a simple semi-phenomenological model, which accurately predicts the dependence of thresholdcurrent for temperature of resonant-phonon three well quantum cascade laser based on verticaltransitions is offered. we found that, the longitude optical phonon scattering of thermally excitedelectrons is the most important limiting factor for thermal performance of high frequency thz qcls.in low frequenc...

In most of advanced processes, quality of a final product depends on the several quality characteristic in the previous stages. This is called a cascade property in multi-stage processes. On the other hand, sometimes the quality of a process or product is characterized by a relationship between a response variable and one or more explanatory variable(s).This relation is called profile. In some ...

Aim of this study is introduction one Approach for Monitoring a Two-Stage Process by Profile Quality Characteristic in the Second Stage. Nowadays, many processes are multistage and such processes often depend on each other. The implication is; the specification features for the product that are used to monitor the quality of that product and are usually assessed in one stage of the process, not...

In most modern manufacturing systems, products are often the output of some multistage processes. In these processes, the stages are dependent on each other, where the output quality of each stage depends also on the output quality of the previous stages. This property is called the cascade property. Although there are many studies in multistage process monitoring, there are fewer works on prof...

Wavelength beam combining was used to co-propagate beams from 28 elements in an array of distributed-feedback quantum cascade lasers (DFB-QCLs). The beam-quality product of the array, defined as the product of near-field spot size and far-field divergence for the entire array, was improved by a factor of 21 by using wavelength beam combining. To demonstrate the applicability of wavelength beam ...

Product units provide a method of automatically learning the higher-order input combinations required for eecient learning in neural networks. However, we show that problems are encountered when using backpropagation to train networks containing these units. This paper examines these problems, and proposes some atypical heuristics to improve learning. Using these heuristics a constructive metho...