A laser gas analyzer includes a light emitter which emits a laser light irradiated onto a gas to be measured; a light receiver which receives a laser light which transmitted the gas to be measured; a plurality of optical-axis adjustment mechanisms, one of which is provided in the light emitter and the other one of which is provided in the light receiver; a main display which is provided in one of the light emitter and the light receiver and displays thereon the measured result acquired by receiving the laser light which transmitted the gas to be measured; and a sub-display which is provided in the other one of the light emitter and the light receiver and displays thereon a part of the measured result displayed on the main display.

A sample structure measuring device includes a light source, a path splitting portion configured to split light from the light source into light on a measurement path passing through a sample and light on a reference path, an optical path merging portion configured to merge the measurement path and the reference path, a photodetector having pixels and configured to detect incident light from the path merging portion and output phase data of the incident light, and a processor. A first region is a region where the sample is present and a second region is a region where the sample is not present. The processor divides the phase data into the first region and the second region, sets an initial estimated sample structure based on the first region, and optimizes the estimated sample structure using simulated light transmitted through the estimated sample structure and measurement light transmitted through the sample.

A device for characterizing substances in a scene, the device including a housing having a cavity configured to contain the substances, an opening for receiving the substances, an imager for capturing an image of the substances, an illumination source for illuminating the substances, a sensor for obtaining sensory data of the substances, a gas supply device for storing and inserting gas into the housing, a mechanical arm for inserting or removing the substances into or from the device via the opening, a syringe to add a material into the housing, a pump for creating a vacuum in the device, an air pump to suck air from the housing and removing the substances from the housing, a fan for cooling the housing, a fluid injector for inserting fluid into the housing, and a processor in communication with the imager and the sensor imaging module. The processor receives the sensory data and the captured images, and compares them to a. database to identify the characteristics of the substances.

A smoke detector includes: a casing; a first light emitting unit; a second light emitting unit; and a light receiving unit. A second scattering angle that is an angle between the reception axis of the light receiving unit and a second extension extending from an intersection of the second emission axis and the reception axis in a direction away from the second light emitting unit is larger than a first scattering angle that is an angle between the reception axis of the light receiving unit and a first extension extending from an intersection of the first emission axis and the reception axis in a direction away from the first light emitting unit.

A method includes receiving, by a processing device, first data from an optical sensor of a processing chamber. The method further includes processing the first data to obtain second data. The second data includes an indication of a condition of a coating on an interior surface of the processing chamber. The method further includes generating an indication of performance of a processing operation of the processing chamber in view of the second data. The method further includes causing performance of a corrective action in view of the indication of performance of the processing chamber.

Aspects of the present disclosure include reconfigurable integrated circuits for characterizing particles of a sample in a flow stream. Reconfigurable integrated circuits according to certain embodiments are programmed to calculate parameters of a particle in a flow stream from detected light; compare the calculated parameters of the particle with parameters of one or more particle classifications; classify the particle based on the comparison between the parameters of the particle classifications and the calculated parameters of the particle; and adjust one or more parameters of the particle classifications based on the calculated parameters of the particle. Methods for characterizing particles in a flow stream with the subject integrated circuits are also described. Systems and integrated circuit devices programmed for practicing the subject methods, such as on a flow cytometer, are also provided.

A metrology three-dimensional (3D) scanning system includes a metrology 3D scanning application (app) comprising computing instructions that, when executed by one or more processors, causing the one or more processors to: record human-robot interaction (HRI) data as a human operator operates the HRI device; generate a preliminary scan path based on the HRI data for operating a robotic element within an operating environment; move the robotic element along at least a portion of the preliminary scan path and record preliminary scan data comprising at least a subset of dimension data defining at least a target object; generate a metrology scanning path plan and a motion plan for the robotic element based on the preliminary scan data; and execute instructions to move the robotic element within the operating environment according to the metrology scanning path plan and the motion plan for scanning the target object.

Protecting information by partitioning data across multiple storage resources. A method includes receiving an image of a test card and an identity of a patient associated with the test card. The method includes associating the image of the test card with the identity of the patient as a data pair on a first storage resource. The method includes providing the image of the test card to a second storage resource by way of a network, wherein the first storage resource is independent of the second storage resource. The method includes receiving a result for the test card and associating the result for the test card with the identity of the patient based on the data pair stored on the first storage resource.

Test cards for agglutination assays, wherein the test cards are configured for computer-implemented image analysis. A test card includes a negative control test region for receiving a negative control fluid sample, a positive control test region for receiving a positive control fluid sample, and a test sample region for receiving a test fluid sample. The test card includes one or more unique scannable codes comprising data for instructing a processor to capture an image of the test card that is suitable for computer-implemented image analysis.

Machine learning image analysis for quantitative and qualitative analysis of agglutination samples. A method includes receiving an image of an agglutination assay comprising a negative control sample, a positive control sample, and a test sample. The method includes providing the image to a machine learning algorithm trained to classify agglutination of the test sample on a quantitative scale. The machine learning algorithm calibrates the quantitative scale based at least in part on the negative control sample and the positive control sample.