A clinical diagnostic analyzer for performing an automated crossover study on quality control (QC) material includes a processor, memory, measurement hardware, and an input panel/display. The analyzer prompts a user to load a QC specimen, and to instigate testing and analysis to determine a mean and a standard deviation for the new material. Associated methods for using one or more clinical diagnostic analyzers to calculate a new mean and standard deviation for a new QC material, reduce error in the calculated mean value, and to reduce the total number of days to complete a crossover study are also disclosed.

Provided are a quality control method, a quality control system, a management apparatus, an analyzer, and a quality control abnormality determination method in which measurement results of both a quality control substance and a specimen are sufficiently utilized to improve the quality of quality control. The quality control method used in a management apparatus which is connected via a network to an analyzer installed in each of a plurality of facilities includes obtaining, from an analyzer in each facility via a network, first quality control information obtained by measuring an artificially generated quality control substance, and second quality control information obtained by measuring a plurality of specimens by the analyzer in each facility; and outputting information concerning quality control of an analyzer in at least one facility, based on the obtained first quality control information and second quality control information.

Various embodiments include methods and apparatuses to reduce false-particle counts in a water-based condensation particle counter (CPC). In one embodiment, a cleanroom CPC has three parallel growth tube assemblies. A detector is coupled to an outlet of each of the three parallel growth tube assemblies, and is used to compare the particle concentrations measured from each of the three growth tube assemblies. An algorithm compares the counts from the three detectors and determines when the particles counted are real and when they are false counts. Any real particle event shows up in all three detectors, while false counts will only be detected by one detector. Statistics are used to determine at which particle count levels the measured counts are considered to be real versus false. Other methods and apparatuses are disclosed.

An automatic analyzer is provided which is easier to investigate when some troubles such as data abnormality occur in a sample analysis result as compared with an automatic analyzer according to the related art. The automatic analyzer includes: analysis units that perform analysis and quality control analysis for ensuring quality of the analysis; a storage medium that stores quality control results of the quality control analysis performed by the analysis units; a monitor that displays the quality control results; and a control PC that controls an operation of the analysis units (8, 9, and 16), executes, when an arbitrary result is selected from the quality control results stored in the storage medium, based on the selected quality control result, statistical calculation of the selected result and a quality control result performed in the past, and causes the monitor to display a statistical calculation screen as a statistical calculation result.

An apparatus for generating monitoring data for managing the state of a sample analyzer is provided. The apparatus includes a processing unit for generating output data for associating and displaying, in a time series, a sample information region indicating information related to measurement data acquired by a sample analyzer from a sample, and an operational information region indicating information related to the operation of the sample analyzer.

The method for generating an index for managing the analytical accuracy of a sample analyzer includes a step of acquiring a determination result related to whether a sample is positive or negative from a plurality of sample analyzers, and a step of generating an index based on a ratio of a sample determined to be positive or negative by the plurality of sample analyzers from a plurality of determination results obtained from the plurality of sample analyzers.

An examination system, a method of obtaining a training set for a classifier, and a non-transitory computer readable medium, the method comprising: upon receiving in a memory device object inspection results comprising data indicative of potential defects, each potential defect of the potential defects associated with a multiplicity of attribute values defining a location of the potential defect in an attribute space: sampling by the processor a first set of defects from the potential defects, wherein the defects within the first set are dispersed independently of a density of the potential defects in the attribute space; and obtaining by the processor a training defect sample set comprising the first set of defects and data or parameters representative of the density of the potential defects in the attribute space.

A method for predicting a failure state of an automated analyzer for analyzing a biological sample is disclosed. The method includes obtaining a prediction algorithm for predicting a failure state of an automated analyzer. The prediction algorithm is configured to predict a failure state of the automated analyzer based on calibration data and/or quality control data generated by an automated analyzer. The method also includes obtaining calibration data and/or quality control data of the automated analyzer and processing the calibration data and/or quality control data by using the prediction algorithm to predict a failure state of the automated analyzer.

A system for identifying or distinguishing materials, comprising at least one local apparatus and a central station. Each local apparatus comprises at least one measuring device for recording at least one actual signature for materials each and at least one local computer communicatively connected to the at least one measuring device, the at least one local computer having a local database for storing and/or processing the actual signature. The at least one central station comprises a server having a central database for storing and/or processing the actual signatures of the local apparatus. Furthermore, the system comprises a network, which communicatively connects the local computers of the local units via the server of the center. The invention further relates to a corresponding method for operating a system, to an analysis method for identifying or distinguishing the materials, and to a measuring device for recording material properties of the materials.

Systems and methods for predicting a condition of an engine are described herein. A fluid sample having particles suspended therein is received from the engine. A plurality of particles are extracted from the fluid sample. A sample profile of the plurality of particles extracted from the fluid sample is obtained. A reference profile of particles of a reference fluid sample from a reference engine is obtained. The reference profile and the sample profile having particles identified based on size, aspect ratio and chemical composition. A correlation index between the sample profile and the reference profile is determined based on size and aspect ratio of the particles of the sample profile and the reference profile. A prediction that the engine has a known condition associated with the reference engine is generated from the correlation index. An output indicating the condition of the engine is generating based on the prediction.