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Infrared systems fundamentals
Published in Antoni Rogalski, Infrared and Terahertz Detectors, 2019
As is shown in Figure 2.4, the image intensifier system is built from three main blocks: optical objective, multichannel plate (MCP), and optical ocular. An MCP is a secondary electron multiplier consisting of array of millions of very thin glass channels (of internal diameter ≈ 10 μm; each capillary works as an independent electron multiplier) bundled in parallel and sliced in the form of disc (see Figure 2.6). Secondary electrons are accelerated by the voltage applied across both ends of the MCP. This process is repeated many times along the channel wall and as a result, a great number of electrons are output from the MCP. Furthermore, the electron flux can be reconverted into an optical image by using a phosphor coating as the rear electrode to provide electroluminescence; this combination provides an image intensifier.
Formal Methods
Published in Cary R. Spitzer, Uma Ferrell, Thomas Ferrell, Digital Avionics Handbook, 2017
Each alternative of the do-loop has the form G → S, where G is known as a guard or guard statement. Guard G is either a Boolean expression or a channel operation (sending or receiving a message). If a guard expression is true or its channel operation is enabled, the statement sequence that follows is executable. When multiple guarded sequences are eligible, one is selected for execution nondeterministically. All four guards within the do-loop of process MCP are channel receive operations. Channel operations are written chan?v to receive into variable v and chan!e to send value e. The statements after each guard specify how the process responds to the corresponding type of incoming message.
Infrared devices and techniques
Published in John P. Dakin, Robert G. W. Brown, Handbook of Optoelectronics, 2017
Antoni Rogalski, Krzysztof Chrzanowski
As is shown in Figure 18.7, the image intensifier system is built from three main blocks: optical objective, multichannel plate (MCP), and optical ocular. An MCP is a secondary electron multiplier consisting of an array of millions of very thin glass channels (of internal diameter ≈10 μm, each capillary works as an independent electron multiplier) bundled in parallel and sliced in the form of a disk (see Figure 18.12). Secondary electrons are accelerated by the voltage applied across both ends of the MCP. This process is repeated many times along the channel wall and as a result, a great number of electrons are output from the MCP. Furthermore, the electron flux can be reconverted into an optical image by using a phosphor coating as the rear electrode to provide electroluminescence; this combination provides an image intensifier.
Development of pavement roughness master curves using Markov Chain
Published in International Journal of Pavement Engineering, 2022
Saeid Alimoradi, Amir Golroo, Seyed Mohammad Asgharzadeh
Typically, probabilistic models are represented by Markov Chain Process (MCP). The challenging concern of using MCP is to develop a Transition Probability Matrix (TPM). TPMs are composed of transition probabilities, by which MCP estimates the probability of an element being in a condition after each transition period (Li et al. 1997, Hassan et al. 2015, Mandiartha et al. 2017, Abaza 2017b). In recent years, different sorts of MCP models have been implemented to analyze the pavement performance, and transition probabilities were calculated by either historical data or a panel of experts. Whether is the contemplating the randomness of pavement deterioration process, or the capability of the model to be updated with the presence of new data, developing a prediction model using MCP is advantageous (Li et al. 1997, Hong and Wang 2003, Abaza et al. 2004, Abaza and Murad 2009, Pulugurta et al. 2009, Hassan et al. 2015, 2017, Moreira et al. 2018, Osorio-Lird et al. 2018, Abaza 2016, Abaza 2017a, 2017b, Ansarilari and Golroo 2019).