DETAILED ACTION
Notice of Pre-AIA or AIA Status
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
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.
Information Disclosure Statement
The information disclosure statement (IDS) submitted on 12 is in compliance with the provisions of 37 CFR 1.97. Accordingly, the information disclosure statement is being considered by the examiner.
Specification
The title of the invention is not descriptive. A new title is required that is clearly indicative of the invention to which the claims are directed.
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.
(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.
Claims 1-7 and 15-17 are rejected under 35 U.S.C. 102(a)(1)/(a)(2)as
being anticipated by Miyamoto et al. (US 20210134397 A1; IDS REF) (hereinafter Miyamoto).
Regarding claim 1, Miyamoto discloses an information processing method executed by an information processing system, comprising: para. [0002], “Embodiments described herein relate generally to an information processing apparatus for discrimination of odors, an information processing method, and a storage medium”; para. [0027], “In general, according to one embodiment, an information processing apparatus comprises a processor. The processor is configured to receive a first number of outputs from the first number of sensors mutually different in response to an odor; obtain a second number of indicators by using the first number of outputs from the first number of sensors, the second number being larger than the first number; obtain the second number of indicator values by using the first number of outputs and the second number of indicators; and discriminate the odor based on the second number of indicator values.”; FIG.3; FIG.4)
a first acquisition step of acquiring target data that is odor data detected from an evaluation target by a sensor (sensor device 12); (112, 114 in FIG. 9;
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para. [0049], "The discrimination apparatus 22 performs calculation processing on an output of the sensor cassette 10 to perform odor discrimination for the sample 8. The discrimination apparatus 22 may control the pump 14, the intake valve 16, and the exhaust valve 18 in conjunction with each other in the odor discrimination."; para. [0079], "In step 112, the driver 19 causes the intake valve 16 to close, and the sensor device 12 measures the amount and concentration of odorous molecules in the sample."; para. [0081], "In step 114, the indicator-value-pattern creation module 62 substitutes the sensor outputs SO1, SO2, SO3, and SO4 of the sensors S1, S2, S3, and S4 of the sensor cassette 10 into the definition equations (FIG. 7) of the indicators ID1 to ID15 that have been set in step 105 to obtain an indicator-value-pattern.")
a specification step (step 124) of specifying a correlation between the target data (target sample) and at least a part of reference data (known samples) that is odor data based on a plurality of predetermined reference odors; and (124 in FIG. 10;
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para. [0087], " in step 124 of FIG. 10, the discrimination module 66 sequentially reads the indicator-value-patterns of the known samples measured by the sensor cassette with which the discrimination target sample has been measured, among the indicator-value-patterns of the known samples stored in the RAM 36. The discrimination module 66 sequentially compares the read indicator-value-patterns with the indicator-value-pattern of the discrimination target sample to search for one or more indicator-value-patterns of the known samples similar to the indicator-value-pattern of the discrimination target sample."; para. [0084], "FIG. 11 illustrates the exemplary indicator-value-patterns of known samples. For convenience of description, each indicator-value-pattern is displayed in a radar chart format in FIG. 11; however, what is written in the RAM 36 is a table such as indicated in FIG. 7. The quality of a sample that is sample specification information includes, for example, musty odor, green grassy odor, metallic odor, . . . , and the like. The quality of the musty odor includes a plurality of indicator-value-patterns of, for example, the first musty odor, second musty odor, . . . , and the like. Similarly, the green grassy odor and the metallic odor each include a plurality of indicator-value-patterns.")
a presentation step of presenting odor information that is information visualizing the target data based on the correlation, using the reference data (known samples) that has specified the correlation as an index. (para. [0089], "In step 126, the discrimination module 66 discriminates the quality and intensity of the discrimination target sample (odor), based on the one or more indicator-value-patterns of the known samples similar to the indicator-value-pattern of the discrimination target sample. Then, the discrimination module 66 causes the display device 40 to display the discrimination result. After step 126 ends, step 122 is executed."; para. [0090], "FIG. 12 illustrates a display example of a discrimination result. FIG. 12 illustrates a discrimination result in a case where the indicator-value-pattern of the discrimination target sample is similar to six indicator-value-patterns of the known samples of different qualities. The display device 40 displays a radar chart representing the respective intensities of the six odors (musty odor, green grassy odor, irritating odor, metallic odor, oil odor, and plastic odor). Together with the radar chart, a text expressing the qualities and intensities is The example of the text is “Odor of the sample X is determined as musty odor: 30%, green grassy odor: 25%, irritating odor: 15%, metallic odor: 12%, oil odor: 9%, and plastic odor: 9%”. Alternatively, only text or a graph such as a radar chart may be displayed."; FIG. 12)
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Regarding claim 2, Miyamoto discloses the information processing method according to claim 1, further comprising:
a second acquisition step of acquiring a set of a plurality of odor data detected from each of the reference odors by a sensor; and (para. [0079], "In step 112, the driver 19 causes the intake valve 16 to close, and the sensor device 12 measures the amount and concentration of odorous molecules in the sample."; para. [0081], "In step 114, the indicator-value-pattern creation module 62 substitutes the sensor outputs SO1, SO2, SO3, and SO4 of the sensors S1, S2, S3, and S4 of the sensor cassette 10 into the definition equations (FIG. 7) of the indicators ID1 to ID15 that have been set in step 105 to obtain an indicator-value-pattern."; para. [0050], "FIG. 4 is a block diagram illustrating an example of the discrimination apparatus 22 according to the first embodiment. The sensor device 12 includes a driver 15 that drives the pump 14, and a driver 19 that drives the intake valve 16 and the exhaust valve 18. The discrimination apparatus 22 includes an indicator value calculating unit and a discrimination unit. The indicator value calculating unit calculates a second number of indicators from the output signals of the sensor device 12. The second number is larger than the number (a first number) of sensors. The indicator value calculating unit obtains indicator values based on the output signals and the indicators. The discrimination unit discriminates an odor based on the indicator values."; para. [0051], "It is sufficient if the discrimination apparatus 22 is capable of exchanging information with the indicator value calculating unit and the discrimination unit. Therefore, the discrimination apparatus 22 may not include the indicator value calculating unit and the discrimination unit. The discrimination apparatus 22 may also include an interface (I/F) 24 that takes an output signal from the sensor cassette 10 into the discrimination apparatus 22, an interface (I/F) 26 that outputs a drive signal to the driver 15, and an interface (I/F) 28 that outputs a drive signal to the driver 19. The interface 24 is also referred to as an input unit." para. [0084], "FIG. 11 illustrates the exemplary indicator-value-patterns of known samples. For convenience of description, each indicator-value-pattern is displayed in a radar chart format in FIG. 11; however, what is written in the RAM 36 is a table such as indicated in FIG. 7. The quality of a sample that is sample specification information includes, for example, musty odor, green grassy odor, metallic odor, . . . , and the like. The quality of the musty odor includes a plurality of indicator-value-patterns of, for example, the first musty odor, second musty odor, . . . , and the like. Similarly, the green grassy odor and the metallic odor each include a plurality of indicator-value-patterns.")
a generation step of generating the reference data (known samples) based on features of odor data acquired in the second acquisition step. (para. [0083], "In a case where it is determined that the operation mode is the learning mode, in step 118, the known-sample indicator-value-pattern writing module 64 writes the indicator-value-pattern of the known sample into the RAM 36, together with the sample specification information. Note that the known-sample indicator-value-pattern writing module 64 writes, into the RAM 36, the sensor-cassette identification information in association with the indicator-value-pattern.")
Regarding claim 3, Miyamoto discloses the information processing method according to claim 1, further comprising:
a second acquisition step of acquiring odor data detected from a reference target (sample) by a sensor and an evaluation of the reference target, the evaluation showing an odor of the reference target by intensity of each of the reference odors, and (para. [0049], "The discrimination apparatus 22 performs calculation processing on an output of the sensor cassette 10 to perform odor discrimination for the sample 8. The discrimination apparatus 22 may control the pump 14, the intake valve 16, and the exhaust valve 18 in conjunction with each other in the odor discrimination."; para. [0079], "In step 112, the driver 19 causes the intake valve 16 to close, and the sensor device 12 measures the amount and concentration of odorous molecules in the sample."; para. [0081], "In step 114, the indicator-value-pattern creation module 62 substitutes the sensor outputs SO1, SO2, SO3, and SO4 of the sensors S1, S2, S3, and S4 of the sensor cassette 10 into the definition equations (FIG. 7) of the indicators ID1 to ID15 that have been set in step 105 to obtain an indicator-value-pattern."; para. [0090], "FIG. 12 illustrates a display example of a discrimination result. FIG. 12 illustrates a discrimination result in a case where the indicator-value-pattern of the discrimination target sample is similar to six indicator-value-patterns of the known samples of different qualities. The display device 40 displays a radar chart representing the respective intensities of the six odors (musty odor, green grassy odor, irritating odor, metallic odor, oil odor, and plastic odor). Together with the radar chart, a text expressing the qualities and intensities is displayed. The example of the text is “Odor of the sample X is determined as musty odor: 30%, green grassy odor: 25%, irritating odor: 15%, metallic odor: 12%, oil odor: 9%, and plastic odor: 9%”. Alternatively, only text or a graph such as a radar chart may be displayed.")
a generation step of generating the reference data (known samples) based on odor data acquired in the second acquisition step and the evaluation. (para. [0053], "The input device 38 inputs various types of information to the discrimination apparatus 22. The various types of information include, for example, operation mode information indicative of whether the operation mode is a discrimination mode or a learning mode. In the learning mode, a known sample having a known odor is measured to obtain an indicator value. Then, sample specification information indicative of the odor quality of the known sample, that is, output information from the sensor cassette 10 and the indicator value are associated with each other to create a database."; para. [0054], "The database is provided in a storage unit such as the flash memory 34 or the RAM 36. A known sample having a known odor is a sample for which the database has the odor information. In contrast, an unknown sample having an unknown odor is a sample for which the database has no odor information. The input device 38 may be used to input the sample specification information. In the discrimination mode, the discrimination target sample that is an unknown sample is measured to obtain an indicator value. Then, sample specification information is obtained by reference to the database."; para. [0083], "In a case where it is determined that the operation mode is the learning mode, in step 118, the known-sample indicator-value-pattern writing module 64 writes the indicator-value-pattern of the known sample into the RAM 36, together with the sample specification information. Note that the known-sample indicator-value-pattern writing module 64 writes, into the RAM 36, the sensor-cassette identification information in association with the indicator-value-pattern.")
Regarding claim 4, Miyamoto discloses the information processing method according to claim 1,wherein:
the reference odors include a plurality of odor components. (FIG 11;
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para. [0084], "FIG. 11 illustrates the exemplary indicator-value-patterns of known samples. For convenience of description, each indicator-value-pattern is displayed in a radar chart format in FIG. 11; however, what is written in the RAM 36 is a table such as indicated in FIG. 7. The quality of a sample that is sample specification information includes, for example, musty odor, green grassy odor, metallic odor, . . . , and the like. The quality of the musty odor includes a plurality of indicator-value-patterns of, for example, the first musty odor, second musty odor, . . . , and the like. Similarly, the green grassy odor and the metallic odor each include a plurality of indicator-value-patterns.")
Regarding claim 5, Miyamoto discloses the information processing method according to claim 1, wherein:
the specification step specifies a correlation between the target data (target sample) and reference data (known samples) corresponding to a presentation target of the odor information among the reference data. (para. [0087], " in step 124 of FIG. 10, the discrimination module 66 sequentially reads the indicator-value-patterns of the known samples measured by the sensor cassette with which the discrimination target sample has been measured, among the indicator-value-patterns of the known samples stored in the RAM 36. The discrimination module 66 sequentially compares the read indicator-value-patterns with the indicator-value-pattern of the discrimination target sample to search for one or more indicator-value-patterns of the known samples similar to the indicator-value-pattern of the discrimination target sample."; para. [0084], “FIG. 11 illustrates the exemplary indicator-value-patterns of known samples. For convenience of description, each indicator-value-pattern is displayed in a radar chart format in FIG. 11; however, what is written in the RAM 36 is a table such as indicated in FIG. 7. The quality of a sample that is sample specification information includes, for example, musty odor, green grassy odor, metallic odor, . . . , and the like. The quality of the musty odor includes a plurality of indicator-value-patterns of, for example, the first musty odor, second musty odor, . . . , and the like. Similarly, the green grassy odor and the metallic odor each include a plurality of indicator-value-patterns.”; FIG 11)
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Regarding claim 6, Miyamoto discloses the information processing method according to claim 1,wherein:
the specification step specifies a correlation between the target data(target sample) and reference data(known samples) corresponding to the evaluation target among the reference data. (para. [0087], " in step 124 of FIG. 10, the discrimination module 66 sequentially reads the indicator-value-patterns of the known samples measured by the sensor cassette with which the discrimination target sample has been measured, among the indicator-value-patterns of the known samples stored in the RAM 36. The discrimination module 66 sequentially compares the read indicator-value-patterns with the indicator-value-pattern of the discrimination target sample to search for one or more indicator-value-patterns of the known samples similar to the indicator-value-pattern of the discrimination target sample.")
Regarding claim 7, Miyamoto discloses the information processing method according to claim 1,wherein:
the odor information is a radar chart showing intensity of the reference odors using the reference odors as an index. (FIG 12; para. [0090], “FIG. 12 illustrates a display example of a discrimination result. FIG. 12 illustrates a discrimination result in a case where the indicator-value-pattern of the discrimination target sample is similar to six indicator-value-patterns of the known samples of different qualities. The display device 40 displays a radar chart representing the respective intensities of the six odors (musty odor, green grassy odor, irritating odor, metallic odor, oil odor, and plastic odor). Together with the radar chart, a text expressing the qualities and intensities is displayed.”)
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Regarding claim 15, Miyamoto discloses an information processing system comprising at least one device, comprising:
at least one processor configured to execute a program so that each step of the information processing method according to claim 1 is executed. (para. [0042], "FIG. 3 is a diagram illustrating an exemplary sensing system according to the first embodiment. The sensing system may be read as an information processing system. The sensing system includes a sensor device 12 and a discrimination apparatus 22."; para. [0052], "The discrimination apparatus 22 also includes a central processing unit (CPU) 32 that controls the entirety, a non-volatile memory 34 that stores programs executed by the CPU 32 and the like, a volatile memory 36 that stores data during work or the like, an input device 38, and a display device 40. The programs include an odor discrimination program. For example, a flash memory is used as the non-volatile memory 34, and a random access memory (RAM) is used as the volatile memory 36. Hereinafter, the non-volatile memory 34 is referred to as a flash memory, and the volatile memory 36 is referred to as a RAM." )
Regarding claim 16, Miyamoto discloses an information processing apparatus, comprising:
at least one processor configured to execute a program so that each step of the information processing method according to claim 1 is performed. (para. [0052], "The discrimination apparatus 22 also includes a central processing unit (CPU) 32 that controls the entirety, a non-volatile memory 34 that stores programs executed by the CPU 32 and the like, a volatile memory 36 that stores data during work or the like, an input device 38, and a display device 40. The programs include an odor discrimination program. For example, a flash memory is used as the non-volatile memory 34, and a random access memory (RAM) is used as the volatile memory 36. Hereinafter, the non-volatile memory 34 is referred to as a flash memory, and the volatile memory 36 is referred to as a RAM.")
Regarding claim 17, Miyamoto discloses a non-transitory computer readable storage medium storing a program, configured to allow at least one computer to execute each step of the information processing method according to claim 1. (claim 18, "A non-transitory computer-readable storage medium storing computer-executable instructions that, when executed, cause the computer to:"; para. [0052], "The discrimination apparatus 22 also includes a central processing unit (CPU) 32 that controls the entirety, a non-volatile memory 34 that stores programs executed by the CPU 32 and the like, a volatile memory 36 that stores data during work or the like, an input device 38, and a display device 40. The programs include an odor discrimination program. For example, a flash memory is used as the non-volatile memory 34, and a random access memory (RAM) is used as the volatile memory 36. Hereinafter, the non-volatile memory 34 is referred to as a flash memory, and the volatile memory 36 is referred to as a RAM.")
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.
Claims 8-10 and 12-14 are rejected under 35 U.S.C. 103 as being unpatentable over Miyamoto et al. (US 20210134397 A1) (hereinafter Miyamoto) in view of Sakassi (JP 2018031882 A; IDS REF) (hereinafter Sakassi).
Regarding claim 8, Miyamoto does not disclose the information processing method according to claim 1, wherein:
the odor information is a set of divided circles obtained by dividing a circle according to intensity of the reference odors.
Sakassi more explicitly teaches the information processing method according to claim 1, wherein:
the odor information is a set of divided circles obtained by dividing a circle according to intensity of the reference odors. (FIG. 8; para. [0058], "Here, the bubble chart of FIG. 8 is a bubble chart in which the vertical axis represents the saturated vapor pressure (mmHg), the horizontal axis represents the aroma sensitivity threshold (ng / Lair), and the radius of each bubble is the volatilization amount It is also good. According to such a bubble chart, a region having a high saturation vapor pressure and a high aroma sensitivity threshold (mainly a component contributing to the top note), a region having a low saturation vapor pressure and a low aroma sensitivity threshold (mainly , A component contributing to last note (residual fragrance)), a region having a high saturation vapor pressure but a low aroma sensitivity threshold (mainly a component contributing to top to middle note), while a saturated vapor pressure is low but a fragrance sensitivity threshold Each volatile component value (volatilization amount) is indicated by the size of the bubble at a position corresponding to the characteristic of each fragrance component, such as a high region (mainly used in a large amount and contributing to middle to last note) Therefore, it is possible to make flavor components fluctuate while adding flavor components to the perfumers. For saturated vapor pressure and aroma sensitivity threshold for each aroma component, well-known information may be used.
As both Miyamoto and Sakassi are from the same field of endeavor, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify Miyamoto to include the odor information is a set of divided circles obtained by dividing a circle according to intensity of the reference odors, in the context of information processing, according to the teaching of Sakassi, in order to display fluctuation of fragrance (para. [0001] of Sakassi).
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Regarding claim 9, Miyamoto does not explicitly disclose the information processing method according to claim 1,wherein:
the odor information is an image in which objects of colors defined for each of the reference odors are arranged.
Sakassi more explicitly teaches the information processing method according to claim 1,wherein:
the odor information is an image in which objects of colors defined for each of the reference odors are arranged. (FIG. 2; FIG. 8; Examiner’s note: It’s well-known presentation method to use colors to reference similarities and differences in material and display the color information in a graphical representation. FIG.2 and FIG.8 are illustrated in black and white but different hatched variation of bars or circles.)
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Sakassi further teaches the graphs could be displayed using colored display methods. (para. [0050]: “there are various methods of “timing presentation”…a motion graph for a predetermined time at a timing when an aroma component distribution corresponding to a target product is displayed. There is also a method of changing the color of at least a part of the display or adding a decoration at the timing when the distribution of the fragrance component corresponding to the target product is displayed)
As both Miyamoto and Sakassi are from the same field of endeavor, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify Miyamoto to include the odor information is a set of divided circles obtained by dividing a circle according to intensity of the reference odors, in the context of information processing, according to the teaching of Sakassi, since it’s a known methodology for representing odors/fragrances in order to display fluctuation of fragrance (para. [0001] of Sakassi).
Regarding claim 10, Miyamoto does not disclose the information processing method according to claim 9, wherein:
a size of each of the objects differs depending on intensity of the reference odors contained in the evaluation target.
Sakassi more explicitly teaches disclose the information processing method according to claim 9, wherein:
a size of each of the objects differs depending on intensity of the reference odors contained in the evaluation target. (FIG. 8)
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As both Miyamoto and Sakassi are from the same field of endeavor, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify Miyamoto to include the odor information is a set of divided circles obtained by dividing a circle according to intensity of the reference odors, in the context of information processing, according to the teaching of Sakassi, in order to display fluctuation of fragrance (para. [0001] of Sakassi).
Regarding claim 12, the combination of Miyamoto and Sakassi discloses the information processing method according to claim 8,wherein:
in a case where the target data (target sample) includes a specific pattern of a combination of the reference odors, the odor information includes an image corresponding to the specific pattern. (Miyamoto, FIG. 12;
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para. [0090], "FIG. 12 illustrates a display example of a discrimination result. FIG. 12 illustrates a discrimination result in a case where the indicator-value-pattern of the discrimination target sample is similar to six indicator-value-patterns of the known samples of different qualities. The display device 40 displays a radar chart representing the respective intensities of the six odors (musty odor, green grassy odor, irritating odor, metallic odor, oil odor, and plastic odor). Together with the radar chart, a text expressing the qualities and intensities is displayed. The example of the text is “Odor of the sample X is determined as musty odor: 30%, green grassy odor: 25%, irritating odor: 15%, metallic odor: 12%, oil odor: 9%, and plastic odor: 9%”. Alternatively, only text or a graph such as a radar chart may be displayed."; Examiner's note: a specific patterns of a combination of the reference odors corresponds to the combination of musty odor: 30%, green grassy odor: 25%, irritating odor: 15%, metallic odor: 12%, oil odor: 9%, and plastic odor: 9%. An image corresponds to a radar chart or graph.)
Regarding claim 13, Miyamoto discloses
the specification step compares the target data (target sample) and the reference data (known samples) and specifies a reference object similar to the target data, and (para. [0087], " in step 124 of FIG. 10, the discrimination module 66 sequentially reads the indicator-value-patterns of the known samples measured by the sensor cassette with which the discrimination target sample has been measured, among the indicator-value-patterns of the known samples stored in the RAM 36. The discrimination module 66 sequentially compares the read indicator-value-patterns with the indicator-value-pattern of the discrimination target sample to search for one or more indicator-value-patterns of the known samples similar to the indicator-value-pattern of the discrimination target sample."; FIG. 12; para. [0090], “FIG. 12 illustrates a display example of a discrimination result. FIG. 12 illustrates a discrimination result in a case where the indicator-value-pattern of the discrimination target sample is similar to six indicator-value-patterns of the known samples of different qualities. The display device 40 displays a radar chart representing the respective intensities of the six odors (musty odor, green grassy odor, irritating odor, metallic odor, oil odor, and plastic odor). Together with the radar chart, a text expressing the qualities and intensities is displayed. The example of the text is “Odor of the sample X is determined as musty odor: 30%, green grassy odor: 25%, irritating odor: 15%, metallic odor: 12%, oil odor: 9%, and plastic odor: 9%”. Alternatively, only text or a graph such as a radar chart may be displayed.”; para. [0091], “The odor quality is also called as the odor type. Various qualities can be considered depending on a discrimination target sample. For example, the odor quality of wine may be classified into 1: spicy, 2: fruity aroma, 3: vegetable aroma, 4: nuts, 5: caramel, 6: woody aroma, 7: earthy aroma, 8: chemical substance, 9: irritating odor, 10: oxide, 11: microorganism, and 12: flower aroma. The odor quality of sake may be classified into 1: ginjo aroma, fruity, fragrant, and floral; 2: woody and glassy aroma, tree-nutty, and spicy; 3: grain-like and koji; 4: sweet, caramel-like, charred; 5: oxidation and deterioration; 6: sulfur-like; 7: transferred aroma; and 8: lipid-like and acid odor.”)
Miyamoto does not disclose the information processing method according to claim 1,wherein:
the reference data includes a change over time of an odor of a reference object,
the odor information includes information that visualizes the change over time of the odor of the reference object.
However, Sakassi more explicitly teaches the information processing method according to claim 1,wherein:
the reference data includes a change over time of an odor of a reference object,
the odor information includes information that visualizes the change over time of the odor of the reference object. (FIG. 7A; FIG. 7B; para. [0008] The first aspect relates to an aroma fluctuation display method. The aroma fluctuation display method according to the first aspect includes a first moving image showing a temporal change in appearance of an object and a second moving image showing in chronological change in the amount or ratio of the aroma component corresponding to the object in a graph form And outputs a display in which time series are associated and reproduced.)
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As both Miyamoto and Sakassi are from the same field of endeavor, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify Miyamoto to include the odor information is a set of divided circles obtained by dividing a circle according to intensity of the reference odors, in the context of information processing, according to the teaching of Sakassi, in order to display fluctuation of fragrance (para. [0001] of Sakassi).
Regarding claim 14, Miyamoto does not disclose the information processing method according to claim 13, wherein: the odor information is a slide image or a moving image.
Sakassi more explicitly teaches the information processing method according to claim 13, wherein: the odor information is a slide image or a moving image. (para. [0008], “The first aspect relates to an aroma fluctuation display method. The aroma fluctuation display method according to the first aspect includes a first moving image showing a temporal change in appearance of an object and a second moving image showing in chronological change in the amount or ratio of the aroma component corresponding to the object in a graph form And outputs a display in which time series are associated and reproduced.”)
As both Miyamoto and Sakassi are from the same field of endeavor, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify Miyamoto to include the odor information is a set of divided circles obtained by dividing a circle according to intensity of the reference odors, in the context of information processing, according to the teaching of Sakassi, in order to display fluctuation of fragrance (para. [0001] of Sakassi).
Claim 11 is rejected under 35 U.S.C. 103 as being unpatentable over Miyamoto et al. (US 20210134397 A1) (hereinafter Miyamoto) in view of Sakassi (JP 2018031882 A; IDS REF) (hereinafter Sakassi) and further in view of Tamura et al. (US 20230090065 A1) (hereinafter Tamura).
Regarding claim 11, the combination of Miyamoto and Sakassi discloses the information processing method according to claim 9,wherein: FIG.2 and FIG.8 are illustrated in black and white but different hatched variation of bars or circle. Sakassi further teaches the graphs could be displayed using colored display methods as discussed in claim 9)
The combination of Miyamoto and Sakassi does not explicitly disclose the information processing method according to claim 9,wherein:
a color shade of each of the objects differs depending on intensity
However, Tamura more explicitly teaches the information processing method according to claim 9,wherein:
a color shade of each of the objects differs depending on intensity (fig. 7B, para. [0037], “FIG. 7B is an illustration showing an example of colors for odors output in real time and time dependency of RGB values in the examples. The horizontal axis represents time (unit: second), and the vertical axis represents RGB values.”)
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As Miyamoto, Sakassi, and Tamura are from the same field of endeavor, it would
have been obvious to one of the ordinary skill in the art before the effective filing date of
the claimed invention to include a color shade of each of the objects differs depending on intensity, in the context of information processing, by the combination of Miyamoto and Sakassi according to the teaching of Tamura in order to represent or present many kinds of odors in a form perceivable by a perception other than olfaction, for example, in color. (para. [0001] of Tamura)
Conclusion
Any inquiry concerning this communication or earlier communications from the examiner should be directed to Hyorim Park whose telephone number is (571)272-3859. The examiner can normally be reached Monday - Friday.
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, Alicia Harrington can be reached at (571) 272-2330. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
Information regarding the status of published or unpublished applications may be obtained from Patent Center. Unpublished application information in Patent Center is available to registered users. To file and manage patent submissions in Patent Center, visit: https://patentcenter.uspto.gov. Visit https://www.uspto.gov/patents/apply/patent-center for more information about Patent Center and https://www.uspto.gov/patents/docx for information about filing in DOCX format. For additional questions, contact the Electronic Business Center (EBC) at 866-217-9197 (toll-free). If you would like assistance from a USPTO Customer Service Representative, call 800-786-9199 (IN USA OR CANADA) or 571-272-1000.
/Hyorim Park/Examiner, Art Unit 2615
/ALICIA M HARRINGTON/Supervisory Patent Examiner, Art Unit 2615
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