A method for providing quantitative information for targets and a device using the same according to an exemplary embodiment of the present disclosure are provided. A quantitative information providing method for targets according to the exemplary embodiment of the present disclosure includes flowing a plurality of microdroplets into a chamber or a channel including a detection region acquiring a single layer of microdroplets in which the plurality of microdroplets is present as a single layer, and providing quantitative data of targets based on the single layer image of the microdroplets, and the detection region has a height which is one time to about two times of a diameter of the plurality of microdroplets and is defined as a region in which the plurality of microdroplets is dispersed in a plurality of columns to fill the detection region.

A model can be trained for discriminant analysis for substance classification and/or measuring calibration. One method includes interacting at least one sensor with one or more known substances, each sensor element being configured to detect a characteristic of the one or more known substances, generating an sensor response from each sensor element corresponding to each known substance, wherein each known substance corresponds to a known response stored in a database, and training a neural network to provide a discriminant analysis classification model for an unknown substance, the neural network using each sensor response as inputs and one or more substance types as outputs, and the outputs corresponding to the one or more known substances.

Systems and methods for interpreting high-energy interactions on a sample are described in this application. In particular, this application describes analysis systems and methods, comprising impinging radiation from a source on an analyte, detecting energy interactions resulting from the impinging radiation using a detector, adjusting a signal emitted from the radiation detector using a pre-processing method to emphasize specific features of that signal, using a machine learning module to interpret specific parts of the adjusted signal, producing a quantitative and/or qualitative model using the machine leaning module, and applying the quantitative and/or qualitative model to a separate energy interaction. The quantitative and qualitative models derived from this training can be applied to new detector inputs from the same or similar instruments. Other embodiments are described.

A thin-film deposition system deposits a thin-film on a wafer. A radiation source irradiates the wafer with excitation light. An emissions sensor detects an emission spectrum from the wafer responsive to the excitation light. A machine learning based analysis model analyzes the spectrum and detects contamination of the thin-film based on the spectrum.

Methods and apparatus to generate calibration models in a cloud environment are disclosed. An example apparatus includes training circuitry to generate a calibration model based on a correlation of reference data and spectra, the reference data based on physical samples collected by one or more vehicles, the spectra associated with the physical samples, and distribution circuitry to provide, via a network communication, the calibration model to the one or more vehicles.

Disclosed herein are a method for diagnosing a disease of a body tissue by using LIBS (Laser-Induced Breakdown Spectroscopy) comprising: preparing a laser device including: a laser projection module, outputting the laser to a suspicious region of the body tissue, a light receiving module, receiving a plurality of light, a spectrum measurement module, and a guide unit; and projecting the laser to generate plasma by inducing tissue ablation in the suspicious region; wherein the laser projected to the suspicious region has a target area, and wherein the target area has smaller size than the suspicious region such that the target area is located inside the suspicious region.

A method of training a machine learning model for determining the composition of a mixture includes obtaining, using Fourier-transform infrared (FTIR) spectroscopy, a spectrum for each of a plurality of mixtures its constituent components. A concentration of each constituent component is known for each of the plurality of mixtures. A plurality of features is extracted from each of the obtained spectra. A machine learning model is trained using the plurality of features. An apparatus for determining formation of a product includes a reactor for containing a reaction mixture and an FTIR spectrometer for producing a spectrum of a sample of the reaction mixture. A processor extracts features from the spectrum; provides the features to an ML model trained using a plurality of mixtures of the constituent components to obtain a concentration of one or more of the constituent components; and determines the formation of the product based on the concentration.

Various embodiments of the teachings herein include a method for determining a radiation intensity and/or a wavelength of a process light, wherein the melt pool underlying the process light can be generated by irradiating a metal material with an energy beam along a path, wherein the energy beam can be moved in accordance with a power profile along the path. The method may include: providing a power profile for a section of the path as an input variable for a machine learning model; training the model using historical and/or synthetic power profiles and associated historical or synthetic radiation intensities and/or wavelengths of the process light for the metal material; and determining the radiation intensity and/or the wavelength of the process light as an output variable of the model.

Systems and methods here may be used for a setup of fluorescence image capturing of a gemstone, such as a diamond placed on a flat stage. Some examples utilize a setup that both sends light and captures the image from the table side of the gemstone by passing ultraviolet (UV) light between 10 nm and 400 nm to the gemstone and capturing the excited fluorescence image for analysis through a dichroic beam splitter. In some examples, the cutoff is 300 nm. The dichroic beam splitter arrangement allows for the camera to focus on the same interface of the stage and gemstone over and over for ease of use and without moving, changing, or adjusting the equipment for different samples.

A blood filtering machine having a blood circuit, which has a plurality of ducts made of a transparent material, and a measuring system, which has a plurality of optical sensors coupled to respective ducts. Each optical sensor has a reading window placed in a point of the respective duct, a light emitter and a light receiver. The measuring system comprises one single spectrometer, an optical mixer comprising a plurality of inputs, each connected to the light receiver of a respective one of the optical sensors, and an output, which is connected to an input of the spectrometer, and a control unit is configured to activate the light emitter of one optical sensor at a time so as to measure a parameter of one organic fluid at a time.