DETAILED ACTION
Claims 1-21 are pending in the application.
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 .
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.
Examiner’s Notes
The Examiner cites particular sections in the references as applied to the claims below for the convenience of the applicant(s). Although the specified citations are representative of the teachings in the art and are applied to the specific limitations within the individual claim, other passages and figures may apply as well. It is respectfully requested that, in preparing responses, the applicant(s) fully consider the references in their entirety as potentially teaching all or part of the claimed invention, as well as the context of the passage as taught by the prior art or disclosed by the Examiner.
Priority
Acknowledgment is made of applicant's claim for foreign priority based on an application filed in Japan on 08/25/2023. It is noted, however, that applicant has not filed a certified copy of the 2023-137196 application as required by 37 CFR 1.55.
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 storage unit that stores therein definition information”, “an acceptance unit that accepts, as a processing pattern, a selection of each of the processes”, “a generating unit that generates, based on the accepted processing pattern and the definition information” in claim 1;
“a learning unit that generates a learning model”, “the storage unit stores therein the learning model”, “the generating unit generates the processing setting information” in claim 2;
“ a learning unit that generates a learning model”, “the storage unit stores therein the learning model”, “the generating unit generates the processing setting information” in claim 3;
“the acceptance unit accepts a processing group” in claim 5;
“the acceptance unit accepts the processing group” in claim 6;
“the acceptance unit accepts, as the processing pattern on a setting screen displayed on a display unit, the selection of each of the processes” in claim 7;
“the acceptance unit accepts, as the processing pattern on the setting screen, the selection of each of the processes and the selection of the execution order” in claim 8;
“the acceptance unit accepts, on a setting screen displayed on a display unit, an input of a set value” in claim 9;
“the acceptance unit accepts, on the setting screen displayed on the display unit, an assignment” in claim 10;
“the generating unit determines whether or not the data processing is executable” in claim 11;
“the generating unit performs a simulation” in claim 12;
“the acceptance unit accepts, on a setting screen of a display unit, at least one of a dynamic-link library file” in claim 13;
“the acceptance unit performs a test” in claim 14;
“the generating unit calculates a set value” in claim 15;
“the generating unit calculates an average period of time series data” in claim 16; and
“the generating unit calculates the set value” in claim 17.
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.
Claim 21 is rejected under 35 U.S.C. 101 because the claimed invention is directed to non-statutory subject matter.
Claim 21 is directed to a computer-readable recording medium. Currently presented, neither the claims nor the specification limits the recording medium to non-transitory embodiments. As such, the medium recited in claim 21 encompasses transitory embodiments which are non-statutory. See MPEP §2106.
Claim Rejections - 35 USC § 102
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.
Claims 1-7, 9-10, 12-15, and 17-21 are rejected under 35 U.S.C. 102(a)(1) as being anticipated by Song et al. (US 2019/0303196 A1; from IDS filed on 04/18/2025; hereinafter “Song”).
With respect to claim 1, Song teaches: An information processing apparatus (see e.g. paragraph 41: “an apparatus for automatically scheduling jobs in computer numerical control machines”; and Fig.3) comprising:
a storage unit that stores (see e.g. paragraph 62: “processing apparatus may access, store, manipulate, process and generate data in response to the execution of software”) therein definition information for defining a processing operation of each of a plurality of processes (see e.g. paragraph 43: “collects a schedule job list from a database”);
an acceptance unit that accepts (see e.g. paragraph 62: “processing apparatus may access, store, manipulate, process and generate data in response to the execution of software”), as a processing pattern, a selection of each of the processes that are used for data processing (see e.g. paragraph 2: “jobs in computer numerical control machines”) and a selection of an execution order of the selected processes (see e.g. paragraph 2: “scheduling jobs in computer numerical control”; paragraph 49: “When the calculated evaluation index reaches the target evaluation index, the schedule analysis unit 340 sets a selection probability so that a schedule having the highest evaluation index is selected”); and
a generating unit that generates (see e.g. paragraph 62: “processing apparatus may access, store, manipulate, process and generate data in response to the execution of software”), based on the accepted processing pattern and the definition information, processing setting information for causing the processing pattern to be performed (see e.g. paragraph 50: “schedule analysis unit 340 incorporates the schedule returned to the user into job assignment information for each machine”).
Song discloses storing a schedule job list, evaluating the schedule job list to accept a selection of a job schedule (i.e. an execution order of jobs), and generating assignments based on the selected schedule for performing jobs on corresponding machines.
With respect to claim 2, Song teaches: The information processing apparatus according to claim 1, further comprising a learning unit that generates a learning model by performing learning by using learning data (see e.g. paragraph 42: “using machine learning includes a pre-processing unit 310, a genetic algorithm-based schedule generation unit 320, a schedule evaluation unit 330, a schedule analysis unit 340 and a display unit”), wherein
the storage unit stores therein the learning model as the definition information (see e.g. paragraph 42: “machine learning includes a pre-processing unit 310”; and paragraph 43: “pre-processing unit 310 collects a schedule job list from a database”), and
the generating unit generates the processing setting information in which the definition information on each of the processes that are indicated by an analysis pattern corresponding to the accepted processing pattern is associated with the accepted analysis pattern (see e.g. paragraph 49: “schedule analysis unit 340 determines whether the calculated evaluation index for the plurality of schedules has reached a target evaluation index. When the calculated evaluation index reaches the target evaluation index, the schedule analysis unit 340 sets a selection probability so that a schedule having the highest evaluation index is selected”).
With respect to claim 3, Song teaches: The information processing apparatus according to claim 1, further comprising a learning unit that generates a learning model by performing learning by using learning data (see e.g. paragraph 42: “using machine learning includes a pre-processing unit 310, a genetic algorithm-based schedule generation unit 320, a schedule evaluation unit 330, a schedule analysis unit 340 and a display unit”), wherein
the storage unit stores therein the learning model as the definition information (see e.g. paragraph 42: “machine learning includes a pre-processing unit 310”; and paragraph 43: “pre-processing unit 310 collects a schedule job list from a database”), and
the generating unit generates the processing setting information in which the definition information on each of the processes that are indicated by a control pattern corresponding to the accepted processing pattern is associated with the accepted control pattern (see e.g. paragraph 49: “schedule analysis unit 340 determines whether the calculated evaluation index for the plurality of schedules has reached a target evaluation index. When the calculated evaluation index reaches the target evaluation index, the schedule analysis unit 340 sets a selection probability so that a schedule having the highest evaluation index is selected”; and paragraph 50: “schedule analysis unit 340 incorporates the schedule returned to the user into job assignment information for each machine”).
With respect to claim 4, Song teaches: The information processing apparatus according to claim 1, further comprising an execution unit that executes the data processing by using the processing setting information (see e.g. paragraph 2: “scheduling jobs in computer numerical control machines”; and paragraph 62: “the apparatus and components described in the embodiments may be implemented using one or more general-purpose computers or special-purpose computers, for example, a processor, a controller, an arithmetic logic unit (ALU), a digital signal processor, a microcomputer, a field programmable array (FPA), a programmable logic unit (PLU), a microprocessor or any other device capable of executing or responding to an instruction. The processing apparatus may perform an operating system (OS) and one or more software applications executed on the OS. Furthermore, the processing apparatus may access, store, manipulate, process and generate data in response to the execution of software”).
With respect to claim 5, Song teaches: The information processing apparatus according to claim 1, wherein
the acceptance unit accepts a processing group that indicates a processing object that is applied to the processing pattern (see e.g. paragraph 47: “genetic algorithm-based schedule generation unit 320 repeatedly performs the step of selecting a schedule corresponding to two evaluation indices and generating two new schedules using the genetic algorithm until new schedules corresponding to the number of plurality of schedules are generated”; and paragraph 48: “In other words, the genetic algorithm-based schedule generation unit 320 groups the N schedules in pair, updates each schedule pair with new two schedules through crossover operation and mutation operation, and repeats crossover and mutation with respect to new N schedules generated in this way”), and
the generating unit associates the processing group with the processing setting information (see e.g. paragraph 49: “schedule analysis unit 340 determines whether the calculated evaluation index for the plurality of schedules has reached a target evaluation index. When the calculated evaluation index reaches the target evaluation index, the schedule analysis unit 340 sets a selection probability so that a schedule having the highest evaluation index is selected”; and paragraph 50: “schedule analysis unit 340 incorporates the schedule returned to the user into job assignment information for each machine”).
With respect to claim 6, Song teaches: The information processing apparatus according to claim 5, wherein the acceptance unit accepts the processing group that includes at least one of instruments between at least one of measurement instruments each of which measures data on the processing object (see e.g. paragraph 37: “evaluation metrics are regarded to measure the optimal level of a given schedule. They are the number of jobs that violates their deadlines, a total of delay hours for jobs over due, and the end time of the last job processed”; paragraph 47: “selecting a schedule corresponding to two evaluation indices”; and paragraph 48: “genetic algorithm-based schedule generation unit 320 induces various schedules having gradually better evaluation indices to be generated by repeating selection and evaluation processes whenever new N schedules are generated”) and at least one of collection instruments each of which collects the data from at least one of the measurement instruments (see e.g. paragraph 37: “In this regard, the schedule that minimizes these metrics is to be determined”; paragraph 49: “sets a selection probability so that a schedule having the highest evaluation index is selected and returns the selection probability”).
With respect to claim 7, Song teaches: The information processing apparatus according to claim 1, wherein the acceptance unit accepts, as the processing pattern on a setting screen displayed on a display unit, the selection of each of the processes and the selection of the execution order of the selected processes (see e.g. paragraph 50: “the schedule analysis unit 340 incorporates the schedule returned to the user into job assignment information for each machine. The display unit displays the job assignment information for each machine by incorporating the schedule returned to the user into the job assignment information for each machine”).
With respect to claim 9, Song teaches: The information processing apparatus according to claim 1, wherein the acceptance unit accepts, on a setting screen displayed on a display unit, an input of a set value that is used for an execution operation of each of the processes, and stores the accepted set value as the definition information in the storage unit (see e.g. paragraph 50: “the schedule analysis unit 340 incorporates the schedule returned to the user into job assignment information for each machine. The display unit displays the job assignment information for each machine by incorporating the schedule returned to the user into the job assignment information for each machine”; and paragraph 59: “The schedule returned to the user is incorporated into job assignment information for each machine. The display unit displays the job assignment information for each machine by incorporating the schedule returned to the user into the job assignment information for each machine. The schedule analysis unit redistributes jobs based on the schedule incorporated into the job assignment information for each machine”).
With respect to claim 10, Song teaches: The information processing apparatus according to claim 9, wherein the acceptance unit accepts, on the setting screen displayed on the display unit (see e.g. paragraph 50: “schedule returned to the user into job assignment information for each machine. The display unit displays the job assignment information for each machine by incorporating the schedule returned to the user”; and paragraph 59: “display unit displays the job assignment information for each machine by incorporating the schedule returned to the user”), an assignment of a frequency with which learning of a learning model is performed or an assignment of a section of learning data that is used for the learning (see e.g. paragraph 50: “the schedule analysis unit 340 incorporates the schedule returned to the user into job assignment information for each machine. The display unit displays the job assignment information for each machine by incorporating the schedule returned to the user into the job assignment information for each machine”; and paragraph 59: “The schedule returned to the user is incorporated into job assignment information for each machine. The display unit displays the job assignment information for each machine by incorporating the schedule returned to the user into the job assignment information for each machine. The schedule analysis unit redistributes jobs based on the schedule incorporated into the job assignment information for each machine”).
With respect to claim 12, Song teaches: The information processing apparatus according to claim 1, wherein the generating unit performs a simulation of the data processing that is executed by using the processing setting information (see e.g. paragraph 23: “a method of generating various schedules, evaluating the schedules by applying three scheduling performance evaluation indices that are autonomously invented, gradually developing the schedules into new schedules, and training the best schedule results”), and displays a simulation result (see e.g. paragraph 49: “When the calculated evaluation index reaches the target evaluation index, the schedule analysis unit 340 sets a selection probability so that a schedule having the highest evaluation index is selected and returns the selection probability to a user”; and paragraph 50: “The display unit displays the job assignment information for each machine by incorporating the schedule returned to the user into the job assignment information for each machine”).
With respect to claim 13, Song teaches: The information processing apparatus according to claim 1, wherein the acceptance unit accepts, on a setting screen of a display unit, at least one of a dynamic-link library file, an executable file, and a text file as a data file (see e.g. paragraph 64: “method according to the embodiment may be implemented in the form of a program instruction executable by various computer means and stored in a computer-readable recording medium. The computer-readable recording medium may include… a data file”) in which each of the plurality of processes is executable (see e.g. paragraph 49: “schedule analysis unit 340 sets a selection probability so that a schedule having the highest evaluation index is selected and returns the selection probability to a user”; paragraph 50: “The display unit displays the job assignment information for each machine by incorporating the schedule returned to the user into the job assignment information for each machine”; and paragraph 64: “method according to the embodiment may be implemented in the form of a program instruction executable by various computer means and stored in a computer-readable recording medium. The computer-readable recording medium may include… a data file”), and stores the accepted data file in the storage unit (see e.g. paragraph 50: “incorporates the schedule returned to the user into job assignment information for each machine. The display unit displays the job assignment information for each machine by incorporating the schedule returned to the user into the job assignment information for each machine”; and paragraph 51: “redistributes jobs according to the schedule incorporated into the job assignment information for each machine”).
With respect to claim 14, Song teaches: The information processing apparatus according to claim 13, wherein the acceptance unit performs a test of each of the processes performed by the data file (see e.g. paragraph 35: “Each schedule pair is updated with new two schedules through crossover operation and mutation operation. Crossover and mutation are repeatedly performed on the new N schedules generated in this way. Whenever the new N schedules are generated, various schedules having gradually better evaluation indices are generated through the repetition of selection and evaluation processes. Thereafter, the process returns to step 230 of calculating an evaluation index for the plurality of generated schedules”) by inputting, on the setting screen, a predetermined input value to the accepted data file (see e.g. paragraph 36: “When the calculated evaluation index reaches the target evaluation index, at step 260, a selection probability is set so that a schedule having the highest evaluation index is selected and returned to a user. Thereafter, the schedule returned to the user is incorporated into job assignment information for each machine, and the job assignment information for each machine is displayed”).
With respect to claim 15, Song teaches: The information processing apparatus according to claim 1, wherein the generating unit calculates a set value that is used to perform each of the processes by using a predetermined algorithm that is applied to each of the processes (see e.g. paragraph 44: “genetic algorithm-based schedule generation unit 320 generates a plurality of schedules with respect to a schedule job to be processed with respect to the schedule job list. It randomly generates N schedules using target job lists to be scheduled, fetched from the database”; and paragraph 47) or by using history information that is related to a processing operation of each of the processes (see e.g. paragraph 48: “genetic algorithm-based schedule generation unit 320 groups the N schedules in pair, updates each schedule pair with new two schedules through crossover operation and mutation operation, and repeats crossover and mutation with respect to new N schedules generated in this way. The genetic algorithm-based schedule generation unit 320 induces various schedules having gradually better evaluation indices to be generated by repeating selection and evaluation processes whenever new N schedules are generated”).
With respect to claim 17, Song teaches: The information processing apparatus according to claim 15, wherein the generating unit calculates the set value that is used for learning of a learning model by using the history information (see e.g. paragraph 42: “scheduling jobs in computer numerical control machines using machine learning includes… a genetic algorithm-based schedule generation unit 320”; and paragraph 48: “genetic algorithm-based schedule generation unit 320 groups the N schedules in pair, updates each schedule pair with new two schedules through crossover operation and mutation operation, and repeats crossover and mutation with respect to new N schedules generated in this way. The genetic algorithm-based schedule generation unit 320 induces various schedules having gradually better evaluation indices to be generated by repeating selection and evaluation processes whenever new N schedules are generated”).
With respect to claim 18, Song teaches: The information processing apparatus according to claim 5, wherein the data processing is a data analysis of data measured by a sensor instrument (see e.g. paragraph 37: “evaluation metrics are regarded to measure the optimal level of a given schedule. They are the number of jobs that violates their deadlines, a total of delay hours for jobs over due, and the end time of the last job processed”; paragraph 47: “selecting a schedule corresponding to two evaluation indices”; and paragraph 48: “genetic algorithm-based schedule generation unit 320 induces various schedules having gradually better evaluation indices to be generated by repeating selection and evaluation processes whenever new N schedules are generated”) installed in a plant (see e.g. paragraph 20: “In a factory in which products are fabricated using a computer numerical control machine, several thousands of types of products are distributed to machines suitable for conditions depending on the size or shape of each product and are fabricated. In this case, such conditions act as a kind of constraints in scheduling… The present invention proposes an optimized schedule necessary for a production site while satisfying such schedule constraints”).
With respect to claim 19, Song teaches: The information processing apparatus according to claim 5, wherein the data processing is data control that controls a plant instrument installed in a plant (see e.g. paragraph 20: “In a factory in which products are fabricated using a computer numerical control machine, several thousands of types of products are distributed to machines suitable for conditions depending on the size or shape of each product and are fabricated. In this case, such conditions act as a kind of constraints in scheduling… The present invention proposes an optimized schedule necessary for a production site while satisfying such schedule constraints”).
With respect to claim 20: Claim 20 is directed to an information processing method corresponding to the active functions implemented by the information processing system disclosed in claim 1; please see the rejection directed to claim 1 above which also covers the limitations recited in claim 20.
With respect to claim 21: Claim 21 is directed to a computer-readable recording medium having stored therein an information processing program that causes a computer to execute a process corresponding to the active functions implemented by the information processing system disclosed in claim 1; please see the rejection directed to claim 1 above which also covers the limitations recited in claim 20. Note that, Song also discloses a computer-readable recording medium storing program instructions to implement a process corresponding to the active functions implemented by the information processing system disclosed in claim 1 (see paragraph 64).
Claim Rejections - 35 USC § 103
The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
This application currently names joint inventors. In considering patentability of the claims the examiner presumes that the subject matter of the various claims was commonly owned as of the effective filing date of the claimed invention(s) absent any evidence to the contrary. Applicant is advised of the obligation under 37 CFR 1.56 to point out the inventor and effective filing dates of each claim that was not commonly owned as of the effective filing date of the later invention in order for the examiner to consider the applicability of 35 U.S.C. 102(b)(2)(C) for any potential 35 U.S.C. 102(a)(2) prior art against the later invention.
Claims 8, 11, and 16 are rejected under 35 U.S.C. 103 as being unpatentable over Song in view of Nanjundappa et al. (US 2019/0370155 A1; hereinafter “Nanjundappa”).
With respect to claim 8, Song teaches: The information processing apparatus according to claim 7, wherein the acceptance unit accepts, as the processing pattern on the setting screen, the selection of each of the processes and the selection of the execution order of the selected processes (see e.g. Song, paragraph 50: “the schedule analysis unit 340 incorporates the schedule returned to the user into job assignment information for each machine. The display unit displays the job assignment information for each machine by incorporating the schedule returned to the user into the job assignment information for each machine”)
Song does not but Nanjundappa teaches:
by connecting blocks that indicate the respective processes by lines with arrows each of which indicates the execution order of the processes (see e.g. Nanjundappa, paragraph 61: “A user may select a desired model element type from a palette, and cause the model editor window 204 to add an instance of that model element type to the canvas 302. The user also may cause the model editor window 204 to establish relationships among the model elements, for example by linking selected model elements using connection elements. The connection elements may be represented on the canvas 302 through graphical affordances, such as wires, arrows, etc.”).
Song and Nanjundappa are analogous art because they are in the same field of endeavor: designing an execution order model. Therefore, it would have been obvious to one with ordinary skill in the art before the effective filing date of the claimed invention to modify Song with the teachings of Nanjundappa. The motivation/suggestion would be to increase the administrative capabilities given to the users; thus improving the overall user-friendliness of the system.
With respect to claim 11, Song teaches: The information processing apparatus according to claim 1,
Song does not but Nanjundappa teaches:
wherein the generating unit determines whether or not the data processing is executable by confirming an arrangement of blocks that indicate the respective processes indicated by the processing pattern and an arrangement of arrows that indicates the execution order of the processes (see e.g. Nanjundappa, paragraph 34: “observers that perform verification and validation of an executable model or a component of a model ”; paragraph 61: “modeling environment 200 may include one or more libraries of model element types, and the UI engine 202 may display one or more palettes presenting the various types of model elements, such as blocks, that may be selected and used to construct or revise a model. A user may select a desired model element type from a palette, and cause the model editor window 204 to add an instance of that model element type to the canvas 302. The user also may cause the model editor window 204 to establish relationships among the model elements, for example by linking selected model elements using connection elements. The connection elements may be represented on the canvas 302 through graphical affordances, such as wires, arrows, etc.”; and paragraph 176: “Execution of the observer may result in verification and validation operations being performed based on the functionality of the observer, as also indicated at step 1348. The observer may make pass/fail determinations”).
Song and Nanjundappa are analogous art because they are in the same field of endeavor: designing an execution order model. Therefore, it would have been obvious to one with ordinary skill in the art before the effective filing date of the claimed invention to modify Song with the teachings of Nanjundappa. The motivation/suggestion would be to increase the administrative capabilities given to the users; thus improving the overall user-friendliness of the system.
With respect to claim 16, Song teaches: The information processing apparatus according to claim 15,
Song does not but Nanjundappa teaches:
wherein the generating unit calculates an average period of time series data by applying a zero cross method to the time series data that has been input to each of the processes (see e.g. Nanjundappa, paragraph 141: “at one simulation time step the value of the signal may be −1 and at a next simulation time step the value may be 1. The simulation engine 206 may issue an execution event in response to that occurrence, e.g., a Zero Crossing execution event… the detector 714 may capture 1180 the simstate at a simulation time in between the two simulation time steps where the zero crossing indicator function was at zero, for example within a root-finding tolerance”; paragraph 142: “During execution of the Observer block 2522, the message may be accessed by 1185 the simulation engine 206, for example at a simulation time step matching the simulation time step when the Zero Crossing execution event occurred”; and paragraph 202: “Hardware events and/or conditions observed by the observer and/or data computed by an observer based on observed hardware events, such as average task execution time”).
Song and Nanjundappa are analogous art because they are in the same field of endeavor: designing an execution order model. Therefore, it would have been obvious to one with ordinary skill in the art before the effective filing date of the claimed invention to modify Song with the teachings of Nanjundappa. The motivation/suggestion would be to .
CONCLUSION
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure:
Fujita et al. (US 2022/0350652 A1) discloses a service design method of supporting high-quality API service design in which a user selects multiple APIs to combine to specify appropriate execution order of the multiple APIs (see paragraph 33).
Morton et al. (US 2022/0035864 A1) discloses a business integration application management system with an integration application development platform that enables a user to create a customized data integration software application by modeling a data integration process flow using a visual user interface (see paragraph 22).
Stienhans et al. (US 2005/0257210 A1) discloses a system for developing user interfaces by using user interface patterns which are configurable, reusable user interface unit designed to let users accomplish a task, such as searching for business objects, and editing the objects that are retrieved (see paragraph 34).
Contact Information
Any inquiry concerning this communication or earlier communications from the examiner should be directed to Umut Onat whose telephone number is (571)270-1735. The examiner can normally be reached M-Th 9:00-7:30.
Examiner interviews are available via telephone, in-person, and video conferencing using a USPTO supplied web-based collaboration tool. To schedule an interview, applicant is encouraged to use the USPTO Automated Interview Request (AIR) at http://www.uspto.gov/interviewpractice.
If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Kevin L Young can be reached at (571) 270-3180. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/UMUT ONAT/Primary Examiner, Art Unit 2194
