scholarly journals Application of the Monte Carlo Method for the Assessment of Long-term Success in Keratoprosthesis Surgery

2002 ◽  
Vol 4 (3) ◽  
pp. 183-190 ◽  
Author(s):  
W. Hitzl ◽  
G. Grabner
Keyword(s):  
Monte Carlo ◽  
Visual Acuity ◽  
Survival Analysis ◽  
Monte Carlo Method ◽  
Surgical Techniques ◽  
Distribution Functions ◽  
Time Interval ◽  
Specific Method ◽  
The Monte Carlo Method

The comparison of different methods of keratoprosthesis (KP) regarding their long-term success, as far as visual acuity is concerned, is difficult: this is the case both as a standardized reporting method agreed upon by all research groups has not been reported and far less accepted, and as the quality of life for the patient not only depends on the level of visual acuity, but also quite significantly on the “survival time” of the implant. Therefore, an analysis of a single series of patients with Osteo–Odonto–Keratoprosthesis (OOKP) was performed. Statistical analysis methods used by others in similar groups of surgical procedures have included descriptive statistics, survival analysis and ANOVA. These methods comprised comparisons of empirical densities or distribution functions and empirical survival curves. It is the objective of this paper to provide an inductive statistical method to avoid the problems with descriptive techniques and survival analysis. This statistical model meets four important standards: (1) the efficiency of a surgical technique can be assessed within an arbitrary time interval by a new index (VAT-index), (2) possible autocorrelations of the data are taken into consideration and (3) the efficiency is not only stated by a point estimator, but also 95% point-wise confidence limits are computed based on the Monte Carlo method, and finally, (4) the efficiency of a specific method is illustrated by line and range plots for quick illustration and can also be used for the comparison of different other surgical techniques such as refractive techniques, glaucoma and retinal surgery.

scholarly journals Monte Carlo-Based Procedure for Determining the Maximum Energy at the Output of Accelerometers

Energies ◽  
2020 ◽  
Vol 13 (7) ◽  
pp. 1552 ◽  
Author(s):  
Krzysztof Tomczyk
Keyword(s):  
Monte Carlo ◽  
Monte Carlo Method ◽  
Transfer Functions ◽  
Linear Measurement ◽  
Maximum Energy ◽  
Time Interval ◽  
Maximum Output ◽  
Accuracy Class ◽  
Fixed Point Algorithm ◽  
The Monte Carlo Method

The solutions presented in this paper can be the basis for mutual comparison of different types of accelerometers produced by competing companies. An application of a procedure based on the Monte Carlo method to determine the maximum energy at the output of accelerometers is discussed here. The fixed-point algorithm controlled by the Monte Carlo method is used to determine this energy. This algorithm can only be used for the time-invariant and linear measurement systems. Hence, the accelerometer nonlinearities are not considered here. The mathematical models of the accelerometer and the special filter, represented by the relevant transfer functions, are the basis for the above procedure. Testing results of the voltage-mode accelerometer of type DJB A/1800/V are presented here as an example of an implementation of the solutions proposed. Calculation of the energy was executed in Mathcad 14 program with the built-in Programming Toolbar. The value of the maximum output energy determined for a specified time interval corresponds to the maximum integral-square error of the accelerometer. Such maximum energy can be a comparative ratio just like the accuracy class in the case of instruments used for the static measurements. Hence, the main analytical and technical contributions of this paper concern the development of theoretical procedures and the presentation of their application on the example of a real type of accelerometer.

scholarly journals A High Performance Digital Time Interval Spectrometer: An Embedded, FPGA-Based System With Reduced Dead Time Behaviour

2015 ◽  
Vol 22 (4) ◽  
pp. 601-619 ◽  
Author(s):  
Mohammad Arkani
Keyword(s):  
Monte Carlo ◽  
Monte Carlo Method ◽  
High Performance ◽  
Dead Time ◽  
Time Spectrum ◽  
Time Interval ◽  
Prototype System ◽  
Short Time Interval ◽  
Time Model ◽  
The Monte Carlo Method

AbstractIn this work, a fast 32-bit one-million-channel time interval spectrometer is proposed based onfield programmable gate arrays(FPGAs). The time resolution is adjustable down to 3.33 ns (=T, the digitization/discretization period) based on a prototype system hardware. The system is capable to collect billions of time interval data arranged in one million timing channels. This huge number of channels makes it an ideal measuring tool for very short to very long time intervals of nuclear particle detection systems. The data are stored and updated in a built-in SRAM memory during the measuring process, and then transferred to the computer. Twotime-to-digital converters(TDCs) working in parallel are implemented in the design to immune the system against loss of the first short time interval events (namely below 10 ns considering the tests performed on the prototype hardware platform of the system). Additionally, the theory of multiple count loss effect is investigated analytically. Using the Monte Carlo method, losses of counts up to 100million events per second(Meps) are calculated and the effective system dead time is estimated by curve fitting of a non-extendable dead time model to the results (τNE= 2.26 ns). An important dead time effect on a measured random process is the distortion on the time spectrum; using the Monte Carlo method this effect is also studied. The uncertainty of the system is analysed experimentally. The standard deviation of the system is estimated as ± 36.6 ×T(T= 3.33 ns) for a one-second time interval test signal (300 millionTin the time interval).

Monte Carlo Computations on Molten Caesium Bromide

1975 ◽  
Vol 30 (1) ◽  
pp. 83-86 ◽  
Author(s):  
Chiara Margheritis ◽  
Cesare Sinistri
Keyword(s):  
Monte Carlo ◽  
Monte Carlo Method ◽  
Thermodynamic Properties ◽  
Total Energy ◽  
Distribution Functions ◽  
Radial Distribution Functions ◽  
Pair Potentials ◽  
The Monte Carlo Method ◽  
Different Temperatures ◽  
Increasing Temperature

Abstract Molten CsBr was computer simulated tat 1 atm and four different temperatures using the Monte Carlo method. Structural and thermodynamic properties of the melt were obtained on the basis of pair potentials. In particular, radial distribution functions, volume, and energy with its coulomb, dipole-dipole, and repulsive components were determined. Separately, the polarization energy was also evaluated: this quantity increases with increasing temperature and ranges between 2 and 4% of the total energy.

scholarly journals Research of mathematical models for minimizing power shortage with quadratic losses in power lines and with using network coefficients (sensitivity coefficients)

2020 ◽  
Vol 216 ◽  
pp. 01009
Author(s):  
Dmitry Krupenev ◽  
Denis Boyarkin ◽  
Dmitrii Iakubovskii
Keyword(s):  
Monte Carlo ◽  
Monte Carlo Method ◽  
Power Systems ◽  
Electric Power Systems ◽  
Power Lines ◽  
First Order ◽  
Sensitivity Coefficients ◽  
The Monte Carlo Method ◽  
Adequacy Assessment

The article presents an analysis of the models for minimizing the power shortage used in adequacy assessment by the Monte Carlo method. We analysed two models: a model with quadratic losses in power lines and a model using network coefficients (first-order sensitivity coefficients), that are showing the dependence of the change in power flows through power lines on the balance of generation / consumption in the reliability zones. As a result of the analysis, a conclusion is made about the applicability of the investigated models for adequacy assessment in the long-term planning of the development of electric power systems.

scholarly journals Simulation of Two-Dimensional Images for Ion-Irradiation Induced Change in Lattice Structures and Magnetic States in Oxides by Using Monte Carlo Method

2021 ◽  
Vol 5 (2) ◽  
pp. 13
Author(s):  
Akihiro Iwase ◽  
Shigeru Nishio
Keyword(s):  
Monte Carlo ◽  
Monte Carlo Method ◽  
Ion Irradiation ◽  
Ion Beam ◽  
Distribution Functions ◽  
Lattice Structures ◽  
Two Dimensional ◽  
The Monte Carlo Method ◽  
Magnetic States ◽  
Two Dimensional Images

A Monte Carlo method was used to simulate the two-dimensional images of ion-irradiation-induced change in lattice structures and magnetic states in oxides. Under the assumption that the lattice structures and the magnetic states are modified only inside the narrow one-dimensional region along the ion beam path (the ion track), and that such modifications are affected by ion track overlapping, the exposure of oxide targets to spatially random ion impacts was simulated by the Monte Carlo method. Through the Monte Carlo method, the evolutions of the two-dimensional images for the amorphization of TiO2, the lattice structure transformation of ZrO2, and the transition of magnetic states of CeO2 were simulated as a function of ion fluence. The total fractions of the modified areas were calculated from the two-dimensional images. They agree well with the experimental results and those estimated by using the Poisson distribution functions.

UGR CALCULATION BASED ON THE LUMINANCE SPATIAL-ANGULAR DISTRIBUTION

2020 ◽  
Vol 2020 (4) ◽  
pp. 25-32
Author(s):  
Viktor Zheltov ◽  
Viktor Chembaev
Keyword(s):  
Monte Carlo ◽  
Angular Distribution ◽  
Monte Carlo Method ◽  
Visual Task ◽  
New Method ◽  
Lighting System ◽  
Preliminary Assessment ◽  
System A ◽  
The Monte Carlo Method

The article has considered the calculation of the unified glare rating (UGR) based on the luminance spatial-angular distribution (LSAD). The method of local estimations of the Monte Carlo method is proposed as a method for modeling LSAD. On the basis of LSAD, it becomes possible to evaluate the quality of lighting by many criteria, including the generally accepted UGR. UGR allows preliminary assessment of the level of comfort for performing a visual task in a lighting system. A new method of "pixel-by-pixel" calculation of UGR based on LSAD is proposed.

PSHA software review based on the Monte Carlo method

2020 ◽  
pp. 14-24
Author(s):  
V.A. Mironov ◽  
S.A. Peretokin ◽  
K.V. Simonov
Keyword(s):  
Monte Carlo ◽  
Monte Carlo Method ◽  
Seismic Hazard ◽  
Hazard Analysis ◽  
Software Review ◽  
Seismic Hazard Analysis ◽  
Probabilistic Seismic Hazard ◽  
Test Calculation ◽  
Seismic Surveys ◽  
The Monte Carlo Method

The article is a continuation of the software research to perform probabilistic seismic hazard analysis (PSHA) as one of the main stages in engineering seismic surveys. The article provides an overview of modern software for PSHA based on the Monte Carlo method, describes in detail the work of foreign programs OpenQuake Engine and EqHaz. A test calculation of seismic hazard was carried out to compare the functionality of domestic and foreign software.

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