Abstract: Apparatuses and methods for generating trace vapors are provided. The apparatus includes a controller and an oven. The controller includes: a processor, a memory storing at least one control program, a clean solution supply port constructed to output a clean solution, an analyte solution supply port constructed to output an analyte solution, a carrier gas inlet port constructed to receive a carrier gas, and a plurality of carrier gas supply controllers constructed to output the carrier gas.

Abstract: Apparatuses and methods for generating trace vapors are provided. The apparatus includes a controller and an oven. The controller includes: a processor, a memory storing at least one control program, a clean solution supply port constructed to output a clean solution, an analyte solution supply port constructed to output an analyte solution, a carrier gas inlet port constructed to receive a carrier gas, and a plurality of carrier gas supply controllers constructed to output the carrier gas.

Abstract: Provided a system and method for detecting an event while discriminating against false alarms in a monitored space using at least one sensor suite to acquire signals, transmitting the signals to a sensor system device where the signal is processed into data packets, transmitting the data packets to a data fusion device, where the data packets are aggregated and algorithmic data fusion analysis is performed to generate threat level information. The threat level information is distributed to a supervisory control system where an alarm level can be generated when predetermined criteria are met to indicate the occurrence of an event in the monitored space.

Abstract: A multi-criteria event detection system, comprising a plurality of sensors, wherein each sensor is capable of detecting a signature characteristic of a presence of an event and providing an output indicating the same. A processor for receiving each output of the plurality of sensors is also employed. The processor includes a probabilistic neural network for processing the sensor outputs. The probabilistic neural network comprises a nonlinear, nor-parametric pattern recognition algorithm that operates by defining a probability density function for a plurality of data sets that are each based on a training set data and an optimized kernel width parameter. The plurality of data sets includes a baseline, non-event, first data set; a second, event data set; and a third, nuisance data set.

Abstract: A multi-criteria fire detection system, comprising a plurality of sensors, wherein each sensor is capable of detecting a signature characteristic of a presence of a fire and providing an output indicating the same. A processor for receiving each output of the plurality of sensors is also employed. The processor includes a probabilistic neural network for processing the sensor outputs. The probabilistic neural network comprises a nonlinear, nor-parametric pattern recognition algorithm that operates by defining a probability density function for a plurality of data sets that are each based on a training set data and an optimized kernel width parameter. The plurality of data sets includes a baseline, non-fire, fist data set; a second, fire data set, and a third, nuisance data set.

Abstract: A multi-criteria event detection system, comprising a plurality of sensors, wherein each sensor is capable of detecting a signature characteristic of a presence of an event and providing an output indicating the same. A processor for receiving each output of the plurality of sensors is also employed. The processor includes a probabilistic neural network for processing the sensor outputs. The probabilistic neural network comprises a nonlinear, nor-parametric pattern recognition algorithm that operates by defining a probability density function for a plurality of data sets that are each based on a training set data and an optimized kernel width parameter. The plurality of data sets includes a baseline, non-event, first data set; a second, event data set; and a third, nuisance data set.

Abstract: A method and apparatus for the detection of hydrazine, monomethylhydrazine, 1,1-dimethylhydrazine in air (or other gas medium) or in an aqueous solution. The detection is accomplished by introducing a stream of air, or other gas medium, or aqueous solution suspected of containing hydrazine, monomethylhydrazine, 1,1-dimethylhydrazine or mixtures thereof into a pH controlled reagent solution containing an aromatic dicarboxaldehyde to react with the hydrazine, monomethylhydrazine, 1,1-dimethylhydrazine or mixtures thereof, respectively, and by exposing the reacted reagent solution to an excitation wavelength range and monitoring an emission from the exposed reagent solution at an emission wavelength range to detect the presence of a hydrazine derivative, monomethylhydrazine derivative, 1,1-dimethylhydrazine derivative, or mixtures thereof (i.e.