An apparatus for analysis of a sample of a material is disclosed. The apparatus has a body configured to accept the sample and a detector with a plurality of points. The detector is configured to provide a signal about the intensities of light received at the points. The apparatus also includes a slit array having a plurality of slits configured to collected light from the accepted sample and a collimating lens array having a plurality of lenses configured to receive the light from the slit array and collimate the collected light. The apparatus also includes a diffraction grating configured to diffract the light received from the collimating lens array and a focusing lens configured to focus the diffracted light of a common frequency on a common point of the detector.

Provided is a portable biosensor that includes a sample filter cartridge, a filter collector, an optical sphere, an electromagnetic radiation emitter, a photo-detector, a processor, a signal display, a vacuum pump, and a power supply. The sample filter cartridge selectively removes small molecules to minimize spectral interference in the detection signal. The sample is concentrated onto the filter collector and subjected to illumination by the electromagnetic radiation emitter, producing Raman-scattering. The optical sphere collects and distributes the Raman-scattering shifts, which then pass through a spectral filter to produce spectral filtered scattering, which is then reflected by the concave holographic flat-field grating onto the photo-detector. The data is displayed graphically to provide the Raman-scattering shift data. The data is compared with a database for sample identification. The device is contained within a housing that is small enough to be easily transported for field use.

A data set is stored in memory circuitry that is indicative of a state of a semiconductor fabrication process or of semiconductor structure fabricated thereby. Features in the data set are discernable to an extent limited by a data resolution. A machine-learning model comprising parameters having respective values assigned thereto as constrained by a model training process is also stored in the memory circuitry. Processor circuitry communicatively coupled to the memory circuitry generates an output data set from the data set in accordance with the machine-learning model such that features in the output data set are discernable to an extent limited by an output data resolution that is finer than the data resolution of the data set.

The present disclosure relates to storing spectroscopy data in layers, including a system having a sensor to generate raw spectroscopy data for an object, a processor to process the raw spectroscopy data in stages to generate multi-stage data using intermediate data at individual stages, and a database to store the intermediate data for individual stages as a multi-dimensional array in an array data model.

An optical measuring device includes a light measurement unit, an acceleration sensor for detecting the acceleration of the optical measuring device, a storage for storing reference data obtained from the light measurement unit by measuring light from a reference object at a first timing and storing the acceleration detected by the acceleration sensor as history information, a first determination unit for determining whether the result of comparison between measurement data obtained from the light measurement unit by measuring light from the reference object at a second timing later than the first timing and the reference data satisfies a first malfunction condition, a second determination unit for determining whether the acceleration included in the history information satisfies a second malfunction condition, and an output unit for outputting that the optical measuring device malfunctions when the first malfunction condition and the second malfunction condition are satisfied.

An auxiliary device and system for traffic light detection and communication. The auxiliary device is positionable adjacent to a traffic light. The auxiliary device includes at least one light pipe positionable adjacent to at least one traffic indicator disposed on a surface of the traffic light. The at least one light pipe is capable of carrying a light output from the least one traffic indicator to the auxiliary device. The auxiliary device includes a sensor for sensing the light output, and a processor operatively connected for computer communication to the sensor. The processor receives a measurement from the sensor. The measurement is associated with the light output. The processor detects a state of the light output based on the measurement, and transmits the state to one or more remote vehicles.

A gas detecting apparatus and a gas detecting method based on terahertz spectroscopy are provided. The apparatus includes a sample chamber allowing a terahertz wave to pass therethrough; a gas feeding unit connected to the sample chamber to feed gas into the sample chamber; a gas outputting unit connected to the sample chamber to output gas from the sample chamber; and a vacuum pump connected to the sample chamber to evacuate the sample chamber. The apparatus further comprises one or more of a pressure gauge disposed on the sample chamber, an anemometer disposed on the sample chamber, a humidity regulation device connected to the sample chamber, and a temperature regulation device connected to the sample chamber.

A hand held spectrometer is used to illuminate the object and measure the one or more spectra. The spectral data of the object can be used to determine one or more attributes of the object. In many embodiments, the spectrometer is coupled to a database of spectral information that can be used to determine the attributes of the object. The spectrometer system may comprise a hand held communication device coupled to a spectrometer, in which the user can input and receive data related to the measured object with the hand held communication device. The embodiments disclosed herein allow many users to share object data with many people, in order to provide many people with actionable intelligence in response to spectral data.

A system for non-invasively interrogating an in vivo sample for measurement of analytes comprises a pulse sensor coupled to the in vivo sample for detect a blood pulse of the sample and for generating a corresponding pulse signal, a laser generator for generating a laser radiation having a wavelength, power and diameter, the laser radiation being directed toward the sample to elicit Raman signals, a laser controller adapted to activate the laser generator, a spectrometer situated to receive the Raman signals and to generate analyte spectral data; and a computing device coupled to the pulse sensor, laser controller and spectrometer which is adapted to correlate the spectral data with the pulse signal based on timing data received from the laser controller in order to isolate spectral components from analytes within the blood of the sample from spectral components from analytes arising from non-blood components of the sample.

An electromagnetic radiation spectrum detection system including a sensor device and an electronic control and processing module. The sensor device may include two photodiodes. The sensor device may convert an incident electromagnetic radiation (EMR) into electrical current. The electronic control and processing module may store numerical calibration values representative of a responsivity matrix of the sensor device. The electronic control and processing module may selectively provide the sensor device with electrical control voltage values (V.sub.B). The electronic control and processing module may process the values of detected electric currents (Iph) and the numerical calibration values to obtain spectrum information related to incident electromagnetic radiation spectrums. The electronic control and processing module may determine power spectral density of incident electromagnetic radiation.