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 .
Claim Interpretation
The following is a quotation of 35 U.S.C. 112(f):
(f) Element in Claim for a Combination. – An element in a claim for a combination may be expressed as a means or step for performing a specified function without the recital of structure, material, or acts in support thereof, and such claim shall be construed to cover the corresponding structure, material, or acts described in the specification and equivalents thereof.
The following is a quotation of pre-AIA 35 U.S.C. 112, sixth paragraph:
An element in a claim for a combination may be expressed as a means or step for performing a specified function without the recital of structure, material, or acts in support thereof, and such claim shall be construed to cover the corresponding structure, material, or acts described in the specification and equivalents thereof.
The claims in this application are given their broadest reasonable interpretation using the plain meaning of the claim language in light of the specification as it would be understood by one of ordinary skill in the art. The broadest reasonable interpretation of a claim element (also commonly referred to as a claim limitation) is limited by the description in the specification when 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, is invoked.
As explained in MPEP § 2181, subsection I, claim limitations that meet the following three-prong test will be interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph:
(A) the claim limitation uses the term “means” or “step” or a term used as a substitute for “means” that is a generic placeholder (also called a nonce term or a non-structural term having no specific structural meaning) for performing the claimed function;
(B) the term “means” or “step” or the generic placeholder is modified by functional language, typically, but not always linked by the transition word “for” (e.g., “means for”) or another linking word or phrase, such as “configured to” or “so that”; and
(C) the term “means” or “step” or the generic placeholder is not modified by sufficient structure, material, or acts for performing the claimed function.
Use of the word “means” (or “step”) in a claim with functional language creates a rebuttable presumption that the claim limitation is to be treated in accordance with 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph. The presumption that the claim limitation is interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, is rebutted when the claim limitation recites sufficient structure, material, or acts to entirely perform the recited function.
Absence of the word “means” (or “step”) in a claim creates a rebuttable presumption that the claim limitation is not to be treated in accordance with 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph. The presumption that the claim limitation is not interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, is rebutted when the claim limitation recites function without reciting sufficient structure, material or acts to entirely perform the recited function.
Claim limitations in this application that use the word “means” (or “step”) are being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, except as otherwise indicated in an Office action. Conversely, claim limitations in this application that do not use the word “means” (or “step”) are not being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, except as otherwise indicated in an Office action.
This application includes one or more claim limitations that do not use the word “means,” but are nonetheless being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, because the claim limitation(s) uses a generic placeholder that is coupled with functional language without reciting sufficient structure to perform the recited function and the generic placeholder is not preceded by a structural modifier. Such claim limitation(s) is/are: “a property specifier to specify an accuracy-related property,…” in the 3rd line of the claim 13. The specification discloses that “a property specifier 104…These functions are performed by software, firmware, or a combination of software and firmware. The software and firmware are described in the form of programs, and stored in the ROM or the storage 12. The programs stored in the ROM or the storage 12 are executed by the CPU, and thus performs these functions” in [0047]. Thus, as disclosed in the specification, “a property specifier” is interpreted as a software or a firmware executed by a CPU.
“an equipment configuration determiner to determine a proposed equipment configuration…” The specification discloses that “an equipment configuration determiner…These functions are performed by software, firmware, or a combination of software and firmware. The software and firmware are described in the form of programs, and stored in the ROM or the storage 12. The programs stored in the ROM or the storage 12 are executed by the CPU, and thus performs these functions” in [0047]. Thus, as disclosed in the specification, “an equipment configuration determiner” is interpreted as a software or a firmware executed by a CPU.
Because this/these claim limitation(s) is/are being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, it/they is/are being interpreted to cover the corresponding structure described in the specification as performing the claimed function, and equivalents thereof.
If applicant does not intend to have this/these limitation(s) interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, applicant may: (1) amend the claim limitation(s) to avoid it/them being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph (e.g., by reciting sufficient structure to perform the claimed function); or (2) present a sufficient showing that the claim limitation(s) recite(s) sufficient structure to perform the claimed function so as to avoid it/them being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph.
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 1-13 are rejected under 35 U.S.C. 101 because the claimed invention is directed to non-statutory subject matter. The claim(s) does/do not fall within at least one of the four categories of patent eligible subject matter because
Regarding claim 1,
At Step 2A, Prong 1: The claim recites the following limitations directed to an abstract idea:
“specify an accuracy-related property, based on the current equipment configuration information, the operation history information, and the accuracy achievement information, the accuracy-related property being a property affecting the processing accuracy of the working machine” The limitation is a mental process, reasonable performed in the mind. “specify” is to identify clearly and definitely as defined in Oxford Languages. Thus, a person can specify or identify a property, which is a value, based on other observation or data in mind.
“determine a proposed equipment configuration, based on the current equipment configuration information, the accuracy-related property, and the product information, the proposed equipment configuration being an equipment configuration that satisfies the user request and that is the current equipment configuration with at least one of the current component configuration or the current control program being changed.” The limitation is a mental process, reasonable performed in the mind. “determine” is to decide. Thus, a person can determine or decide something or configuration based on observation or data.
At Step 2, Prong 2:
“processing circuitry to acquire current equipment configuration information indicating a current equipment configuration containing a current component configuration of a working machine and a current control program of the working machine.” The limitation is an example of insignificant extra-solution activity, mere data gathering (e.g., see. MPEP 2106.05(g)).
“acquire operation history information indicating an operation history of the working machine.” The limitation is an example of insignificant extra-solution activity, mere data gathering (e.g., see. MPEP 2106.05(g)).
“acquire accuracy achievement information indicating a processing accuracy achieved by the working machine” The limitation is an example of insignificant extra-solution activity, mere data gathering (e.g., see. MPEP 2106.05(g)).
“acquire a user request for processing accuracy.” The limitation is an example of insignificant extra-solution activity, mere data gathering or selecting a particular data source or type of data to be manipulated (e.g., see. MPEP 2106.05(g)).
“acquire product information indicating at least one of a lineup of components applicable to the working machine or a lineup of control programs applicable to the working machine” The limitation is an example of insignificant extra-solution activity, mere data gathering (e.g., see. MPEP 2106.05(g)).
“output proposed equipment related information that is information related to the proposed equipment configuration.” The limitation is an example of field of use and technological environment without any limitations specifying how to achieve the desired result (e.g., see. MPEP 2106.05(a) I. & II., MPEP 2106.05(h)).
Accordingly, these additional elements do not integrate the abstract idea into a practical application because they do no impose any meaning full limits on practicing the abstract idea. The claim is directed to an abstract idea.
At Step 2B:
The claim does not include additional elements that are sufficient to amount to significantly more than the judicial exception. The claim limitations are recited at a high level of generality and amount to insignificant extra-solution activity. With respect to the monitoring and data entry limitations (addressed as insignificant extra-solution activity above) these steps are also well-understood, routine, or conventional. See MPEP 2106.05(d)(II): receiving or transmitting data over a network; storing and retrieving information in memory; electronic recordkeeping. As discussed above with respect to integration of the abstract idea into a practical application, the additional elements amount to no more than instructions to apply the exception using generic computing or electronic components.
Regarding claim 2,
At Step 2A, Prong 1:
“wherein the processing circuitry selects a first trajectory among trajectories drawn by a traveling member while the working machine is processing an object, the traveling member being included in the working machine.” The limitation is a mental process, reasonable performed in the mind. “select” is to carefully choose as being the best or most suitable as defined in Oxford Languages. Thus, a person can select one among a plurality of options based on other observation or data in mind.
“specifies a first component in the current component configuration, the first component being used when the traveling member draws the first trajectory.” The limitation is a mental process, reasonable performed in the mind. “specify” is to identify clearly and definitely as defined in Oxford Languages. Thus, a person can specify or identify a property, which is a value, based on other observation or data in mind.
“determines, as the proposed equipment configuration, an equipment configuration that is the current equipment configuration with a new component applied in place of the first component, or an equipment configuration that is the current equipment configuration with a new component applied in addition to the first component” The limitation is a mental process, reasonable performed in the mind. “determine” is to decide. Thus, a person can determine or decide something or configuration based on observation or data.
Regarding claim 3,
At Step 2A, Prong 1
“wherein the processing circuitry selects, as the first trajectory based on the current equipment configuration information and the operation history information, a frequently drawn trajectory among the trajectories drawn by the traveling member.” The limitation is a mental process, reasonable performed in the mind. “select” is to carefully choose as being the best or most suitable as defined in Oxford Languages. Thus, a person can select one among a plurality of options based on other observation or data in mind.
Regarding claim 4,
At Step 2A, Prong 1:
“wherein the processing circuitry selects, as the first trajectory, based on the current equipment configuration information and the operation history information, a trajectory that readily causes vibration among the trajectories drawn by the traveling member.” The limitation is a mental process, reasonable performed in the mind. “select” is to carefully choose as being the best or most suitable as defined in Oxford Languages. Thus, a person can select one among a plurality of options based on other observation or data in mind.
Regarding claim 5,
At Step 2A, Prong 1:
“wherein the processing circuitry specifies one or more candidate components corresponding to the first component from the lineup indicated by the product information, and determines, as the new component, a candidate component satisfying the user request, among the one or more candidate components” The limitation is a mental process, reasonable performed in the mind. “specify” is to identify clearly and definitely as defined in Oxford Languages. Thus, a person can specify or identify a property, which is a value, based on other observation or data in mind. “determine” is to decide. Thus, a person can determine or decide something or configuration based on observation or data.
Regarding claim 6,
At Step 2A, Prong 1:
“wherein the processing circuitry specifies a frequency that readily causes vibration among frequencies used while the working machine is processing an object, and determines, as the proposed equipment configuration, an equipment configuration containing a control program in which the specified frequency is not used.” The limitation is a mental process, reasonable performed in the mind. “specify” is to identify clearly and definitely as defined in Oxford Languages. Thus, a person can specify or identify a property, which is a value, based on other observation or data in mind. “determine” is to decide. Thus, a person can determine or decide something or configuration based on observation or data.
Regarding claim 7
At Step 2A, Prong 1:
“specifies, as the parameter value indicating the accuracy-related property of the working machine, a parameter value corresponding to a feature quantity that is minimum in the calculated deviation among a plurality of the feature quantities indicated by the accuracy database information.” The limitation is a mental process, reasonable performed in the mind. “specify” is to identify clearly and definitely as defined in Oxford Languages. Thus, a person can specify or identify a property, which is a value, based on other observation or data in mind.
At Step 2A, Prong 2:
“wherein the processing circuitry, based on accuracy database information containing at least one of (i) simulation information indicating, for each of parameter values each indicating the accuracy-related property, a result of simulation of a feature quantity of a vibration characteristic or processing accuracy or (ii) actual-device experiment information indicating, for each of the parameter values, an experimental result of an experiment for a feature quantity of a vibration characteristic or processing accuracy that is performed using an actual device, calculates, for each of the parameter values, a deviation of the feature quantity indicated by the accuracy database information from the feature quantity indicated by the accuracy achievement information.” The limitation is an example of insignificant extra-solution activity, mere data gathering. The caveat of the limitation is a description of the nature of the data itself and at best a general link to a particular field of use (e.g., see MPEP 2106.05(h) (vi. Electric Power example). The database itself is generically recited at a high level of generality.
The claim does not include additional elements that are sufficient to amount to significantly more than the judicial exception. As discussed above with respect to integration of the abstract idea into a practical application, the additional elements amount to no more than mere instructions to apply the exception - using generic computing components - and general linking of the abstract idea to a particular technological environment or field of use. With respect to the monitoring and data entry limitations (addressed as insignificant extra-solution activity above) these steps are also well-understood, routine, or conventional. See MPEP 2106.05(d)(II): receiving or transmitting data over a network; storing and retrieving information in memory; electronic recordkeeping.
Regarding claim 8,
At Step 2A, Prong 1:
“wherein the processing circuitry calculates, for each of parameter values each indicating the accuracy-related property, using a trained model that is established for the parameter value and that outputs accuracy prediction information in response to input of the operation history information, a deviation of a feature quantity indicated by the accuracy prediction information from a feature quantity indicated by the accuracy achievement information” The claim limitation is a mathematical concept. The limitation recites calculating a deviation for each parameter, which is a measure to quantify the disparity between an observed value of a variable and another designated value, frequently the mean of that variable.
“specifies, as the parameter value indicating the accuracy-related property of the working machine, a parameter value that is minimum in the calculated deviation among the parameter values.” The limitation is a mental process, reasonable performed in the mind. “specify” is to identify clearly and definitely as defined in Oxford Languages. Thus, a person can specify or identify a property, which is a value, based on other observation or data in mind.
Regarding claim 9,
At Step 2A, Prong 1:
“calculates a deviation of a feature quantity indicated by the accuracy prediction information from a feature quantity indicated by the accuracy achievement information” The claim limitation is a mathematical concept. The limitation recites calculating a deviation for each parameter, which is a measure to quantify the disparity between an observed value of a variable and another designated value, frequently the mean of that variable.
“specifies, as the parameter value indicating the accuracy-related property of the working machine, a parameter value provided when the calculated deviation reaches the allowable deviation or smaller.” The limitation is a mental process, reasonable performed in the mind. “specify” is to identify clearly and definitely as defined in Oxford Languages. Thus, a person can specify or identify a property, which is a value, based on other observation or data in mind.
At Step 2A, Prong 2:
“wherein the processing circuitry acquires accuracy prediction information, through simulation that outputs the accuracy prediction information in response to input of a parameter value indicating the accuracy-related property and the operation history information” “repeats processing of acquiring the accuracy prediction information through the simulation while updating the parameter value with an optimizer until the calculated deviation reaches an allowable deviation or smaller” The limitation is an example of insignificant extra-solution activity, mere data gathering (e.g., see. MPEP 2106.05(g)).
“sets a standard parameter value as an initial value of the parameter value” The limitation is an example of an “apply it” type limitation (see MPEP 2106.05(f)(1) – the claim recites only the idea of a solution or outcome without reciting details on how it is accomplished.)
Accordingly, these additional elements do not integrate the abstract idea into a practical application because they do no impose any meaning full limits on practicing the abstract idea. The claim is directed to an abstract idea.
At Step 2B:
The claim does not include additional elements that are sufficient to amount to significantly more than the judicial exception. The claim limitations are recited at a high level of generality and amount to insignificant extra-solution activity. With respect to the monitoring and data entry limitations (addressed as insignificant extra-solution activity above) these steps are also well-understood, routine, or conventional. See MPEP 2106.05(d)(II): receiving or transmitting data over a network; storing and retrieving information in memory; electronic recordkeeping. As discussed above with respect to integration of the abstract idea into a practical application, the additional elements amount to no more than instructions to apply the exception using generic computing or electronic components.
Regarding claim 10,
At Step 2A, Prong 1:
“calculates a deviation of a feature quantity indicated by the accuracy prediction information from a feature quantity indicated by the accuracy achievement information” The claim limitation is a mathematical concept. The limitation recites calculating a deviation for each parameter, which is a measure to quantify the disparity between an observed value of a variable and another designated value, frequently the mean of that variable.
“specifies, as the parameter value indicating the accuracy-related property of the working machine, a parameter value provided when the calculated deviation reaches the allowable deviation or smaller” The limitation is a mental process, reasonable performed in the mind. “specify” is to identify clearly and definitely as defined in Oxford Languages. Thus, a person can specify or identify a property, which is a value, based on other observation or data in mind.
At Step 2A, Prong 2:
“acquires accuracy prediction information, using a trained model that outputs the accuracy prediction information in response to input of a parameter value indicating the accuracy-related property and the operation history information” “repeats processing of acquiring the accuracy prediction information using the trained model while updating the parameter value with an optimizer until the calculated deviation reaches an allowable deviation or smaller” The limitation is an example of insignificant extra-solution activity, mere data gathering (e.g., see. MPEP 2106.05(g)).
“sets a standard parameter value as an initial value of the parameter value” The limitation is an example of an “apply it” type limitation (see MPEP 2106.05(f)(1) – the claim recites only the idea of a solution or outcome without reciting details on how it is accomplished.)
Accordingly, these additional elements do not integrate the abstract idea into a practical application because they do no impose any meaning full limits on practicing the abstract idea. The claim is directed to an abstract idea.
At Step 2B:
The claim does not include additional elements that are sufficient to amount to significantly more than the judicial exception. The claim limitations are recited at a high level of generality and amount to insignificant extra-solution activity. With respect to the monitoring and data entry limitations (addressed as insignificant extra-solution activity above) these steps are also well-understood, routine, or conventional. See MPEP 2106.05(d)(II): receiving or transmitting data over a network; storing and retrieving information in memory; electronic recordkeeping. As discussed above with respect to integration of the abstract idea into a practical application, the additional elements amount to no more than instructions to apply the exception using generic computing or electronic components.
Regarding claim 11,
The claim limitation “the proposal device according to claim 1” is rejected under 35 U.S.C. § 101, as discussed above. The claim 11 further recites the limitation “a working machine; and a display device, wherein the working machine includes a storage to store the current equipment configuration information and the operation history information, and the display device includes a display to display the proposed equipment related information output from the proposal device.”
At Step 2A, Prong 2:
“a working machine; and a display device, wherein the working machine includes a storage to store the current equipment configuration information and the operation history information” The limitation is recited at a high level of generality, and amount to no more than generic computing elements.
“the display device includes a display to display the proposed equipment related information output from the proposal device” The limitation is an example of field of use and technological environment without any limitations specifying how to achieve the desired result (e.g., see. MPEP 2106.05(a) I. & II., MPEP 2106.05(h)).
Accordingly, these additional elements do not integrate the abstract idea into a practical application because they do no impose any meaning full limits on practicing the abstract idea. The claim is directed to an abstract idea.
At Step 2B:
The claim does not include additional elements that are sufficient to amount to significantly more than the judicial exception. The claim limitations are recited at a high level of generality and amount to insignificant extra-solution activity. A claim reciting a generic computer component performing a generic computer function is necessarily ineligible (see MPEP 2106.05(d) II.). With respect to the monitoring and data entry limitations (addressed as insignificant extra-solution activity above) these steps are also well-understood, routine, or conventional. See MPEP 2106.05(d)(II): receiving or transmitting data over a network; storing and retrieving information in memory; electronic recordkeeping.
Regarding claim 12,
At Step 2A, Prong 1:
“specifying an accuracy-related property, based on current equipment configuration information, operation history information, and accuracy achievement information, the accuracy-related property being a property affecting a processing accuracy of a working machine, the current equipment configuration information indicating a current equipment configuration containing a current component configuration of the working machine and a current control program of the working machine, the operation history information indicating an operation history of the working machine, the accuracy achievement information indicating a processing accuracy achieved by the working machine” The limitation is a mental process, reasonable performed in the mind. “specify” is to identify clearly and definitely as defined in Oxford Languages. Thus, a person can specify or identify a property, which is a value, based on other observation or data in mind.
“determining a proposed equipment configuration, based on the current equipment configuration information, the accuracy-related property, and product information, the proposed equipment configuration being an equipment configuration that satisfies the user request and that is the current equipment configuration with at least one of the current component configuration or the current control program being changed, the product information indicating at least one of a lineup of components applicable to the working machine or a lineup of control programs applicable to the working machine” The limitation is a mental process, reasonable performed in the mind. “determine” is to decide. Thus, a person can determine or decide something or configuration based on observation or data.
At Step 2A, Prong 2:
“presenting proposed equipment related information that is information related to the proposed equipment configuration” The limitation is an example of field of use and technological environment without any limitations specifying how to achieve the desired result (e.g., see. MPEP 2106.05(a) I. & II., MPEP 2106.05(h)).
Accordingly, these additional elements do not integrate the abstract idea into a practical application because they do no impose any meaning full limits on practicing the abstract idea. The claim is directed to an abstract idea.
At Step 2B:
The claim does not include additional elements that are sufficient to amount to significantly more than the judicial exception. The claim limitations are recited at a high level of generality and amount to insignificant extra-solution activity. With respect to the monitoring and data entry limitations (addressed as insignificant extra-solution activity above) these steps are also well-understood, routine, or conventional. See MPEP 2106.05(d)(II): receiving or transmitting data over a network; storing and retrieving information in memory; electronic recordkeeping.
Regarding claim 13,
At Step 2A, Prong 1:
“a property specifier to specify an accuracy-related property, based on current equipment configuration information, operation history information, and accuracy achievement information, the accuracy-related property being a property affecting a processing accuracy of a working machine, the current equipment configuration information indicating a current equipment configuration containing a current component configuration of the working machine and a current control program of the working machine, the operation history information indicating an operation history of the working machine, the accuracy achievement information indicating a processing accuracy achieved by the working machine” The limitation is a mental process, reasonable performed in the mind. “specify” is to identify clearly and definitely as defined in Oxford Languages. Thus, a person can specify or identify a property, which is a value, based on other observation or data in mind.
“an equipment configuration determiner to determine a proposed equipment configuration, based on the current equipment configuration information, the accuracy-related property, and product information, the proposed equipment configuration being an equipment configuration that satisfies the user request and that is the current equipment configuration with at least one of the current component configuration or the current control program being changed, the product information indicating at least one of a lineup of components applicable to the working machine or a lineup of control programs applicable to the working machine.” The limitation is a mental process, reasonable performed in the mind. “determine” is to decide. Thus, a person can determine or decide something or configuration based on observation or data.
At Step 2A, Prong 2:
“a non-transitory computer-readable recording medium storing a program configured to cause a computer to function” The limitation is recited at a high level of generality, and amount to no more than generic computing elements.
Accordingly, these additional elements do not integrate the abstract idea into a practical application because they do no impose any meaning full limits on practicing the abstract idea. The claim is directed to an abstract idea.
At Step 2B:
The claim does not include additional elements that are sufficient to amount to significantly more than the judicial exception. The claim limitations are recited at a high level of generality. A claim reciting a generic computer component performing a generic computer function is necessarily ineligible (see MPEP 2106.05(d) II.).
Claim Rejections - 35 USC § 102
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.
(a)(2) the claimed invention was described in a patent issued under section 151, or in an application for patent published or deemed published under section 122(b), in which the patent or application, as the case may be, names another inventor and was effectively filed before the effective filing date of the claimed invention.
Claim(s) 1, 8-10, 12, and 13 is/are rejected under 35 U.S.C. 102(a)(2) as being anticipated by Assem Aly Salama et al. (United States Patent Application Publication US 2019/0050751), hereinafter Assem.
Regarding claim 1, Assem teaches a proposal device comprising: processing circuitry to acquire current equipment configuration information indicating a current equipment configuration containing a current component configuration of a working machine and a current control program of the working machine ([0017] “a "configuration" generally refers to the manner in which a system is configured to train a machine learning model with certain accuracy and time. A configuration may involve one or more files. A configuration may include but not limited to system settings such as system name, hardware architecture, number of CPUs (central processing units), RAM (random-access memory) size, storage capacity, operating system, and network configurations. In addition to these system settings, a configuration may also include dependent variables necessary to train the machine learning model.” [0018] “configuration could include configuring one or more virtual machines in terms of, e.g., number of CPUs, size of RAM, storage capacity, operating system, hardware architecture, network settings etc. Configuration may also include tweaking the existing hardware of system in a specific setting to train a machine learning model.” [0039] “method for use in managing a system comprising one or more computers”),
acquire operation history information indicating an operation history of the working machine ([0020] “Configuration generation module 140 looks at the available hardware resources 120…”“Configuration generation module 140 may use virtualization tools to create multiple virtualized configurations 150 based on various settings of number of CPUs, storage capacity and operating system for given hardware resources.” [0026] “If an optimal configuration file already exists for the given set of inputs 210 (YES branch of step 220), then the process goes to step 230, where the configuration implementation module 160 configures the system according to the optimal configuration.” Configuration file that already exists is a previous configuration, which is a history of the configuration. Furthermore, the configuration is setting to operate the hardware and software of the computer or device.),
acquire accuracy achievement information indicating a processing accuracy achieved by the working machine, specify an accuracy-related property, based on the current equipment configuration information, the operation history information, and the accuracy achievement information, the accuracy-related property being a property affecting the processing accuracy of the working machine ([0016] “its accuracy required by application/user,” [0028] “the accuracy reached are recorded.” [0029] “Step 270 determines whether configuration 250 satisfies the accuracy constraints 112 and time constraints 113 provided in step 210.” [0031] “FIG. 3 could be used to determine which machine learning model is optimal in terms of the required accuracy and time constraint when deployed on given hardware resources.” The accuracy constraint of the model for the configuration of the computer or device to be satisfied is interpreted as accuracy achievement information. Furthermore, the accuracy constraint of the models considers hardware resources, “the optimal configuration file that already exists for the given set of inputs”, and the accuracy constraint to satisfy the accuracy required by application/user.),
acquire a user request for processing accuracy ([0016] “its accuracy required by application/user”),
acquire product information indicating at least one of a lineup of components applicable to the working machine or a lineup of control programs applicable to the working machine ([0021] “Configuration generation module 140 may use virtualization tools to create multiple virtualized configurations 150 based on various settings of number of CPUs, storage capacity and operating system for given hardware resources.” Based on the constraints and models, the hardware resources and software resources are configured, which is to acquire information regarding available or applicable resources of the computer.),
determine a proposed equipment configuration, based on the current equipment configuration information, the accuracy-related property, and the product information, the proposed equipment configuration being an equipment configuration that satisfies the user request and that is the current equipment configuration with at least one of the current component configuration or the current control program being changed ([0029] “Step 270 determines whether configuration 250 satisfies the accuracy constraints 112 and time constraints 113 provided in step 210…If the constraints are satisfied (YES branch of step 270), the configuration is deemed to be an optimal configuration 280 and is saved to the configuration database 290 with a unique name.” Based on the determined optimal configuration that is determined based on hardware resources, “the optimal configuration file that already exists for the given set of inputs”, and the accuracy constraint to satisfy the accuracy required by application/user, the optimal configuration is to configure the computer.), and
output proposed equipment related information that is information related to the proposed equipment configuration ([0029] “If the constraints are satisfied (YES branch of step 270), the configuration is deemed to be an optimal configuration 280 and is saved to the configuration database 290 with a unique name.”).
Regarding claim 8, Assem teaches wherein the processing circuitry calculates, for each of parameter values each indicating the accuracy-related property, using a trained model that is established for the parameter value and that outputs accuracy prediction information in response to input of the operation history information, a deviation of a feature quantity indicated by the accuracy prediction information from a feature quantity indicated by the accuracy achievement information, and specifies, as the parameter value indicating the accuracy-related property of the working machine, a parameter value that is minimum in the calculated deviation among the parameter values ([0031] “FIG. 3 could be used to determine which machine learning model is optimal in terms of the required accuracy and time constraint when deployed on given hardware resources.” [0032] “A denotes the required accuracy of the ML model for the business problem (e.g., 113 in FIG. 1). m, denotes an arbitrary given machine learning (ML) model (e.g., 250 in FIG. 2) that needs to be trained and whose computational complexity is O(m,). t, denotes the time spent by m, with accuracy of a,. HW, denotes the hardware settings such that when a given hardware is configured with HWi, it minimizes the t, of ML model m, when deployed on HW,. M={m1, m2, m3…} denotes all the ML models that can be applied to identify optimal HW'. M' is a list of selected ML models to solve the problem.” [0035] “In step 330, t, and a, are estimated based on HW,. Step 340 checks to whether that the time and accuracy constraints are met: is t,<T and a,2:A? If so, the procedure performs step 350, in which m, is appended into M', before proceeding to step 360. If not, the procedure skips step 350 and proceeds directly to step 360.”).
Regarding claim 9, Assem teaches wherein the processing circuitry acquires accuracy prediction information, through simulation that outputs the accuracy prediction information in response to input of a parameter value indicating the accuracy-related property and the operation history information, calculates a deviation of a feature quantity indicated by the accuracy prediction information from a feature quantity indicated by the accuracy achievement information, sets a standard parameter value as an initial value of the parameter value, repeats processing of acquiring the accuracy prediction information through the simulation while updating the parameter value with an optimizer until the calculated deviation reaches an allowable deviation or smaller, and specifies, as the parameter value indicating the accuracy-related property of the working machine, a parameter value provided when the calculated deviation reaches the allowable deviation or smaller ([0031] “FIG. 3 could be used to determine which machine learning model is optimal in terms of the required accuracy and time constraint when deployed on given hardware resources.” [0032] “A denotes the required accuracy of the ML model for the business problem (e.g., 113 in FIG. 1). m, denotes an arbitrary given machine learning (ML) model (e.g., 250 in FIG. 2) that needs to be trained and whose computational complexity is O(m,). t, denotes the time spent by m, with accuracy of a,. HW, denotes the hardware settings such that when a given hardware is configured with HWi, it minimizes the t, of ML model m, when deployed on HW,. M={m1, m2, m3…} denotes all the ML models that can be applied to identify optimal HW'. M' is a list of selected ML models to solve the problem.” [0035] “In step 330, t, and a, are estimated based on HW,. Step 340 checks to whether that the time and accuracy constraints are met: is t,<T and a,2:A? If so, the procedure performs step 350, in which m, is appended into M', before proceeding to step 360. If not, the procedure skips step 350 and proceeds directly to step 360.”).
Regarding claim 10, Assem teaches wherein the processing circuitry acquires accuracy prediction information, using a trained model that outputs the accuracy prediction information in response to input of a parameter value indicating the accuracy-related property and the operation history information, calculates a deviation of a feature quantity indicated by the accuracy prediction information from a feature quantity indicated by the accuracy achievement information, sets a standard parameter value as an initial value of the parameter value, repeats processing of acquiring the accuracy prediction information using the trained model while updating the parameter value with an optimizer until the calculated deviation reaches an allowable deviation or smaller, and specifies, as the parameter value indicating the accuracy-related property of the working machine, a parameter value provided when the calculated deviation reaches the allowable deviation or smaller ([0031] “FIG. 3 could be used to determine which machine learning model is optimal in terms of the required accuracy and time constraint when deployed on given hardware resources.” [0032] “A denotes the required accuracy of the ML model for the business problem (e.g., 113 in FIG. 1). m, denotes an arbitrary given machine learning (ML) model (e.g., 250 in FIG. 2) that needs to be trained and whose computational complexity is O(m,). t, denotes the time spent by m, with accuracy of a,. HW, denotes the hardware settings such that when a given hardware is configured with HWi, it minimizes the t, of ML model m, when deployed on HW,. M={m1, m2, m3…} denotes all the ML models that can be applied to identify optimal HW'. M' is a list of selected ML models to solve the problem.” [0035] “In step 330, t, and a, are estimated based on HW,. Step 340 checks to whether that the time and accuracy constraints are met: is t,<T and a,2:A? If so, the procedure performs step 350, in which m, is appended into M', before proceeding to step 360. If not, the procedure skips step 350 and proceeds directly to step 360.”).
Regarding claim 12, Assem teaches a proposal method comprising: specifying an accuracy-related property, based on current equipment configuration information, operation history information, and accuracy achievement information, the accuracy-related property being a property affecting a processing accuracy of a working machine, the current equipment configuration information indicating a current equipment configuration containing a current component configuration of the working machine and a current control program of the working machine, the operation history information indicating an operation history of the working machine, the accuracy achievement information indicating a processing accuracy achieved by the working machine ([0017] “a "configuration" generally refers to the manner in which a system is configured to train a machine learning model with certain accuracy and time. A configuration may involve one or more files. A configuration may include but not limited to system settings such as system name, hardware architecture, number of CPUs (central processing units), RAM (random-access memory) size, storage capacity, operating system, and network configurations. In addition to these system settings, a configuration may also include dependent variables necessary to train the machine learning model.” [0018] “configuration could include configuring one or more virtual machines in terms of, e.g., number of CPUs, size of RAM, storage capacity, operating system, hardware architecture, network settings etc. Configuration may also include tweaking the existing hardware of system in a specific setting to train a machine learning model.” [0039] “method for use in managing a system comprising one or more computers” [0016] “its accuracy required by application/user,” [0028] “the accuracy reached are recorded.” [0029] “Step 270 determines whether configuration 250 satisfies the accuracy constraints 112 and time constraints 113 provided in step 210.” [0031] “FIG. 3 could be used to determine which machine learning model is optimal in terms of the required accuracy and time constraint when deployed on given hardware resources.”);
determining a proposed equipment configuration, based on the current equipment configuration information, the accuracy-related property, and product information, the proposed equipment configuration being an equipment configuration that satisfies the user request and that is the current equipment configuration with at least one of the current component configuration or the current control program being changed, the product information indicating at least one of a lineup of components applicable to the working machine or a lineup of control programs applicable to the working machine ([0029] “Step 270 determines whether configuration 250 satisfies the accuracy constraints 112 and time constraints 113 provided in step 210…If the constraints are satisfied (YES branch of step 270), the configuration is deemed to be an optimal configuration 280 and is saved to the configuration database 290 with a unique name.” Based on the determined optimal configuration that is determined based on hardware resources, “the optimal configuration file that already exists for the given set of inputs”, and the accuracy constraint to satisfy the accuracy required by application/user, the optimal configuration is to configure the computer.); and
presenting proposed equipment related information that is information related to the proposed equipment configuration ([0029] “If the constraints are satisfied (YES branch of step 270), the configuration is deemed to be an optimal configuration 280 and is saved to the configuration database 290 with a unique name.”).
Regarding claim 13, Assem teaches a non-transitory computer-readable recording medium storing a program ([0050] “The computer readable storage medium can be a tangible device that can retain and store instructions for use by an instruction execution device.”) configured to cause a computer to function as:
a property specifier to specify an accuracy-related property, based on current equipment configuration information, operation history information, and accuracy achievement information, the accuracy-related property being a property affecting a processing accuracy of a working machine, the current equipment configuration information indicating a current equipment configuration containing a current component configuration of the working machine and a current control program of the working machine, the operation history information indicating an operation history of the working machine, the accuracy achievement information indicating a processing accuracy achieved by the working machine ([0041] “The term "processor" as used herein is intended to include any processing device, such as, for example, one that includes a CPU (central processing unit) and/or other forms of processing circuitry.” [0017] “a "configuration" generally refers to the manner in which a system is configured to train a machine learning model with certain accuracy and time. A configuration may involve one or more files. A configuration may include but not limited to system settings such as system name, hardware architecture, number of CPUs (central processing units), RAM (random-access memory) size, storage capacity, operating system, and network configurations. In addition to these system settings, a configuration may also include dependent variables necessary to train the machine learning model.” [0018] “configuration could include configuring one or more virtual machines in terms of, e.g., number of CPUs, size of RAM, storage capacity, operating system, hardware architecture, network settings etc. Configuration may also include tweaking the existing hardware of system in a specific setting to train a machine learning model.” [0039] “method for use in managing a system comprising one or more computers” [0016] “its accuracy required by application/user,” [0028] “the accuracy reached are recorded.” [0029] “Step 270 determines whether configuration 250 satisfies the accuracy constraints 112 and time constraints 113 provided in step 210.” [0031] “FIG. 3 could be used to determine which machine learning model is optimal in terms of the required accuracy and time constraint when deployed on given hardware resources.”); and
an equipment configuration determiner to determine a proposed equipment configuration, based on the current equipment configuration information, the accuracy-related property, and product information, the proposed equipment configuration being an equipment configuration that satisfies the user request and that is the current equipment configuration with at least one of the current component configuration or the current control program being changed, the product information indicating at least one of a lineup of components applicable to the working machine or a lineup of control programs applicable to the working machine ([0029] “Step 270 determines whether configuration 250 satisfies the accuracy constraints 112 and time constraints 113 provided in step 210…If the constraints are satisfied (YES branch of step 270), the configuration is deemed to be an optimal configuration 280 and is saved to the configuration database 290 with a unique name.” Based on the determined optimal configuration that is determined based on hardware resources, “the optimal configuration file that already exists for the given set of inputs”, and the accuracy constraint to satisfy the accuracy required by application/user, the optimal configuration is to configure the computer.).
Claim Rejections - 35 USC § 103
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 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.
Claim(s) 2, 3, and 5 are rejected under 35 U.S.C. 103 as being unpatentable over Assem in view of STROTHER et al. (United States Patent Application Publication US 2016/0196701), hereinafter STROTHER, and further in view of Maeda (United States Patent Application Publication US 2021/0049832), hereinafter Maeda.
Regarding claim 2, Assem teaches all the limitations of the proposal device according to claim 1, as discussed above.
However, Assem does not explicitly teach wherein the processing circuitry specifies a first component in the current component configuration, the first component being used when the traveling member draws the first trajectory, and determines, as the proposed equipment configuration, an equipment configuration that is the current equipment configuration with a new component applied in place of the first component, or an equipment configuration that is the current equipment configuration with a new component applied in addition to the first component.
STROTHER teaches wherein the processing circuitry specifies a first component in the current component configuration, the first component being used when the traveling member draws the first trajectory, and determines, as the proposed equipment configuration, an equipment configuration that is the current equipment configuration with a new component applied in place of the first component, or an equipment configuration that is the current equipment configuration with a new component applied in addition to the first component ([0002] “repeat visits by one or more employees to fix one bicycle may be necessary when the bicycle requires replacement parts not available during prior visits or when an employee with greater mechanic expertise is needed to fix the bicycle.” [0040] “if a first renter reports a steering problem for a particular bicycle and the issue report has a maintenance information weight of ten, a second renter reports the same problem and the issue report has a maintenance information weight of three, and a third renter reports the same problem and the issue report has a maintenance information weight of three, then the technique creates a maintenance task for fixing the bicycle's steering problem.” Based on the current state, a component that needs a maintenance or to be fixed is determined, which is then provided with a new component. STROTHER suggests that the determination is made while operating the bicycle by a user.).
It would have been obvious to obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified the teaching of Assem by incorporating the teaching of STROTHER of wherein the processing circuitry specifies a first component in the current component configuration, the first component being used when the traveling member draws the first trajectory, and determines, as the proposed equipment configuration, an equipment configuration that is the current equipment configuration with a new component applied in place of the first component, or an equipment configuration that is the current equipment configuration with a new component applied in addition to the first component. As recognized by STROTHER, without an efficient and cost effective maintenance system, a bicycle sharing system incurs high maintenance cost, especially in areas where the maintenance workload does not merit the employment of a full-time maintenance staff ([0002]). Therefore, by specifying the component that need to be fixed or replaced with a new component, efficiency to maintain the service can be improved. Therefore, it would be advantageous to incorporate the teaching of STROTHER of wherein the processing circuitry specifies a first component in the current component configuration, the first component being used when the traveling member draws the first trajectory, and determines, as the proposed equipment configuration, an equipment configuration that is the current equipment configuration with a new component applied in place of the first component, or an equipment configuration that is the current equipment configuration with a new component applied in addition to the first component in order to improve the efficiency of the system.
However, Assem in view of STROTHER does not explicitly teach wherein the processing circuitry selects a first trajectory among trajectories drawn by a traveling member while the working machine is processing an object, the traveling member being included in the working machine.
Maeda teaches wherein the processing circuitry selects a first trajectory among trajectories drawn by a traveling member while the working machine is processing an object, the traveling member being included in the working machine ([0041] “At block 202, the pattern module 118 identifies a travel pattern 300 of vehicle usage for the vehicle 100. For example, the travel pattern 300 includes a first trip 302 and a second trip 304 as well as a current trip 306 that the vehicle 100 repeatedly travels from an origin 308 to a destination 310 along a path 312 or a portion 314 of the path.” [0051] “the first predictive range estimate 324 for the current trip 306 may be generated based on the first t2 actual remaining range value 318 of 22 miles t2 at t2 and the second t2 actual remaining range value 322 for the second trip 304 is 56 miles at t2” Based on the previous travel patterns, a travel pattern is predicted or selected. Since a various possible paths are available between an origin to a destination, the predicted travel path is selected among the various possible paths.).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified Assem in view of STROTHER by incorporating the teaching of Maeda of wherein the processing circuitry selects a first trajectory among trajectories drawn by a traveling member while the working machine is processing an object, the traveling member being included in the working machine. As recognized by Maeda, the estimates of the range can rise and fall inconsistently based on topography, grade, and weather conditions, among others, thereby exasperating the range anxiety ([0001]). However, by identifying a travel pattern that is selected more frequently, more accurate estimation of the travel pattern allows more accurate estimation of the power sources and the remaining range estimation, which then helps the traveling member to make a proper decision. Therefore, it would be advantageous to incorporate the teaching of Maeda of wherein the processing circuitry selects a first trajectory among trajectories drawn by a traveling member while the working machine is processing an object, the traveling member being included in the working machine in order to improve the user experience and stability of the system.
Regarding claim 3, Assem in view of STROTHER and further in view of Maeda teaches all the limitations of the proposal device according to claim 2, as discussed above.
Maeda further teaches wherein the processing circuitry selects, as the first trajectory based on the current equipment configuration information and the operation history information, a frequently drawn trajectory among the trajectories drawn by the traveling member ([0041] “At block 202, the pattern module 118 identifies a travel pattern 300 of vehicle usage for the vehicle 100. For example, the travel pattern 300 includes a first trip 302 and a second trip 304 as well as a current trip 306 that the vehicle 100 repeatedly travels from an origin 308 to a destination 310 along a path 312 or a portion 314 of the path.” [0047] “The historical ranges estimates may be remaining range estimates for previous trips.” [0051] “At block 210, the method 200 includes the prediction module 122 generating predictive range estimates along the path 312 based on the actual remaining range values.”).
Regarding claim 5, Assem in view of STROTHER and further in view of Maeda teaches all the limitations of the proposal device according to claim 2, as discussed above.
STROTHER further teaches wherein the processing circuitry specifies one or more candidate components corresponding to the first component from the lineup indicated by the product information, and determines, as the new component, a candidate component satisfying the user request, among the one or more candidate components ([0040] “if a first renter reports a steering problem for a particular bicycle and the issue report has a maintenance information weight of ten, a second renter reports the same problem and the issue report has a maintenance information weight of three, and a third renter reports the same problem and the issue report has a maintenance information weight of three, then the technique creates a maintenance task for fixing the bicycle's steering problem.”).
Claim(s) 6 and 7 are rejected under 35 U.S.C. 103 as being unpatentable over Assem in view of Dunkin et al. (United States Patent Application Publication US 2016/0297044), hereinafter Dunkin.
Regarding claim 6, Assem teaches all the limitations of the proposal device according to claim 1, as discussed above.
However, Assem does not teach wherein the processing circuitry specifies a frequency that readily causes vibration among frequencies used while the working machine is processing an object, and determines, as the proposed equipment configuration, an equipment configuration containing a control program in which the specified frequency is not used.
Dunkin teaches wherein the processing circuitry specifies a frequency that readily causes vibration among frequencies used while the working machine is processing an object ([0021] “controller 30 may select the at least one machining parameter to mitigate machining resonance or machining resonance induced chatter during the machining of component 24 by machine toot 23.” [0027] “FIGS. 2-5 illustrate acoustic frequency responses and stability diagrams for a thin-walled component.” [0041] “controller 30 may further monitor vibrations signals produced by the machining of the component 24 by machine tool 23 via vibration sensor 17.” The controller monitors vibration signals at a range of frequency while a system is performing a machining operation on a workpiece. Also, a resonance of the frequency is specified.), and
determines, as the proposed equipment configuration, an equipment configuration containing a control program in which the specified frequency is not used ([0041] “controller 34 may continuously evaluate the vibrations and the acoustic signals to determine whether there is increasing machining resonance or machining resonance induced chatter. In such an example, modification of the machining parameter may be further based on the monitored vibrations.” The controller is to operate the system with the configuration to avoid the resonance).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified Assem by incorporating the teaching of Dunkin of wherein the processing circuitry specifies a frequency that readily causes vibration among frequencies used while the working machine is processing an object. As recognized by Dunkin, tool vibrations may affect the machining accuracy and the finish quality of the component and may also reduce the life of the tool ([0003]). Dunkin further discloses a matching resonance that incudes chatter during the machining of component ([0021]). By controlling the configuration of the machine to avoid the matching resonance, the performance of the system can be improved ([0033]). Therefore, it would be advantageous to incorporate the teaching of Dunkin of wherein the processing circuitry specifies a frequency that readily causes vibration among frequencies used while the working machine is processing an object in order to improve the performance of the system.
Regarding claim 7, Assem teaches all the limitations of the proposal device according to claim 1, as discussed above.
Dunkin further teaches wherein the processing circuitry, based on accuracy database information containing at least one of (i) simulation information indicating, for each of parameter values each indicating the accuracy-related property, a result of simulation of a feature quantity of a vibration characteristic or processing accuracy or (ii) actual-device experiment information indicating, for each of the parameter values, an experimental result of an experiment for a feature quantity of a vibration characteristic or processing accuracy that is performed using an actual device, calculates, for each of the parameter values, a deviation of the feature quantity indicated by the accuracy database information from the feature quantity indicated by the accuracy achievement information ([0027] “FIGS. 2-5 illustrate acoustic frequency responses and stability diagrams for a thin-walled component.” [0032] “In order to mitigate the machining resonance or machining resonance induced chatter represented by FIGS. 4 and 5, spindle rate may be reduced from point 54 to point 84 as shown in plot 80.”), and
specifies, as the parameter value indicating the accuracy-related property of the working machine, a parameter value corresponding to a feature quantity that is minimum in the calculated deviation among a plurality of the feature quantities indicated by the accuracy database information ([0021] “controller 30 may select the at least one machining parameter to mitigate machining resonance or machining resonance induced chatter during the machining of component 24 by machine toot 23.” [0032] “a computing device controlling the machining may adjust reduce the spindle speed in response to changes in acoustic frequency magnitudes in order to remain between the harmonic frequencies of the component being machined, and also remain distant from chatter regions, even as the harmonic frequencies of the component being machined and the chatter regions change as a result of the machining in a closed-loop control of machining parameters.”).
Claim(s) 11 is rejected under 35 U.S.C. 103 as being unpatentable over Assem in view of Johari (United States Patent Application Publication US 2022/0012032), hereinafter Johari.
Regarding claim 11, Assem teaches the proposal device according to claim 1, as discussed above.
Assem further teaches a working machine ([0038] “an item (e.g., computer, cluster, etc.)”); and a display device (FIG. 4 “display 406”), wherein the working machine includes a storage to store the current equipment configuration information and the operation history information ([0022] “The configurations 150 created by module 140 may follow a virtual machine file format (e.g., vmx). Configuration generator module 140 can save those created configurations in a database 190 so that these configurations can be retrieved by other modules when deploying the configuration in another environment.”).
However, Assem does not explicitly teach wherein the display device includes a display to display the proposed equipment related information output from the proposal device.
Johari teaches wherein the display device includes a display to display the proposed equipment related information output from the proposal device ([0096] “The user interface section 603 can include a number of selectable categories including "user groups," "configuration peers," "devices," and "applications." Each of the selectable categories can, when selected by a user, update the user interface 600 to display configurations and recommendations for the client devices 106, organized according to the selected category.”).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified the teaching of Assem by incorporating the teaching of Johari of wherein the display device includes a display to display the proposed equipment related information output from the proposal device. They are all directed toward configuring resources of the computer. As recognized by Johari, the recommended configuration can include undesirable changes from the user ([0050]). By displaying the recommended configuration changes to the user, the user can decide whether to accept or reject the changes, which allows flexibility and avoid undesirable changes. Therefore, it would be advantageous to incorporate the teaching of Johari of wherein the display device includes a display to display the proposed equipment related information output from the proposal device in order to improve user experience and flexibility of the system.
Allowable Subject Matter
Claim 4 is objected to as being dependent upon a rejected base claim, but would be allowable if rewritten in independent form including all of the limitations of the base claim and any intervening claims.
The following is a statement of reasons for the indication of allowable subject matter:
Assem teaches determining configuration of resources of the computer. However, Assem does not teach “wherein the processing circuitry s selects, as the first trajectory, based on the current equipment configuration information and the operation history information, a trajectory that readily causes vibration among the trajectories drawn by the traveling member.”
STROTHER teaches predicting a maintenance for a bicycle sharing system based on rental history, a bicycle being used less than expected based on rental trends and predicted usage, frequency of rental, bicycle mileage, bicycle age, maintenance history, and sensor data. However, STROTHER does not teach “wherein the processing circuitry s selects, as the first trajectory, based on the current equipment configuration information and the operation history information, a trajectory that readily causes vibration among the trajectories drawn by the traveling member.”
Maeda teaches identifying a travel pattern of vehicle usage based on previous patterns of travels. However, Maeda does not teach “wherein the processing circuitry s selects, as the first trajectory, based on the current equipment configuration information and the operation history information, a trajectory that readily causes vibration among the trajectories drawn by the traveling member.”
Dunkin teaches to control the machining tool to avoid the resonant frequency of. However, Dunkin does not teach “wherein the processing circuitry s selects, as the first trajectory, based on the current equipment configuration information and the operation history information, a trajectory that readily causes vibration among the trajectories drawn by the traveling member.”
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure.
Abeloe (United States Patent Application Publication US 2024/0203132) teaches controlling an autonomous machine using two or more neural networks that inference using input data and generate output data.
Hill et al. (United States Patent Application Publication US 2016/0283254) teaches a system to perform an optimization operation by identifying process states associated with specific ranges for a limited subset of control parameter inputs to optimize a continuous process.
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/HYUN SOO KIM/Examiner, Art Unit 2176