Computationally efficient determination of threshold voltages in narrow-channel and short-channel MOSFETs using infinite-network manipulations

2003 ◽  
Author(s):  
H.K. An ◽  
A.H. Zemanian
Keyword(s):  
Narrow Channel ◽  
Computationally Efficient ◽  
Short Channel ◽  
Threshold Voltages ◽  
Infinite Network

scholarly journals Multi-city modeling of epidemics using spatial networks: Application to 2019-nCov (COVID-19) coronavirus in India

2020 ◽  
Author(s):  
Bhalchandra S. Pujari ◽  
Snehal Shekatkar
Keyword(s):  
Hybrid Approach ◽  
Coarse Grained ◽  
Spatial Networks ◽  
Computationally Efficient ◽  
Transport Networks ◽  
Epidemiological Modeling ◽  
Fine Grained ◽  
City Modeling ◽  
Coupling Parameters

The ongoing pandemic of 2019-nCov (COVID-19) coronavirus has made reliable epidemiological modeling an urgent necessity. Unfortunately, most of the existing models are either too fine-grained to be efficient or too coarse-grained to be reliable. Here we propose a computationally efficient hybrid approach that uses SIR model for individual cities which are in turn coupled via empirical transportation networks that facilitate migration among them. The treatment presented here differs from existing models in two crucial ways: first, self-consistent determination of coupling parameters so as to maintain the populations of individual cities, and second, the incorporation of distance dependent temporal delays in migration. We apply our model to Indian aviation as well as railway networks taking into account populations of more than 300 cities. Our results project that through the domestic transportation, the significant population is poised to be exposed within 90 days of the onset of epidemic. Thus, serious supervision of domestic transport networks is warranted even after restricting international migration.

MACHINE LEARNING ALGORITHMS FOR IDENTIFICATION OF ABNORMAL GLOW CURVES AND ASSOCIATED ABNORMALITY IN CaSO4:DY-BASED PERSONNEL MONITORING DOSIMETERS

2020 ◽  
Vol 190 (3) ◽  
pp. 342-351
Author(s):  
Munir S Pathan ◽  
S M Pradhan ◽  
T Palani Selvam
Keyword(s):  
Machine Learning ◽  
Glow Curve ◽  
Good Accuracy ◽  
Machine Learning Algorithms ◽  
Support Vector ◽  
Computationally Efficient ◽  
Artificial Neural Network Ann ◽  
First Time

Abstract In the present study, machine learning (ML) methods for the identification of abnormal glow curves (GC) of CaSO4:Dy-based thermoluminescence dosimeters in individual monitoring are presented. The classifier algorithms, random forest (RF), artificial neural network (ANN) and support vector machine (SVM) are employed for identifying not only the abnormal glow curve but also the type of abnormality. For the first time, the simplest and computationally efficient algorithm based on RF is presented for GC classifications. About 4000 GCs are used for the training and validation of ML algorithms. The performance of all algorithms is compared by using various parameters. Results show a fairly good accuracy of 99.05% for the classification of GCs by RF algorithm. Whereas 96.7% and 96.1% accuracy is achieved using ANN and SVM, respectively. The RF-based classifier is recommended for GC classification as well as in assisting the fault determination of the TLD reader system.

scholarly journals A wavefront orientation method for precise numerical determination of tsunami travel time

2013 ◽  
Vol 13 (11) ◽  
pp. 2863-2870 ◽  
Author(s):  
I. V. Fine ◽  
R. E. Thomson
Keyword(s):  
Travel Time ◽  
Grid Point ◽  
Point Pattern ◽  
Numerical Determination ◽  
Computationally Efficient ◽  
Tsunami Travel Time ◽  
Orientation Method ◽  
Huygens Principle ◽  
Improved Accuracy

Abstract. We present a highly accurate and computationally efficient method (herein, the "wavefront orientation method") for determining the travel time of oceanic tsunamis. Based on Huygens' Principle, the method uses an eight-point grid-point pattern and the most recent information on the orientation of the advancing wavefront to determine the time for a tsunami to travel to a specific oceanic location. The method is shown to provide improved accuracy and reduced anisotropy compared with the conventional multiple grid-point method presently in widespread use.

scholarly journals An efficient mechanical-probabilistic approach for the collapse modelling of RC structures

2019 ◽  
Vol 12 (2) ◽  
pp. 386-397
Author(s):  
K. O. COELHO ◽  
E. D. LEONEL ◽  
J. FLÓREZ-LÓPEZ
Keyword(s):  
Probabilistic Approach ◽  
Damage Model ◽  
Coupled Model ◽  
Simulation Method ◽  
Computationally Efficient ◽  
Rc Structures ◽  
Realistic Representation ◽  
Probabilistic Context ◽  
Numerical Approaches

Abstract The reinforced concrete (RC) structures are widely utilized around the world. However, the modelling of its complex mechanical behaviour by efficient numerical approaches has been presented marginally in the literature. The efficient approaches enable the accurate and the realistic representation of the mechanical phenomena involved and are computationally efficient for analysing complex structures. In the present study, the improved version of the lumped damage model is coupled to the Monte Carlo simulation method to represent the mechanical-probabilistic behaviour of RC structures. In such model, the concrete cracking and reinforcements’ yield are represented accurately. Moreover, this damage approach enables the accurate modelling of failure scenarios, which are based on the damage variable. Furthermore, this coupled model enables the determination of the collapse modelling accounting for uncertainties, which is the main contribution of the present study. One simple supported RC beam and one 2D RC frame are analysed in the probabilistic context. The accurate results are obtained for the probabilistic collapse path as well as its changes as a function of the loading conditions and material properties uncertainties.

scholarly journals A Computationally Efficient Multidiode Model for Optimizing the Front Grid of Multijunction Solar Cells under Concentration

2020 ◽  
Vol 2020 ◽  
pp. 1-10
Author(s):  
Chris H. van de Stadt ◽  
Pilar Espinet Gonzalez ◽  
Harry A. Atwater ◽  
Rebecca Saive
Keyword(s):  
Solar Cells ◽  
Operating Conditions ◽  
Design Parameters ◽  
Computationally Efficient ◽  
Fast Determination ◽  
Wide Range ◽  
Multijunction Solar Cells ◽  
Efficiency Increase ◽  
Light Concentration

We have developed a computationally efficient simulation model for the optimization of redirecting electrical front contacts for multijunction solar cells under concentration, and we present its validation by comparison with experimental literature results. The model allows for fast determination of the maximum achievable efficiency under a wide range of operating conditions and design parameters such as the contact finger redirecting capability, period and width of the fingers, the light concentration, and the metal and emitter sheet resistivity. At the example of a state-of-the-art four-junction concentrator solar cell, we apply our model to determine ideal operating conditions for front contacts with different light redirection capabilities. We find a 7% relative efficiency increase when enhancing the redirecting capabilities from 0% to 100%.

New Method of the Threshold Voltages Determination of a Cholesteric-Nematic Transition

2011 ◽  
Vol 535 (1) ◽  
pp. 225-232 ◽  
Author(s):  
Z. Hotra ◽  
Z. Mykytyuk ◽  
O. Hotra ◽  
A. Fechan ◽  
O. Syshynskyy ◽  
...  
Keyword(s):  
New Method ◽  
Threshold Voltages

scholarly journals A computationally efficient depression-filling algorithm for digital elevation models applied to proglacial lake drainage

2016 ◽  
Author(s):  
Constantijn J. Berends ◽  
Roderik S. W. van de Wal
Keyword(s):  
Geographical Area ◽  
Computation Time ◽  
Equation Model ◽  
Limiting Factor ◽  
Computationally Efficient ◽  
Digital Elevation ◽  
Lake Drainage ◽  
Elevation Model ◽  
Flood Fill

Abstract. We present and evaluate several optimizations to a standard flood-fill algorithm in terms of computational efficiency. As an example, we determine the land/ocean-mask for a 1 km resolution digital elevation model (DEM) of North America and Greenland, a geographical area of roughly 7000 by 5000 km (roughly 35 million elements), about half of which is covered by ocean. Determining the land/ocean-mask with our improved flood-fill algorithm reduces computation time by 90 % relative to using a standard stack-based flood-fill algorithm. In another experiment, we use the bedrock elevation, ice thickness and geoid perturbation fields from the output of a coupled ice-sheet–sea-level equation model at 30,000 years before present and determine the extent of Lake Agassiz, using both the standard and improved versions of the flood-fill algorithm. We show that several optimizations to the flood-fill algorithm used for filling a depression up to a water level, that is not defined at forehand, decrease the computation time by up to 99 %. The resulting reduction in computation time allows determination of the extent and volume of depressions in a DEM over large geographical grids or repeatedly over long periods of time, where computation time might otherwise be a limiting factor.

ACCURATE ANALYTICAL MODELING OF FREQUENCY DEPENDENT LOOP SELF-INDUCTANCE

2008 ◽  
Vol 17 (01) ◽  
pp. 77-93
Author(s):  
MOSIN MONDAL ◽  
YEHIA MASSOUD
Keyword(s):  
Integrated Circuits ◽  
Frequency Dependence ◽  
Intermediate Frequency ◽  
Propagation Delay ◽  
Computationally Efficient ◽  
Frequency Dependent ◽  
Wide Range ◽  
Global Interconnects ◽  
Very High Frequencies

Parasitic inductance of global interconnects has gained much attention in the recent past since the inductance can no longer be neglected due to different design and fabrication issues. This has led to a paradigm shift from RC to RLC modeling of global interconnects in modern integrated circuits. However, the extraction of inductance is often expensive and presents a bottleneck in performing RLC analysis of interconnects. Unlike capacitance, the frequency dependence of current distribution through return paths present a major challenge in inductance extraction. In this paper, an efficient analytical model of frequency dependent self-inductance that can be applied to model a wide range of real design scenarios was presented. The model is based on the determination of the inductances at low and very high frequencies, an intermediate frequency point and the corresponding slope of the inductance frequency response. It is demonstrate that the approach is computationally efficient and it produces accurate values of frequency dependent inductance. It is also investigate how the frequency dependence of loop self-inductance affects the RLC delay and show that the pessimism in RLC propagation delay estimation could be as high as 49% if the frequency dependence of inductance is not considered properly. Thus, realistic (less pessimistic) delay values can be obtained using our model, leading to improved system performance.

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