated to do so, in order to provide the model with the right data only. Furthermore, the Supreme Court has supported that combining well known prior art elements, in a well-known manner, to obtain predictable results is sufficient to determine an invention obvious over such combination (see KSR International Co. v. Teleflex Inc. (KSR), 550 U.S.,82 USPQ2d 1385 (2007) & MPEP 2143). In the instant case, Melanson, Satoh evidently discloses adjusting the clock frequency. Satoh is merely relied upon to illustrate the additional functionality of filtering input data in the same or similar context. Since the subject matter is merely a combination of old elements, and in the combination each element would have performed the same function it performed separately, one having ordinary skill in the art before the effective filing date would have recognized that the results of the combination were predictable.
Regarding Claims 8, 15: Melanson, Satoh discloses the limitations of Claims 7, 14. Melanson further discloses: wherein the clock synchronization circuitry is to
apply the predicted frequency or the predicted frequency adjustment to adjust the local clock signal. {see at least [0004] keep synchronizing toe an accurate clock (reads on applying the adjustment). The claim element “to adjust the local clock signal” consists entirely of language disclosing at most a reason to have performed earlier method steps (intended use or field of use), but does not affect the functions in a manipulative sense (see MPEP 2103 I C) and imparts neither structure nor functionality to the claimed method (see MPEP 2111.05, MPEP 2114 and authorities cited therein), so it is considered but given no patentable weight. The reference is provided for the purpose of compact prosecution.}
Regarding Claims 12: Melanson, Satoh discloses the limitations of Claims 1. Satoh further discloses:
wherein the machine learning model may be trained in accordance with any one or more of the following machine learning models: a time series prediction model; an ARIMA model; an autoregressive model; a moving average model; a recurrent neural network (RNN) {see at least fig17, rS127, [0216] machine learning process, using RNN}; a long short-term memory (LSTM), a gated recurrent unit (GRU); or a transformer model.
It would have been obvious to one of ordinary skill in the art, at the time of filing, to modify Melanson, Satoh to include additional elements of Satoh. One would have been motivated to do so, in order to utilize a recognized process. Furthermore, the Supreme Court has supported that combining well known prior art elements, in a well-known manner, to obtain predictable results is sufficient to determine an invention obvious over such combination (see KSR International Co. v. Teleflex Inc. (KSR), 550 U.S.,82 USPQ2d 1385 (2007) & MPEP 2143). In the instant case, Melanson, Satoh evidently discloses adjusting the clock frequency. Satoh is merely relied upon to illustrate the additional functionality of utilizing a specific leaning model in the same or similar context. Since the subject matter is merely a combination of old elements, and in the combination each element would have performed the same function it performed separately, one having ordinary skill in the art before the effective filing date would have recognized that the results of the combination were predictable.
Regarding Claim 13: Melanson discloses: A system, comprising:
a processor to
… to predict a frequency or a frequency adjustment for applying to a local clock signal during the clock holdover; and {see at least [0024] predict error based on sensed temperature. The claim element “to predict a frequency or a frequency adjustment for applying to a local clock signal during the clock holdover” consists entirely of language disclosing at most a reason to have performed earlier method steps (intended use or field of use), but does not affect the functions in a manipulative sense (see MPEP 2103 I C) and imparts neither structure nor functionality to the claimed method (see MPEP 2111.05, MPEP 2114 and authorities cited therein), so it is considered but given no patentable weight. The reference is provided for the purpose of compact prosecution.}
a memory to
store data used by the processor. {see at least fig2, rc204, [0025] data stored in table}
Melanson does not disclose, however, Satoh discloses:
execute a trained machine learning model … {see at least [0134] learning using training training data; fig14, [0182] CNN has been trained}
It would have been obvious to one of ordinary skill in the art, at the time of filing, to modify Melanson to include the elements of Satoh. One would have been motivated to do so, in order to improve adjustment accuracy. Furthermore, the Supreme Court has supported that combining well known prior art elements, in a well-known manner, to obtain predictable results is sufficient to determine an invention obvious over such combination (see KSR International Co. v. Teleflex Inc. (KSR), 550 U.S.,82 USPQ2d 1385 (2007) & MPEP 2143). In the instant case, Melanson evidently discloses adjusting the clock frequency. Satoh is merely relied upon to illustrate the functionality of training a machine learning model in the same or similar context. Since both adjusting the clock frequency, as well as training a machine learning model are implemented through well-known computer technologies in the same or similar context, combining their features as outlined above using such well-known computer technologies (i.e., conventional software/hardware configurations), would be reasonable, according to one of ordinary skill in the art. Moreover, since the elements disclosed by Melanson, as well as Satoh would function in the same manner in combination as they do in their separate embodiments, it is concluded that their resulting combination would be predictable. Accordingly, the claimed subject matter is obvious over Melanson / Satoh.
Claims 11, 18 are rejected under 35 U.S.C. 103 as being unpatentable over Melanson et al (US 2015/0372681), in view of Satoh et al (US 2021/0329164), in further view of Jaisimha et al (US 2009/0143035).
Regarding Claims 11, 18: Melanson, Satoh discloses the limitations of Claims 7, 13. Melanson, Satoh does not disclose, however, Jaisimha discloses: wherein the processor or the machine learning model is to
provide a confidence level associated with the prediction of the frequency or the frequency adjustment. {see at least [0065]-[0075] prediction confidence level}
It would have been obvious to one of ordinary skill in the art, at the time of filing, to modify Melanson, Satoh to include the elements of Jaisimha. One would have been motivated to do so, in order to assess probability of the adjustment outcome. Furthermore, the Supreme Court has supported that combining well known prior art elements, in a well-known manner, to obtain predictable results is sufficient to determine an invention obvious over such combination (see KSR International Co. v. Teleflex Inc. (KSR), 550 U.S.,82 USPQ2d 1385 (2007) & MPEP 2143). In the instant case, Melanson, Satoh evidently discloses adjusting the clock frequency. Jaisimha is merely relied upon to illustrate the functionality of a prediction confidence level in the same or similar context. Since both adjusting the clock frequency, as well as prediction confidence level are implemented through well-known computer technologies in the same or similar context, combining their features as outlined above using such well-known computer technologies (i.e., conventional software/hardware configurations), would be reasonable, according to one of ordinary skill in the art. Moreover, since the elements disclosed by Melanson, Satoh, as well as Jaisimha would function in the same manner in combination as they do in their separate embodiments, it is concluded that their resulting combination would be predictable. Accordingly, the claimed subject matter is obvious over Melanson, Satoh / Jaisimha.
The prior art made of record and not relied upon which, however, is considered pertinent to applicant's disclosure:
US 20230009804 A1 Ayshford; Robbert J. et al. MACHINE-LEARNING TECHNIQUES FOR GENERATING ENTITY INSTRUCTIONS A method for training and using a machine-learning model to determine an execution date for an instruction and to determine an associated action item. A machine-learning model can be trained by receiving entity data that includes historical prescription data, by generating training data by labeling data in the entity data, and by training the machine-learning model by mapping the labeled data to possible predictions for subsequent prescription executions for the entity. Data, which includes at least a prescription and a previous execution date can be received. A subsequent execution date and an associated action item can be determined. A prescription can be executed on the subsequent execution date. The action item can be executed before the subsequent execution date.
US 20240163000 A1 AGARWAL; Anshu et al. DEVICES AND METHODS FOR ENHANCED TIME SYNCHRONIZATION The present disclosure relates to a device including a processor configured to: detect a failed reception of time synchronization information at a follower device, wherein the time synchronization information provides an update of a clock of the follower device for synchronization to a clock of a leader device; determine whether a clock drift between the clock of the follower device and the clock of the leader device is less than a predefined drift threshold; and in the case that the clock drift is less than the predefined drift threshold, instruct an update of the clock of the follower device based on time synchronization information previously received at the follower device.
US 20060171496 A1 Nakamuta; Koji et al. Digital PLL circuit A DPLL circuit is provided for making it possible to inhibit an initial frequency offset during holdover. The DPLL circuit includes a slave oscillator for generating a frequency signal corresponding to the size of a control signal value; a phase difference detection circuit for detecting the difference in phase between the output of said slave oscillator and the inputted reference clock, and outputting a digital signal of the prescribed number of bits corresponding to said detected phase difference; and a holdover unit for generating a correction value based on the output of said phase difference detection circuit, wherein when the holdover is detected, said holdover unit periodically adds the correction value to the output of said phase difference detection circuit to obtain a control value for said slave oscillator.
US 20230077631 A1 BIEDERMAN; Daniel Christian et al. TIME DOMAIN MONITORING AND ADJUSTMENT BY A NETWORK INTERFACE DEVICE Examples described herein relate to a network interface device that includes a host interface; a network interface; and circuitry to: receive time information of a device that executes a service and based on the time information being outside of a permitted jitter range for the service, perform one or more actions to cause execution of the service on a device that operates based on a clock signal within a permitted jitter range.
US 20230199450 A1 Tam; Joyce et al. Autonomous Vehicle Communication Gateway Architecture A gateway processor coordinates communication among an autonomous vehicle components boundary domain, a vehicle boundary domain, and an oversight server. The gateway processor receives a message from the oversight server. The gateway processor determines a priority level, a domain tag data, and destination data associated with the message. The priority level indicates a scheduling requirement associated with the message. The domain tag data indicates that the message is associated with a particular domain from among the autonomous vehicle components boundary domain, the vehicle components boundary domain, or the security domain. The destination data indicates that the message is designated to a particular component within the particular domain. In response, the gateway processor schedules the message to be transmitted to the particular domain. The gateway processor routes the message to the particular component.
US 20240224205 A1 Machireddy; Ramana Reddy TIME SYNCHRONIZATION OVER CLOUD RADIO ACCESS NETWORKS A method, a system, and a computer program product for performing clock synchronization in a wireless communication system. One or more communication parameters are received from one or more communication devices communicating in a wireless communication system. Based on the received one or more communication parameters, one or more synchronization parameters are determined for each of the one or more communication devices. The determined one or more synchronization parameters are provided to each of the one or more communication devices, and one or more communication devices are synchronized using provided one or more synchronization parameters.
US 20150092796 A1 Aweya; James METHOD AND DEVICES FOR TIME AND FREQUENCY SYNCHRONIZATION This invention relates to methods and devices for time and frequency synchronization, especially over packet networks using, for example, the IEEE 1588 Precision Time Protocol (PTP). Timing protocol messages are exposed to artifacts in the network such as packet delay variations (PDV) or packet losses. Embodiments of the invention provide a recursive least squares mechanism for clock offset and skew estimation. A major potential advantage of such estimation is that it does not require knowledge of the statistics of the measurement noise and process noise. An implementation using a digital phase locked loop based on direct digital synthesis to provide both time and frequency signals for use at the slave (time client) is also provided.
US 20160099221 A1 CHIANG; YUNG-PING et al. SEMICONDUCTOR STRUCTURE AND MANUFACTURING METHOD THEREOF A semiconductor structure includes a semiconductive substrate, a post passivation interconnect (PPI) and a polymer layer. The PPI is disposed above the semiconductive substrate and includes a landing area for receiving a conductor. The polymer layer is on the PPI, wherein the conductor is necking a turning point so as to include an oval portion being substantially surrounded by the polymer layer, and the oval portion of the conductor is disposed on the landing area of the PPI.
US 20170214516 A1 Rivaud; Daniel et al. SYSTEM AND METHOD FOR MANAGING HOLDOVER A system for managing holdover. The system may include a local oscillator device. The system may include a phase locked loop (PLL) device coupled to the local oscillator device and a reference clock source. The PLL device may obtain a reference clock signal from the reference clock source to produce an extracted clock signal. The system may include a drift monitoring device coupled to the local oscillator device and the PLL device. The drift monitoring device may determine an amount of oscillator drift within the local oscillator device using the extracted clock signal and an oscillator signal from the local oscillator device. The system may include a drift compensation device coupled to the drift monitoring device and the PLL device. The drift compensation device may transmit a drift compensation signal to the PLL device based on the amount of oscillator drift.
US 20240056795 A1 NAIK; Gaurang et al. MACHINE LEARNING FRAMEWORK FOR WIRELESS LOCAL AREA NETWORKS (WLANs) An apparatus has a memory and one or more processors coupled to the memory. The processor(s) is configured to transmit a first message indicating a first machine learning capability of the first wireless device. The processor(s) is also configured to receive, from a second wireless device, a second message indicating a second machine learning capability of the second wireless device. The processor(s) is further configured to communicate information associated with a machine learning model for use between the first wireless device and the second wireless device based at least in part on the second machine learning capability and the first machine learning capability. The processor(s) is also configured to communicate with the second wireless device based at least in part on the machine learning model.
US 20220337683 A1 BIEDERMAN; Daniel Christian et al. MULTIPLE TIME DOMAIN NETWORK DEVICE TRANSLATION Examples described herein relate to a network interface device that includes circuitry to determine a target time domain in which to translate a time stamp associated with a workload and identify the target time domain to cause translation of the time stamp associated with the workload to the target time domain. In some examples, the network interface device stores time domain translation parameters of time stamps from a first time domain to one or more time domains and the network interface device translates the time stamp from the first time domain to the one or more time domains. In some examples, the network interface device comprises circuitry to store time domain translation parameters of time stamps from a first time domain to one or more time domains and the server is to perform translation of the time stamp from the first time domain to the one or more time domains based on the time domain translation parameters.
US 20210201178 A1 Fanini; Otto et al. MULTI-PHASE CHARACTERIZATION USING DATA FUSION FROM MULTIVARIATE SENSORS A method for determining a wellbore fluid phase includes receiving, from a first sensor, first fluid data for a fluid flowing through a wellbore. The method also includes receiving, from a second sensor, second fluid data for the fluid. The method further includes determining, based at least in part on the first fluid data, a first fluid property. The method also includes determining, based at least in part on the second fluid data, a second fluid property. The method further includes determining a relationship between the first fluid property and the second fluid property, the relationship based at least in part on respective evaluations of the first fluid property with respect to a first threshold and the second fluid property with respect to a second threshold. The method includes determining, based at least in part on the relationship, a phase of the fluid.
US 20190012278 A1 Sindhu; Pradeep et al. DATA PROCESSING UNIT FOR COMPUTE NODES AND STORAGE NODES A new processing architecture is described in which a data processing unit (DPU) is utilized within a device. Unlike conventional compute models that are centered around a central processing unit (CPU), example implementations described herein leverage a DPU that is specially designed and optimized for a data-centric computing model in which the data processing tasks are centered around, and the primary responsibility of, the DPU. For example, various data processing tasks, such as networking, security, and storage, as well as related work acceleration, distribution and scheduling, and other such tasks are the domain of the DPU. The DPU may be viewed as a highly programmable, high-performance input/output (I/O) and data-processing hub designed to aggregate and process network and storage I/O to and from multiple other components and/or devices. This frees resources of the CPU, if present, for computing-intensive tasks.
US 20230246723 A1 Tzeng; Shrjie et al. TIME SYNCHRONIZATION BASED ON LOOKUP TABLE Described herein are systems and methods for implementing a look up table by a network node, and performing or supporting time synchronization based on the look up table. In one aspect, a network node may receive a packet. The network node can identify a few number of bits in the packet, and determine one or more actions or functions corresponding to the few number of bits via the look up table. In addition, the network node can execute or perform the determined one or more actions to support time synchronization.
US 20240223603 A1 Lesi; Vuk et al. Physics-Aware Detector for Protocol Spoofing Attacks in Time Sensitive Networks Techniques include receiving a message with time information from a clock leader by a clock follower in a time-synchronized network (TSN), the time information to synchronize a clock to a network time for the TSN, retrieving an actual time offset value for the message, the actual time offset value to comprise a value between an actual sending time and an actual receiving time of the message, retrieving an estimated time offset value for the message, the estimated time offset value to comprise a value between an estimated sending time and an estimated receiving time of the message, the estimated time offset value generated using a physics-aware model of the TSN and a clock adjustment value for the clock based on the time information, and determining whether the time information for the message was modified to cause the clock to desynchronize based on difference information. Other embodiments are described and claimed.
US 5933059 A Asokan; Ramanathan Method and apparatus for controlling frequency synchronization in a radio telephone A method and apparatus for controlling frequency synchronization in a frequency correction feedback loop of a radio telephone. A processor in a frequency update controller ascertains increment/decrement values pro-proportionally related to confidence levels representing a ratio that a likelihood probability of estimated offset frequecies of an input carrier signal are accurate in proportion to a likelihood probability that the estimated offset frequencies are inaccurate. The processor adds or subtracts the value to a counter depending on its sign. When the counter reaches a certain predefined positive number, the counter is decremented by this number and the processor increases the frequency of a reference oscillator frequency. When the counter reaches a certain predefined negative number, the counter is incremented by the absolute value of the negative number and the processor decreases the frequency of the reference oscillator frequency.
US 5864315 A Welles, II; Kenneth Brakeley et al. Very low power high accuracy time and frequency circuits in GPS based tracking units A direct sequence spread spectrum signal processing system permits the receiver to be turned off during most of the acquisition phase of reception to significantly reduce the on time of the associated receiver front end. Power requirements are further reduced by use of very low power high accuracy time and frequency circuits in GPS based tracking units. The microprocessor based GPS tracking system is shut down almost all the time, using extremely little electrical power, and is powered up for very short periods of time at scheduled intervals by an extremely low power clock circuit with accuracy that varies with temperature. Each time the microprocessor is powered up, system temperature is recorded in memory. At times when the microprocessor is powered up, the GPS system is accessed and the GPS standard time is read. The difference between the low power clock circuit based time and the GPS based time is correlated with the recorded temperature history. A correction table, built from this data, provides a temperature history based correction to the low power clock based circuit without reference to the GPS system, and provides a highly accurate time standard. An additional table constructed in the microprocessor temperature compensates the local frequency standard used for frequency synthesis in satellite communication channels. This table is constructed by measuring offset between the calculated and actual synthesized frequency required to lock onto the satellite transmitted reference (pilot tone), and correlating this measured offset with the system ambient temperature.
US 20190354489 A1 Gupta; Lokesh M. et al. SELECTING ONE OF MULTIPLE CACHE EVICTION ALGORITHMS TO USE TO EVICT A TRACK FROM THE CACHE BY TRAINING A MACHINE LEARNING MODULE Provided are a computer program product, system, and method for using a machine learning module to select one of multiple cache eviction algorithms to use to evict a track from the cache. A first cache eviction algorithm determines tracks to evict from the cache. A second cache eviction algorithm determines tracks to evict from the cache, wherein the first and second cache eviction algorithms use different eviction schemes. At least one machine learning module is executed to produce output indicating one of the first cache eviction algorithm and the second cache eviction algorithm to use to select a track to evict from the cache. A track is evicted that is selected by one of the first and second cache eviction algorithms indicated in the output from the at least one machine learning module.
US 20210326711 A1 XI; Jinwen et al. DUAL-MOMENTUM GRADIENT OPTIMIZATION WITH REDUCED MEMORY REQUIREMENTS Systems and methods related to dual-momentum gradient optimization with reduced memory requirements are described. An example method in a system comprising a gradient optimizer and a memory configured to store momentum values associated with a neural network model comprising L layers is described. The method includes retrieving from the memory a first set of momentum values and a second set of momentum values, corresponding to a layer of the neural network model, having a selected storage format. The method further includes converting the first set of momentum values to a third set of momentum values having a training format associated with the gradient optimizer and converting the second set of momentum values to a fourth set of momentum values having a training format associated with the gradient optimizer. The method further includes performing gradient optimization using the third set of momentum values and the fourth set of momentum values.
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