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. Status of the Claims Claims 1-14 are pending and under consideration in this action. Priority The instant application is a 371 of PCT / JP2020 /042404 , filed 11/13/2020 , which claims priority to Japanese Application Number 2019-209936 , filed 11/20/2019 , as reflected in the filing receipt mailed on 8/23/2022 . Acknowledgment is made of applicant' s claim for foreign priority under 35 U.S.C. 119 (a)-(d). Receipt is acknowledged of certified copies of papers required by 37 CFR 1.55. The claims to the benefit of priority are acknowledged and the effective filing date of claims 1-14 is 11/20/2019 . Information Disclosure Statement The information disclosure statements (IDS) submitted on 5/12/2022, 7/22/2025, 10/13/2025, and 10/13/2025 are in compliance with the provisions of 37 CFR 1.97. Accordingly, the IDS’s have been considered by the examiner. Drawings The drawings are objected to because of the following informalities: In Fig. 2, the “Fluorescent Dye Amount” is labeled as “FS” in the local environment and “FC” in the cloud environment. In Fig. 3, the “Fluorescent Dye Amount” is labeled as “FS” in both the local and cloud environments, but is labeled as “FC” in Para. [0024] of the specification. In Fig. 12, the “Fluorescent Dye Amount” is labeled as “FS” in both the local and cloud environments, but is labeled as “FC” in Para. [0088] of the specification. In Fig. 13, the “Flow Cytometer” is labeled as 100, but is labeled as “10” in Figs. 5 and 10. Corrected drawing sheets in compliance with 37 CFR 1.121(d) are required in reply to the Office action to avoid abandonment of the application. Any amended replacement drawing sheet should include all of the figures appearing on the immediate prior version of the sheet, even if only one figure is being amended. The figure or figure number of an amended drawing should not be labeled as “amended.” If a drawing figure is to be canceled, the appropriate figure must be removed from the replacement sheet, and where necessary, the remaining figures must be renumbered and appropriate changes made to the brief description of the several views of the drawings for consistency. Additional replacement sheets may be necessary to show the renumbering of the remaining figures. Each drawing sheet submitted after the filing date of an application must be labeled in the top margin as either “Replacement Sheet” or “New Sheet” pursuant to 37 CFR 1.121(d). If the changes are not accepted by the examiner, the applicant will be notified and informed of any required corrective action in the next Office action. The objection to the drawings will not be held in abeyance. Specification The abstract of the disclosure is objected to because it is 160 word s in length . The abstract should be within the range of 50 to 150 words. A corrected abstract of the disclosure is required and must be presented on a separate sheet, apart from any other text. See MPEP § 608.01(b). Claim Rejections - 35 USC § 101 35 U.S.C. 101 reads as follows: Whoever invents or discovers any new and useful process, machine, manufacture, or composition of matter, or any new and useful improvement thereof, may obtain a patent therefor, subject to the conditions and requirements of this title. Claims 1-14 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more. The claims recite both (1) mathematical concepts (mathematical relationships, formulas or equations, or mathematical calculations) and (2) mental processes, i.e., concepts performed in the human mind (including observations, evaluations, judgements or opinions) (see MPEP § 2106.04(a)). Step 1: In the instant applicat ion, claims 1-13 are directed towards a system and claim 14 is directed towards a machine , which falls into one of the categories of statutory subject matter ( Step 1: YES ). Step 2A , Prong One: In accordance with MPEP § 2106, claims found to recite statutory subject matter ( Step 1: YES ) are then analyzed to determine if the claims recite any concepts that equate to an abstract idea, law of nature or natural phenomenon ( Step 2A , Prong One ). The following instant claims recite limitations that equate to one or more categories of judicial exceptions: Claim 1 recites a mathematical concept (i.e., an algorithm for compression of data) in “performing compression processing on measurement data measured by the irradiation, using reference data for each of the fluorescent dyes used for dyeing the measurement target” and a mathematical concept (i.e., an algorithm for restoring compressed data) in “performing restoration processing using the reference data and the compressed data received from the first information processing apparatus ” . Claim 2 recites a mental process (i.e., an observation of the measurement target) in “wherein the measurement target is a biogenic particle including at least one of a cell, a tissue, a microorganism, or a bio-related particle”. Claim 4 recites a mathematical concept (i.e., algorithms for linear or nonlinear compression) in “wherein the compression processing includes at least one of linear processing or nonlinear processing ” . Claim 5 recites a mathematical concept (i.e., algorithms for dimension compression processing, clustering or grouping processing) in “wherein the compression processing includes at least one of dimension compression processing, clustering processing or grouping processing ” . Claim 6 recites a mental process (i.e., an evaluation of the composition of the compressed data) in “wherein the compressed data is a fluorescent dye amount representing a measurement result for each of the fluorescent dyes used for dyeing the measurement target ” . Claim 7 recites a mathematical concept (i.e., an algorithm for inverse transformation) in “wherein the restoration processing is inverse transformation processing of the compressed data ” . Claim 8 recites a mathematical concept (i.e., an algorithm for compression of data) in “wherein the first processing unit performs the compression processing on the measurement data using dummy reference data in addition to the reference data to generate dummy compressed data in which dummy data is added to the compressed data” ; and a mathematical concept (i.e., an algorithm for restoring compressed data) in “the second processing unit generates the restored data by performing the restoration processing using the reference data, the dummy compressed data, and the dummy reference data ” . Claim 9 recites a mathematical concept (i.e., an algorithm for inverse transformation and calculation of differences between two datasets) in “wherein the first processing unit further restores the measurement data by performing inverse transformation of unmixing using the compressed data and the reference data and generates difference information representing a difference between restored measurement data that is the restored measurement data and the measurement data ” ; and a mathematical concept (i.e., applying an algorithm to correct the restored measurement data) in “ the second processing unit further corrects the restored measurement data on a basis of the difference information” . Claim 10 recites a mental process (i.e., an evaluation of the two data sets for the measurement target) in “an analysis processing unit configured to analyze the measurement target using the compressed data and restored measurement data that is the measurement data obtained by restoring the compressed data ”. Claim 11 recites a mathematical concept (i.e., an algorithm to sort the data) in “ a learning unit configured to construct a learning model for determining a sorting target by performing machine learning using the measurement data corresponding to the sorting target specified on a basis of an analysis result by the analysis processing unit”; a mental process (i.e., an evaluation of the sorting target based on the output of the model) in “a determination unit configured to determine the sorting target on a basis of the learning model”. Claim 14 recites a mathematical concept (i.e., an algorithm for compression of data) in “performing compression processing on measurement data, using reference data for each of the fluorescent dyes used for dyeing the measurement target” and a mathematical concept (i.e., an algorithm for restoring compressed data) in “performing restoration processing using the reference data and the compressed data ” . These recitations are similar to the concepts of collecting information, and displaying certain results of the collection and analysis is Electric Power Group, LLC, v. Alstom (830 F.3d 1350, 119 USPQ2d 1739 (Fed. Cir. 2016)), comparing information regarding a sample or test to a control or target data in Univ. of Utah Research Found. v. Ambry Genetics Corp. (774 F.3d 755, 113 U.S.P.Q.2d 1241 (Fed. Cir. 2014)) and Association for Molecular Pathology v. USPTO (689 F.3d 1303, 103 U.S.P.Q.2d 1681 (Fed. Cir. 2012)), and organizing and manipulating information through mathematical correlations in Digitech Image Techs., LLC v Electronics for Imaging, Inc. (758 F.3d 1344, 111 U.S.P.Q.2d 1717 (Fed. Cir. 2014)) that the courts have identified as concepts that can be practically performed in the human mind or mathematical relationships. The abstract ideas recited in the claims are evaluated under the broadest reasonable interpretation (BRI) of the claim limitations when read in light of and consistent with the specification, and are determined to be directed to mental processes that in the simplest embodiments are not too complex to practically perform in the human mind. Additionally, the recited limitations that are identified as judicial exceptions from the mathematical concepts grouping of abstract ideas are abstract ideas irrespective of whether or not the limitations are practical to perform in the human mind. The instant claims must therefore be examined further to determine whether they integrate the abstract idea into a practical application ( Step 2A , Prong One: YES ). Step 2A , Prong Two: In determining whether a claim is directed to a judicial exception, further examination is performed that analyzes if the claim recites additional elements that when examined as a whole integrates the judicial exception(s) into a practical application (MPEP § 2106.04(d)). A claim that integrates a judicial exception into a practical application will appl y , rely on, or use the judicial exception in a manner that imposes a meaningful limit on the judicial exception. The claimed additional elements are analyzed to determine if the abstract idea is integrated into a practical application (MPEP § 2106.04(d)(I)). If the claim contains no additional elements beyond the abstract idea, the claim fails to integrate the abstract idea into a practical application ( MPEP § 2106.04(d)(III)). The following claims recite limitations that equate to additional elements: Claim 1 recites “a first information processing apparatus ” ; “ a second information processing apparatus”; “a first processing unit configured to generate compressed data”; “ measured by irradiating a measurement target dyed with a plurality of fluorescent dyes with light”; “a transmission unit configured to transmit the compressed data to the second information processing apparatus”; and “a second processing unit configured to generate restored data”. Claim 3 further recites “wherein the first information processing apparatus and the second information processing apparatus are connected so as to be able to perform communication with each other via a predetermined network”. Claim 8 further recites “the transmission unit transmits the dummy compressed data and the dummy reference data to the second information processing apparatus”. Claim 9 further recites “the transmission unit further transmits the difference information to the second information processing apparatus” ; and “the second information processing apparatus further receives the difference information from the first information processing apparatus”. Claim 11 further recites “a learning model transmission unit configured to transmit the learning model to the first information processing apparatus” and “a learning model reception unit configured to receive the learning model from the second information processing apparatus”. Claim 12 further recites “wherein the measurement data is a fluorescence signal obtained by measuring fluorescence emitted from the measurement target”. Claim 13 further recites “wherein the measurement data is image data obtained by imaging the measurement target”. Claim 14 recites “a first processing unit configured to generate compressed data”; “ measured by irradiating a measurement target dyed with a plurality of fluorescent dyes with light”; and “a second processing unit configured to generate restored data”. Regarding the above cited limitations in claims 1 and 14 of ( i ) a first information processing apparatus (claim 1) ; (ii) a second information processing apparatus (claim 1) ; (iii) a first processing unit configured to generate compressed data (claims 1 and 14) ; and (iv) a second processing unit configured to generate restored data (claims 1 and 14) . These limitations require only a generic computer component, which does not improve computer technology. Therefore, these limitations equate to mere instructions to implement an abstract idea on a generic computer, which the courts have established does not render an abstract idea eligible in Alice Corp. 573 U.S. at 223, 110 USPQ2d at 1983. Regarding the above cited limitations in claims 1, 3, 8 - 9, and 11-14 of (v) wherein the first information processing apparatus and the second information proc essing apparatus are connected so as to be able to perform communication with each other via a predetermined network (claim 3); (vi) measured by irradiating a measurement target dyed with a plurality of fluorescent dyes with light (claims 1 and 14); (vii) a transmission unit configured to transmit the compressed data to the second information processing apparatus (claim 1); (viii) the transmission unit transmits the dummy compressed data and the dummy reference data to the second information processing apparatus (claim 8); (ix) the transmission unit further transmits the difference information to the second information processing apparatus (claim 9 ) ; (x) the second processing unit further corrects the restored measurement data on a basis of the difference information (claim 9 ); (xi) a learning model transmission unit configured to transmit the learning model to the first information processing apparatus (claim 11 ); (xii) a learning model reception unit configured to receive the learning model from the second information processing apparatus (claim 11 ); (xi ii ) wherein the measurement data is a fluorescence signal obtained by measuring fluorescence emitted from the measurement target (claim 12); and (x i v) wherein the measurement data is image data obtained by imaging the measurement target (claim 13) . These limitations equate to insignificant, extra-solution activity of mere data gathering because these limitations gather data before or after the recited judicial exceptions of performing restoration processing using the reference data and compressed data (see MPEP § 2106.04(d)). As such, claims 1-14 are directed to an abstract idea ( Step 2A , Prong Two: NO ). Step 2B : Claims found to be directed to a judicial exception are then further evaluated to determine if the claims recite an inventive concept that provides significantly more than the judicial exception itself ( Step 2B ). The claims do not include additional elements that are sufficient to amount to significantly more than the judicial exception because the claims recite additional elements that equate to well-understood, routine and conventional ( WURC ) limitations ( MPEP § 2106.05(d)). The instant claims recite same additional elements described in Step 2A , Prong Two above. Regarding the above cited limitations in claims 1 and 14 of ( i ) a first information processing apparatus (claim 1); (ii) a second information processing apparatus (claim 1); (iii) a first processing unit configured to generate compressed data (claims 1 and 14); and (iv) a second processing unit configured to generate restored data (claims 1 and 14) . These limitations equate to instructions to implement an abstract idea on a generic computing environment, which the courts have established does not provide an inventive concept (see MPEP § 2106.05(d) and MPEP § 2106.05(f)). Regarding the above cited limitations in claims 1, 3, 8-9, and 11 of (v) wherein the first information processing apparatus and the second information proc essing apparatus are connected so as to be able to perform communication with each other via a predetermined network (claim 3); (vii) a transmission unit configured to transmit the compressed data to the second information processing apparatus (claim 1); (viii) the transmission unit transmits the dummy compressed data and the dummy reference data to the second information processing apparatus (claim 8); (ix) the transmission unit further transmits the difference information to the second information processing apparatus (claim 9); (xi) a learning model transmission unit configured to transmit the learning model to the first information processing apparatu s (claim 11); and (xii) a learning model reception unit configured to receive the learning model from the second information processing apparatus (claim 11) . These limitations equate to receiving/transmitting data over a network, which the courts have establishe d as a WURC limitation of a generic computer in buySAFE , Inc. v. Google, Inc ., 765 F.3d 1350, 1355, 112 USPQ2d 1093, 1096 (Fed. Cir. 2014). Regarding the above cited limitations in claims 1 and 12-14 of (vi) measured by irradiating a measurement target dyed with a plurality of fluorescent dyes with light (claims 1 and 14); (xi ii ) wherein the measurement data is a fluorescence signal obtained by measuring fluorescence emitted from the measurement target (claim 12); and (x i v) wherein the measurement data is image data obtained by imaging the measurement target (claim 13) . These limitations are considered to be insignificant extra-solution activity of mere data gathering. These steps are incidental to the primary process of performing restoration processing using the reference data and compressed data , wherein measured data are merely inputs for the compression algorithm (see MPEP § 2106.05(g)). These additional elements do not comprise an inventive concept when considered individually or as an ordered combination that transforms the claimed judicial exception into a patent-eligible application of the judicial exception. Therefore, the instant claims do not amount to significantly more than the judicial exception itself ( Step 2B : NO ). As such, claims 1-14 are not patent eligible . 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. The factual inquiries for establishing a background for determining obviousness under 35 U.S.C. 103 are summarized as follows: 1. Determining the scope and contents of the prior art. 2. Ascertaining the differences between the prior art and the claims at issue. 3. Resolving the level of ordinary skill in the pertinent art. 4. Considering objective evidence present in the application indicating obviousness or nonobviousness . Claims 1- 3 , 6, and 12-14 are rejected under 35 U.S.C. 103 as being unpatentable over Weisberg et al. (WIPO Application, WO 2015/101992 A2 ; published 7/9/2015) in view of Kato et al. (US Patent Application Publication, US 2014/0365159 A1; published 12/11/2014) . Regarding claim 1, Weisberg et al. teaches an apparatus to measure spectra of an object with a spectrometer and a mobile communication device. The mobile communication device may comprise a processor and wireless communication circuitry to couple to the spectrometer and communicate with a remote server, the processor comprising instructions to transmit spectral data of an object to a remote server and receive object data in response to the spectral data from the remote server (i.e., the mobile communication device is a first information processing apparatus and the remote server is a second information processing apparatus ) (Pg. 3, Lines 16-21). Weisberg et al. further teaches that the mobile communication device comprises a user interface coupled to the processor for the user to input commands to the spectrometer (Pg. 4, Lines 5-6). The spectral data comprises compressed spectral data and the processor comprises instructions to transmit the compressed spectral data to the remote server (i.e., a first processing unit configured to generate compressed data and a transmission unit configured to transmit the compressed data to the second information processing apparatus ) (Pg. 4, Lines 16-18). Weisberg et al. further teaches that the spectrometer can be a hand held spectrometer with wavelength multiplexing in which a plurality of wavelengths are used to illuminate the object and measure the one or more spectra (Pg. 3, Lines 6-8). The optical spectrometer measures spectra of a sample with a plurality of light sources, and the light spectrum can be a fluorescence spectrum (i.e., irradiating a measurement target with light ) (Pg. 12, Lines 1-2 and Pg. 25, Lines 9-10). Weisberg et al. further teaches that the compression may be performed using a data compression algorithm tailored according to the physical properties of the optical system that create s the spatial distribution of light onto the light detector of the spectrometer module. The data generated by the optical system described herein typically contains symmetries that allow significant compression of the raw data into much more compact data structures (i.e., performing compression processing on measurement data measured by the irradiation ) (Pg. 59, Lines 26-31). Weisberg et al. further teaches that the processor or communication interface of the cloud server can then decrypt the compressed data, and a digital signal processing unit of the cloud server can perform signal processing on the decrypted signal to transform the signal into spectral data. The server may perform additional pre-processing of the spectrum, such as noise reduction, to produce pre-processed spectral data. Analysis of the pre-processed spectrum can then be performed by a processor of the server having instructions stored thereon for performing various data analysis algorithms. In addition, the analyzed spectral data and/or related additional analysis results may be dynamically added to a universal database operated by the cloud server, where spectral data associated with sample materials may be stored. The spectral data stored on the database may comprise data generated by the one or more users of the spectrometer system, and/or pre-loaded spectral data of materials with known spectra (i.e., the reference data ). The cloud server may comprise a memory having the database stored thereon (i.e., a second processing unit configured to generate restored data by performing restoration processing using the reference data and the compressed data received from the first information processing apparatus ) (Pg. 60, Line 29 – Pg. 61, Line 12). Regarding claim 2, Weisberg et al. teaches that the spectrometer can be used to analyze skin for various properties (i.e., wherein the measurement target is a biogenic particle including at least one of a tissue ) (Pg. 80, Line 7). Regarding claim 3, Weisberg et al. teaches that the spectrometer system typically comprises a spectrometer as described herein and a hand held device in wireless communication with a cloud based server or storage system. The spectrometer can then send the data to a hand held device, for example via communication circuitry having a communication link such as Bluetooth™. The hand held device can transmit the data to the cloud based storage system. The data can be processed and analyzed by the cloud based server, and transmitted back to the hand held device to be displayed to the user. The hand held device may comprise one or more of a smartphone, tablet, or smartwatch, for example. In some embodiments, a single device having internet connectivity is configured to communicate with the spectrometer on the one hand and with the cloud based server on the other hand. In some embodiments, the spectrometer system comprises two or more hand held devices, connected via Bluetooth communication and/or internet connection (i.e., wherein the first information processing apparatus and the second information processing apparatus are connected so as to be able to perform communication with each other via a predetermined network ) (Pg. 58, Lines 4-24). Regarding claim 12, Weisberg et al. teaches that the spectrometers as described herein can be adapted, with proper choice of light source, detector, and associated optics, for a use with a wide variety of spectroscopic techniques, including fluorescence (i.e., wherein the measurement data is a fluorescence signal obtained by measuring fluorescence emitted from the measurement target ) (Pg. 33, Lines 31 – Pg. 34, Line 2). Regarding claim 13, Weisberg et al. teaches that the system further includes an image capture device configured to acquire image data representative of the environment. The image capture device can include a camera, wherein the at least one processing device is further configured to: receive the image data acquired by the image capture device; and use at least a portion of the image data in the selection of the first type of analysis or the second type of analysis (i.e., wherein the measurement data is image data obtained by imaging the measurement target ) (Pg. 21, Lines 15-20). Regarding claim 14, Weisberg et al. teaches the limitations of a first processing unit configured to generated compressed data by performing compression processing on measurement data measured by irradiating a measurement target with light and a second processing unit configured to generate restored data by performing restoration processing using the reference data and the compressed data as described for claim 1 above. Weisberg et al. does not teach a measurement target dyed with a plurality of fluorescent dyes ; using reference data for each of the fluorescent dyes used for dyeing the measurement target ; and wherein the compressed data is a fluorescent dye amount representing a measurement result for each of the fluorescent dyes used for dyeing the measurement target . Regarding claims 1 and 14, Kato et al. teaches a fluorescence intensity calculating apparatus for fluorescence generated from a microparticle individually labeled with fluorescent dyes (i.e., irradiating a measurement target dyed with a plurality of fluorescent dyes with light ) (Abstract). Kato et al. further teaches that “the single-dyeing spectra" are fluorescence wavelength distributions of the respective fluorescent dyes, and are obtained by receiving fluorescence generated from fluorescent dyes excited by radiating a light to a microparticle individually labeled with fluorescent dyes by photodetectors, respectively, and by collecting detected values from the respective photo detectors (i.e ., using reference data for each of the fluorescent dyes used for dyeing the measurement target ) (Para. [0047]). Regarding claim 6, Kato et al. teaches that "the measured spectra" are obtained by receiving fluorescence generated from fluorescent dyes excited by radiating a light to a microparticle multiply-labeled with plural fluorescent dyes having fluorescence wavelength bands overlapping one another by photodetectors which correspond to different received light wavelength bands and which number is larger than the number of fluorescent dyes, and collecting detected values from the respective photodetectors (i.e., wherein the compressed data is a fluorescent dye amount representing a measurement result for each of the fluorescent dyes used for dyeing the measurement target ) (Para. [0047]). Therefore, regarding claims 1- 3 , 6, and 12-14, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the apparatus coupling a fluorescence spectrometer to a remote server of Weisberg et al. with the measurement of fluorescent dyes of Kato et al. because the method of Kato et al., incorporating multiple fluorescent dyes and photodetectors, makes it possible to precisely calculate the fluorescence intensities from the respective fluorescent dyes. This allows the characteristics of the target to be more precisely analyzed ( Kato et al., Para. [0090]) . One of ordinary skill in the art would be able to combine the teachings of Weisberg et al. with Kato et al. with reasonable expectation of success due to the same nature of the problem to be solved, since both are drawn towards an analysis method for fluorescence spectra . Therefore, regarding claims 1- 3 , 6, and 12-14, the instant invention is prima facie obvious (MPEP § 2142). Claims 4-5 are rejected under 35 U.S.C. 103 as being unpatentable over Weisberg et al. in view of Kato et al. as applied to claims 1-3, 6, and 12-14 above, and further in view of Kaiser et al. (U.S. Patent Application Publication, US 2013/0266959 A1; published 10/10/2013). Weisberg et al. in view of Kato et al. , as applied to claims 1-3, 6, and 12-14 above, does not teach wherein the compression processing includes at least one of linear processing or nonlinear processing ; and wherein the compression processing includes at least one of dimension compression processing, clustering processing or grouping processing . Regarding claim 4, Kaiser et al. teaches a method of data compression using principal component analysis ( PCA ) to analyze spectra from flow cytometry systems (i.e., wherein the compression processing includes at least one of linear processing ) (Para. [0030] and [0052]). Regarding claim 5, Kaiser et al. teaches that the data generated by flow-cytometers can be plotted in a single dimension, to produce a histogram, or in two-dimensional dot plots (Para. [0006]). Kaiser et al. further teaches data compression using PCA as described for claim 4 above (i.e., wherein the compression processing includes at least one of dimension compression processing ). Therefore, regarding claims 4-5, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the apparatus coupling a fluorescence spectrometer to a remote server of Weisberg et al. in view of Kato et al. with the compression analysis of Kaiser et al. because incorporating PCA , according to the method of Kaiser et al., provides a cost-effective and practical method for improving the data acquisition and quality of data acquired on existing flow cytometry devices (Kaiser et al., Para. [0036]) . One of ordinary skill in the art would be able to combine the teachings of Weisberg et al. in view of Kato et al. with Kaiser et al. with reasonable expectation of success due to the same nature of the problem to be solved, since both incorporate a method for spectral compression processing . Therefore, regarding claims 4-5, the instant invention is prima facie obvious (MPEP § 2142). Claim 7 is rejected under 35 U.S.C. 103 as being unpatentable over Weisberg et al. in view of Kato et al. as applied to claims 1-3, 6, and 12-14 above, and further in view of Gallagher et al. ( WIPO Application , WO 20 09 / 006696 A1; published 1 /1 5 /20 09 ). Weisberg et al. in view of Kato et al. , as applied to claims 1-3, 6, and 12-14 above, does not teach wherein the restoration processing is inverse transformation processing of the compressed data . Regarding claim 7, Gallagher et al. teaches that de con volution can be performed by applying the inverse transformation in the principal component analysis ( PCA ) approach (i.e., wherein the restoration processing is inverse transformation processing of the compressed data ) (Pg. 17, Lines 5-12). Therefore, regarding claim 7 , it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the apparatus coupling a fluorescence spectrometer to a remote server of Weisberg et al. in view Kato et al. with the restoration processing of Gallagher et al. because robust automated systems with proven analysis algorithms (i.e., PCA and inverse transformation processing) can provide quantitative analysis for use in pathology laboratories or clinical studies (Gallagher et al., Pg. 2, Lines 3-19) . One of ordinary skill in the art would be able to combine the teachings of Weisberg et al. in view of Kato et al. with Gallagher et al. with reasonable expectation of success due to the same nature of the problem to be solved, since both incorporate a method of restoring compressed data . Therefore, regarding claim 7 , the instant invention is prima facie obvious (MPEP § 2142). Claims 10-11 are rejected under 35 U.S.C. 103 as being unpatentable over Weisberg et al. in view of Kato et al. as applied to claims 1-3, 6, and 12-14 above, and further in view of Yamane et al. ( WIPO Application , WO 2018 / 198586 A1; published 11 /1/20 18; provided in the IDS dated 5/12/2022 ). Regarding claim 10, Weisberg et al. teaches the compressed data and restored measurement data that is the measurement data obtained by restoring the compressed data as described for claim 1 above. Regarding claim 11, Weisberg et al. teaches that a user may may also provide instructions to the user interface (UI) to perform one or more specific types of analysis; in this case, the UI may transmit, along with the compressed, encrypted raw data and/or metadata, user instructions for performing the analysis (i.e., a learning model transmission unit configured to transmit the learning model to the first information processing apparatus ) (Pg. 60, Lines 23-26). Weisberg et al. further teaches t hat the processor comprises instructions to transmit control instructions to the remote server and to receive control instructions from the remote server. The remote server can comprise a cloud based server. The remote server can comprise a database and a tangible medium embodying instructions of an algorithm (i.e., a learning model reception unit configured to receive the learning model from the second information processing apparatus ) (Pg. 4, Lines 22-25), Weisberg et al. in view of Kato et al. , as applied to claims 1-3, 6, and 12-14 above, does not teach an analysis processing unit configured to analyze the measurement target ; a learning unit configured to construct a learning model for determining a sorting target by performing machine learning using the measurement data corresponding to the sorting target specified on a basis of an analysis result by the analysis processing unit ; and a determination unit configured to determine the sorting target on a basis of the learning model. Regarding claim 10, Yamane et al. teaches that the information processing device includes an analysis unit (i.e., wherein the second information processing apparatus includes an analysis processing unit ) (Para. [0008]). Yamane et al. further teaches that the analysis unit calculates fluorescent dye information, which is the emission amount of each of multiple types of fluorescent dyes, based on detection data, which is the emission amount for each wavelength band of fluorescence emitted from microparticles irradiated with excitation light, and determines whether or not to process the microparticle based on the fluorescent dye information, and generates training data by associating the determination result with the detection data (Para. [0008]). The analysis unit calculates fluorescent dye information from the detection data detected for the particles, and uses the fluorescent dye information to determine whether the particles are to be processed (for example, to be sorted) (i.e ., an analysis processing unit configured to analyze the measurement target using the data ) (Para. [0009]). Regarding claim 11, Yamane et al. teaches that th e information processing device includes an analyzing unit, a learning unit, and a determination unit (i.e., wherein the second information processing apparatus includes a learning unit and a determination unit ) ( Abstract ). The learning unit uses machine learning to learn what kind of detection data belongs to the particle to be processed (whether the fluorescent dye information calculated from the detection data satisfies a predetermined condition). In the sorting phase, the discrimination unit uses the learning results to determine whether the supplied detection data is that of the particles to be processed (i.e., a learning unit configured to construct a learning model for determining a sorting target by performing machine learning using the measurement data corresponding to the sorting target specified on a basis of an analysis result by the analysis processing unit ) (Para. [0009]). Yamane et al. further teaches that the determination unit determines whether or not a cell is a processing target (i.e., a determination unit configured to determine the sorting target on a basis of the learning model ) (Para. [0102]). Therefore, regarding claim s 10-11 , it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the apparatus coupling a fluorescence spectrometer to a remote server of Weisberg et al. in view of Kato et al. with the analysis, learning, and determination units of Yamane et al. because the analysis, learning, and determination units of Yamane et al. make it possible to determine whether a cell is a processing target directly from the measurement data without calculating the fluorescent dye information in the sorting phase . This eliminates the need for a large amount of processing, and makes it possible to distinguish cells in a shorter time period, i.e., immediately after fluorescence observation in the flow cytometer (Yamane et al., Para. [0071]) . One of ordinary skill in the art would be able to combine the teachings of Weisberg et al. in view of Kato et al. with Yamane et al. with reasonable expectation of success due to the same nature of the problem to be solved, since both incorporate a method for processing and analyzing measured fluorescence spectra . Therefore, regarding claim s 10-11 , the instant invention is prima facie obvious (MPEP § 2142). Conclusion No claims allowed. Claims 8 and 9 are free from the prior art because the prior art does not fairly suggest or teach wherein the compression processing uses dummy reference data, which is incorporated into the compressed data; generating restored data using the dummy compressed data; restoring the measurement data by generating difference information between the restored data and the original measurement data; or correcting the restored measurement using the difference information . The closest prior art is Weisberg et al. (WIPO Application, WO 2015/101992 A2 ) . Weisberg et al. discloses an apparatus containing a fluorescence spectrometer and mobile communication device to communicate with a remote server . The apparatus generates compressed data to send to the server and the server subsequently decrypts and restores the compressed data. However, Weisberg et al. does not teach wherein the first processing unit performs the compression processing on the measurement data using dummy reference data in addition to the reference data to generate dummy compressed data in which dummy data is added to the compressed data ; the second processing unit generates the restored data by performing the restoration processing using the reference data, the dummy compressed data, and the dummy reference data ; wherein the first processing unit further restores the measurement data by performing inverse transformation of unmixing using the compressed data and the reference data and generates difference information representing a difference between restored measurement data that is the restored measurement data and the measurement data ; and the second processing unit further corrects the restored measurement data on a basis of the difference information as disclosed in instant claim s 8 and 9 . Inquiries Any inquiry concerning this communication or earlier communications from the examiner should be directed to FILLIN "Examiner name" \* MERGEFORMAT DIANA P SANFORD whose telephone number is FILLIN "Phone number" \* MERGEFORMAT (571)272-6504 . The examiner can normally be reached FILLIN "Work Schedule?" \* MERGEFORMAT Mon-Fri 8am-5pm EST . 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, FILLIN "SPE Name?" \* MERGEFORMAT Karlheinz Skowronek can be reached at FILLIN "SPE Phone?" \* MERGEFORMAT (571)272-9047 . 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. /D.P.S./ Examiner, Art Unit 1687 /Karlheinz R. Skowronek/ Supervisory Patent Examiner, Art Unit 1687