The Experts below are selected from a list of 65217 Experts worldwide ranked by ideXlab platform
Takamichi Nakamoto - One of the best experts on this subject based on the ideXlab platform.
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high speed active gas odor sensing system using adaptive control theory
Sensors and Actuators B-chemical, 1997Co-Authors: Takamichi Nakamoto, N Okazaki, T MornzumiAbstract:An active gas/odor sensing system using an internal blender was previously proposed to measure the mixture composition of an aroma. In the system, the mixture composition of the blender outlet was repeatedly adjusted using an optimization algorithm to match the sensor array Output Pattern of blended vapor to that of a test vapor. The system is highly flexible and can be used even when sensors have nonlinearities and the additive property is not valid. Since vapor and air were repeatedly supplied to the sensor array, the previous measurement was lengthy. Here, the concentration of each component vapor in the blender is continuously changed using adaptive feedback control theory so that the measurement time can be reduced. After the introduction of adaptive control theory, the measurement was drastically speeded up. Using this approach, the quantification results of both two-component and three-component vapors were successfully obtained within at least 2 min, whereas more than 40 min was required in the previous method.
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improvement of identification capability in an odor sensing system
Sensors and Actuators B-chemical, 1991Co-Authors: Takamichi Nakamoto, Atsushi Fukuda, Toyosaka Moriizumi, Yasuo AsakuraAbstract:Abstract Recognition of the Output Pattern from an array of gas sensors with partially overlapped specificity is valuable in odor identification. The authors have developed a method using a quartz-resonator sensor array and neural-network Pattern recognition, with which the fine differences among whisky aromas can be discriminated. In the present study, the measurement system has been improved by modifying the sample flow system and including a few lipid materials in the sensing membrane set. The identification capability has now been raised from 76% in the previous report to a recognition probability of 94%.
Yasuo Asakura - One of the best experts on this subject based on the ideXlab platform.
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improvement of identification capability in an odor sensing system
Sensors and Actuators B-chemical, 1991Co-Authors: Takamichi Nakamoto, Atsushi Fukuda, Toyosaka Moriizumi, Yasuo AsakuraAbstract:Abstract Recognition of the Output Pattern from an array of gas sensors with partially overlapped specificity is valuable in odor identification. The authors have developed a method using a quartz-resonator sensor array and neural-network Pattern recognition, with which the fine differences among whisky aromas can be discriminated. In the present study, the measurement system has been improved by modifying the sample flow system and including a few lipid materials in the sensing membrane set. The identification capability has now been raised from 76% in the previous report to a recognition probability of 94%.
T Mornzumi - One of the best experts on this subject based on the ideXlab platform.
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high speed active gas odor sensing system using adaptive control theory
Sensors and Actuators B-chemical, 1997Co-Authors: Takamichi Nakamoto, N Okazaki, T MornzumiAbstract:An active gas/odor sensing system using an internal blender was previously proposed to measure the mixture composition of an aroma. In the system, the mixture composition of the blender outlet was repeatedly adjusted using an optimization algorithm to match the sensor array Output Pattern of blended vapor to that of a test vapor. The system is highly flexible and can be used even when sensors have nonlinearities and the additive property is not valid. Since vapor and air were repeatedly supplied to the sensor array, the previous measurement was lengthy. Here, the concentration of each component vapor in the blender is continuously changed using adaptive feedback control theory so that the measurement time can be reduced. After the introduction of adaptive control theory, the measurement was drastically speeded up. Using this approach, the quantification results of both two-component and three-component vapors were successfully obtained within at least 2 min, whereas more than 40 min was required in the previous method.
Robert E. Hebner - One of the best experts on this subject based on the ideXlab platform.
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High-power pulse generator with flexible Output Pattern
IEEE Transactions on Power Electronics, 2010Co-Authors: Sungwoo Bae, Mark M. Flynn, Andres Kwasinski, Robert E. HebnerAbstract:This paper presents a high-voltage bipolar rectangular pulse generator using a solid-state boosting front-end and an H-bridge Output stage. The topology generates rectangular pulses with fast enough rise time and allows easy step-up input voltage. In addition, the circuit is able to adjust positive or negative pulsewidth, dead time between two pulses, and operating frequency. The topology can also be controlled to produce unipolar pulses and other pulse Patterns without changing its configuration. With an appropriate dc source, the Output voltage can also be adjusted to requirements of different applications. The intended application for such a circuit is algal cell membrane rupture for oil extraction, although additional applications, include biotechnology and plasma sciences, medicine, and food industry. A 1 kV/200 A bipolar solid-state pulse generator was fabricated to validate the theoretical analysis presented in this paper. In addition, to validate the analysis with simulations and prototype tests, biological test were conducted in order to examine the technical value of the proposed circuit. These evaluations seem to suggest that oil production rate from bipolar pulses may double that of an equivalent process with unipolar pulses.
Atsushi Fukuda - One of the best experts on this subject based on the ideXlab platform.
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improvement of identification capability in an odor sensing system
Sensors and Actuators B-chemical, 1991Co-Authors: Takamichi Nakamoto, Atsushi Fukuda, Toyosaka Moriizumi, Yasuo AsakuraAbstract:Abstract Recognition of the Output Pattern from an array of gas sensors with partially overlapped specificity is valuable in odor identification. The authors have developed a method using a quartz-resonator sensor array and neural-network Pattern recognition, with which the fine differences among whisky aromas can be discriminated. In the present study, the measurement system has been improved by modifying the sample flow system and including a few lipid materials in the sensing membrane set. The identification capability has now been raised from 76% in the previous report to a recognition probability of 94%.