25 nm Figure 3 (a) Intensity of the zero order, when phase differ

25 nm.Figure 3.(a) Intensity of the zero order, when phase difference is 2m��. (b) Intensity of the zero order, when phase difference is (2m+1)��.Figure 3(a) is the calculated intensity on the detector when the phase difference of GLM is 2m��, while Figure 3(b) is the intensity when the phase difference of GLM is (2m+1) ��. It can be seen that when voltage Von actuated, the energy of the zero order, almost equaling that of the incident light, reaches maximum, the phase difference is 2m�� and the pixel is on and when a voltage Voff is actuated, the energy reaches nearly zero, when the phase difference is (2m+1) �� and the pixel is off. Suppose the reflection efficiency is T, which is the ratio between the intensity of the zero order and the incident light, when the pixel is on, while the reflected ratio is T0, when the pixel is off.

The calculation results derived from formula (6) shows that T and T0 equals 0.94 and 0.008 respectively. Apparently, the grating light modulator acts as a programmable
There are different means of transporting products between cities and countries worldwide. According to the type and importance of the transported products, certain requirements are considered in the selection and supervision of transportation systems [1]. The use of wireless sensor networks to record environmental conditions such as temperature and humidity during the transport of sensitive goods and products has increased considerably [2,3]. After measuring environmental conditions, data are sent for processing and decision-making; in advanced transportation systems, key decisions are made in measurement systems in a distributed manner [4].

The use of distributed data processing techniques increases the autonomy and reliability of transportation systems. This allows further decisions to be made based on the current condition of the goods. The ��intelligent container�� is an example of an intelligent transportation system that features distributed data processing [5]. In recent years, several data processing and analysis techniques have been developed. Entinostat Typically, the processing algorithm consists of both an approximation mechanism and a classification algorithm. The approximation theory concerns the approximation of unknown functions or parameters according to known functions or parameters [6].

Different approaches exist to approximate data, including stochastic approximation, polynomial interpolation, differential and integral equations, ��least squares��, and ��neural network�� [7]. Furthermore, for data classification and inference, different algorithms such as fuzzy, neural network and the hierarchical approach can be applied [8�C10]. The artificial neural network (ANN) is a knowledge-based approach with several applications in engineering, economics, and transportation industries [11].

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