An object recognition apparatus includes a first spectrometer configured to obtain a first type of spectrum data from light scattered, emitted, or reflected from an object; a second spectrometer configured to obtain a second type of spectrum data from the light scattered, emitted, or reflected from the object, the second type of spectrum data being different from the first type of spectrum data; an image sensor configured to obtain image data of the object; and a processor configured to identify the object using data obtained from at least two from among the first spectrometer, the second spectrometer, and the image sensor and using at least two pattern recognition algorithms.

An apparatus includes an integrated waveguide structure, and a first light source operable to produce a probe beam having a first wavelength, wherein the probe beam is coupled into a first end of the waveguide structure. A second light source is operable to produce an excitation beam with having a second wavelength to excite gas molecules in close proximity to a path of the probe beam. A light detector is coupled to a second end of the integrated waveguide structure and is operable to detect the probe beam after it passes through the waveguide structure. The apparatus is operable such that excitation of the gas molecules results in a temperature increase of the gas molecules that induces a change in the probe beam that is measurable by the light detector.

A multimode biological sample inspection apparatus and method is provided. The apparatus includes illumination hardware arrangement including transmission and sensing hardware, the illumination hardware arrangement configured to inspect a biological sample using at least two modes from a fluorescence imaging mode, a reflectance imaging mode, a scattering imaging mode, and a Raman imaging mode, and processing hardware configured to operate the illumination hardware arrangement according to a protocol including inspection settings of the at least two modes. The processing hardware receives scan results from the illumination hardware arrangement and identifies attributes of the biological sample. The processing hardware is configured to employ the attributes of at least one biological sample to alter the protocol.

An object recognition apparatus includes a first spectrometer configured to obtain a first type of spectrum data from light scattered, emitted, or reflected from an object; a second spectrometer configured to obtain a second type of spectrum data from the light scattered, emitted, or reflected from the object, the second type of spectrum data being different from the first type of spectrum data; an image sensor configured to obtain image data of the object; and a processor configured to identify the object using data obtained from at least two from among the first spectrometer, the second spectrometer, and the image sensor and using at least two pattern recognition algorithms.

An automatic analysis device has a plurality of types of photometers having different quantitative ranges, and an analysis control unit for quantifying the desired component in specimens based on measurement values of one or more photometers selected from among the plurality of types of photometers. The analysis control unit: sets a switching region in an overlap region of respective quantitative ranges of the plurality of types of photometers, said switching region having a greater width than does the variation in quantitative values of the desired component based on the measurement values of photometers having the same specimen; compares the quantitative value of a quantitative range portion that corresponds to the switching region and the quantitative values of the desired component based on the measurement values of the photometers; and selects a photometer to be used in quantitative output of the desired component from among the plurality of types of photometers.

An automatic analysis device has a plurality of types of photometers having different quantitative ranges, and an analysis control unit for quantifying the desired component in specimens based on measurement values of one or more photometers selected from among the plurality of types of photometers. The analysis control unit: sets a switching region in an overlap region of respective quantitative ranges of the plurality of types of photometers, said switching region having a greater width than does the variation in quantitative values of the desired component based on the measurement values of photometers having the same specimen; compares the quantitative value of a quantitative range portion that corresponds to the switching region and the quantitative values of the desired component based on the measurement values of the photometers; and selects a photometer to be used in quantitative output of the desired component from among the plurality of types of photometers.

A sample analysis system is provided with: a reference substance database including measurement results and component classification information of reference substances obtained by each analysis device on information of each reference substance; a reference substance designation unit; a measurement result collation unit to obtain the commonality of the components, the difference between the physical quantities of the respective components, and the degree of coincidence of the measurement results for each analysis device for the designated reference substance; an integration coincidence degree calculation unit to obtain an integration degree of coincidence; and a judgment unit to judge whether or not the difference between the contents of contained components is within an allowable range and classify the corresponding component based on the component classification information.

Systems and methods for analyzing an unknown sample are disclosed. The system includes at least one subsystem to obtain molecular information about the sample and at least one other subsystem to obtain elemental information about the sample. The system also includes a data collection component to collect and combine the information from the subsystems to create combined analytical information and a multivariate model that relates known attributes to information previously generated with at least two analytical systems that are the same types of systems as the at least two analytical subsystems. A prediction engine applies the multivariate model to the combined analytical information to produce predictions of attributes in the unknown sample.

A process of analyzing a sample by Raman spectroscopy and X-ray photoelectron spectroscopy (XPS) includes providing a sample having a sample surface within a vacuum chamber, performing a Raman spectroscopic analysis on a plurality of selected areas of the sample surface within the vacuum chamber to map an area of the sample surface comprising the selected areas, the Raman spectroscopic analysis including identifying one or more face in one or more of the selected areas of the sample surface, and performing an X-ray photoelectron spectroscopy (XPS) analysis of one or more selected areas of the sample surface containing at least one chemical and/or structural feature identified by the Raman spectroscopic analysis, wherein the duration of the XPS analysis of a given selected area of the sample surface is longer than the duration of the Raman spectroscopic analysis of that given selected area.

The present disclosure describes a method in which a sample is passed through a fluid flow path of a sensor assembly such that the sample intersects at least one sensor comprising at least three electrodes arranged such that two or more electrodes are opposing and two or more electrodes are beside one another. The sensor is read by a reader monitoring changes to the sensor due to the presence of the sample. The reader measures the presence and/or concentration of one or more analytes within the sample based upon data obtained by the reader.