Implementation and characterization of a DUV raster-scanned mask pattern generation system

2002 ◽  
Author(s):  
Michael J. Bohan ◽  
Henry Chris Hamaker ◽  
Warren Montgomery
Keyword(s):  
Pattern Generation ◽  
Mask Pattern ◽  
Generation System

Characterization of an integrated multibeam laser mask-pattern generation and dry etch processing total solution

2002 ◽  
Author(s):  
Alex H. Buxbaum ◽  
Melisa J. Buie ◽  
Brigitte C. Stoehr ◽  
Warren Montgomery ◽  
Scott E. Fuller
Keyword(s):  
Pattern Generation ◽  
Mask Pattern ◽  
Dry Etch

Manufacture of the Glass Nanopore Based on Laser Heating and Experimental Research

2016 ◽  
Vol 851 ◽  
pp. 244-248
Author(s):  
Ya Fei Zhang ◽  
Zhi Yuan Yao ◽  
Bi Cheng Wu
Keyword(s):  
Laser Heating ◽  
Chemical Method ◽  
Physical Method ◽  
Experimental Basis ◽  
Generation System ◽  
Glass Capillary ◽  
Linear Ultrasonic Motor ◽  
Capillary Tension ◽  
Through Hole

The glass nanopore produced by the physical method has better physical characteristics, higher strength, stronger stability, longer life and other significant features compared with the chemical method. The purpose of this paper is to study DNA sequencing (973 project) to provide experimental basis for preparation of glass capillary 5nm 3D nanochannel In this paper, we design a set of glass capillary tension system which is controlled by laser heating and linear ultrasonic motor and produced successfully the device for the preparation of nanopore below 50 nm. In addition, the use of micro droplet generation system has carried out preliminary characterization of nanopore drawn devices. Seen from the characterization, the nanopore device fabricated can indeed produce a through-hole.

scholarly journals Probabilistic Generation Model of Solar Irradiance for Grid Connected Photovoltaic Systems Using Weibull Distribution

2020 ◽  
Vol 12 (6) ◽  
pp. 2241 ◽  
Author(s):  
Muhammad Umar Afzaal ◽  
Intisar Ali Sajjad ◽  
Ahmed Bilal Awan ◽  
Kashif Nisar Paracha ◽  
Muhammad Faisal Nadeem Khan ◽  
...  
Keyword(s):  
Weibull Distribution ◽  
Solar Irradiance ◽  
Goodness Of Fit ◽  
Pattern Generation ◽  
Generalized Regression Neural Network ◽  
Generation Model ◽  
Moving Window ◽  
Renewable Energy Resources ◽  
Proposed Model

Around the world, countries are integrating photovoltaic generating systems to the grid to support climate change initiatives. However, solar power generation is highly uncertain due to variations in solar irradiance level during different hours of the day. Inaccurate modelling of this variability can lead to non-optimal dispatch of system resources. Therefore, accurate characterization of solar irradiance patterns is essential for effective management of renewable energy resources in an electrical power grid. In this paper, the Weibull distribution based probabilistic model is presented for characterization of solar irradiance patterns. Firstly, Weibull distribution is utilized to model inter-temporal variations associated with reference solar irradiance data through moving window averaging technique, and then the proposed model is used for irradiance pattern generation. To achieve continuity of discrete Weibull distribution parameters calculated at different steps of moving window, Generalized Regression Neural Network (GRNN) is employed. Goodness of Fit (GOF) techniques are used to calculate the error between mean and standard deviation of generated and reference patterns. The comparison of GOF results with the literature shows that the proposed model has improved performance. The presented model can be used for power system planning studies where the uncertainty of different resources such as generation, load, network, etc., needs to be considered for their better management.

scholarly journals Computational Models of Neuromodulation

1998 ◽  
Vol 10 (4) ◽  
pp. 771-805 ◽  
Author(s):  
Jean-Marc Fellous ◽  
Christiane Linster
Keyword(s):  
Sensory Processing ◽  
Information Integration ◽  
Computational Models ◽  
Neural Substrates ◽  
Pattern Generation ◽  
Neural Models ◽  
Functional Roles ◽  
Modeling Studies ◽  
And Control

Computational modeling of neural substrates provides an excellent theoretical framework for the understanding of the computational roles of neuromodulation. In this review, we illustrate, with a large number of modeling studies, the specific computations performed by neuromodulation in the context of various neural models of invertebrate and vertebrate preparations. We base our characterization of neuromodulations on their computational and functional roles rather than on anatomical or chemical criteria. We review the main framework in which neuromodulation has been studied theoretically (central pattern generation and oscillations, sensory processing, memory and information integration). Finally, we present a detailed mathematical overview of how neuromodulation has been implemented at the single cell and network levels in modeling studies. Overall, neuromodulation is found to increase and control computational complexity.

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