Quantitative Models for Complex Physical Systems

2014 ◽  
Vol 1061-1062 ◽  
pp. 1144-1147
Author(s):  
Jun Fu ◽  
Jin Zhao Wu ◽  
Ning Zhou ◽  
Hong Yan Tan
Keyword(s):  
Quantitative Analysis ◽  
State Space ◽  
Control Systems ◽  
Chemical Reaction ◽  
Metric Space ◽  
Manufacturing Systems ◽  
Quantitative Model ◽  
Hybrid Automata ◽  
Physical Systems ◽  
The Difference

We present a quantitative model, called metric hybrid automata, for quantifying the behaviors of complex physical systems, such as chemical reaction control systems, manufacturing systems etc. Due to the introduction of a metric, the state space of hybrid automata forms a metric space, in which the difference of states can be quantified. Furthermore, in order to reveal the distance of system behaviors, we construct the simulation distance and the bisimulation distance, which quantify the similarity of system behaviors. Our model provides the basis for quantitative analysis for those complex physical systems.

scholarly journals Quantitative Analysis of Fluorescence Detection Using a Smartphone Camera for a PCR Chip

Sensors ◽  
2021 ◽  
Vol 21 (11) ◽  
pp. 3917
Author(s):  
Jong-Dae Kim ◽  
Chan-Young Park ◽  
Yu-Seop Kim ◽  
Ji-Soo Hwang
Keyword(s):  
Quantitative Analysis ◽  
Fluorescence Detection ◽  
High Performance ◽  
Low Cost ◽  
Dna Amplification ◽  
Fluorescent Detection ◽  
Rt Pcr ◽  
Commercial System ◽  
Intensity Changes ◽  
The Difference

Most existing commercial real-time polymerase chain reaction (RT-PCR) instruments are bulky because they contain expensive fluorescent detection sensors or complex optical structures. In this paper, we propose an RT-PCR system using a camera module for smartphones that is an ultra small, high-performance and low-cost sensor for fluorescence detection. The proposed system provides stable DNA amplification. A quantitative analysis of fluorescence intensity changes shows the camera’s performance compared with that of commercial instruments. Changes in the performance between the experiments and the sets were also observed based on the threshold cycle values in a commercial RT-PCR system. The overall difference in the measured threshold cycles between the commercial system and the proposed camera was only 0.76 cycles, verifying the performance of the proposed system. The set calibration even reduced the difference to 0.41 cycles, which was less than the experimental variation in the commercial system, and there was no difference in performance.

On-the-Fly Substrate Eccentricity Recognition for Robotized Manufacturing Systems

2005 ◽  
Vol 127 (1) ◽  
pp. 206-216 ◽  
Author(s):  
Martin Hosek ◽  
Jan Prochazka
Keyword(s):  
Optical Sensors ◽  
Semiconductor Manufacturing ◽  
Manufacturing Systems ◽  
Robotic Manipulator ◽  
End Effector ◽  
Transfer Path ◽  
The Difference ◽  
Manufacturing Applications ◽  
Actual Location

This paper describes a method for on-the-fly determination of eccentricity of a circular substrate, such as a silicon wafer in semiconductor manufacturing applications, carried by a robotic manipulator, where eccentricity refers to the difference between the actual location of the center of the substrate and its desired position on the end-effector of the robotic manipulator. The method utilizes a pair of external optical sensors located along the substrate transfer path. When moving a substrate along the transfer path, the robotic manipulator captures the positions and velocities of the end-effector at which the edges of the substrate are detected by the sensors. These data along with the expected radius of the substrate and the coordinates of the sensors are used to determine the eccentricity of the substrate. This information can be used by the robotic manipulator to compensate for eccentricity of the substrate when performing a place operation, resulting in the substrate being placed centered regardless of the amount and direction of the initial eccentricity. The method can also be employed to detect a defect, such as breakage, of a circular substrate and report an error condition which can abort or otherwise adjust operation of the robotic manipulator.

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