Theoretical analysis and simulation of pedestrian evacuation under invisible conditions

SIMULATION ◽  
2012 ◽  
Vol 88 (9) ◽  
pp. 1138-1148 ◽  
Author(s):  
Ren-Yong Guo ◽  
Hai-Jun Huang
Keyword(s):  
Theoretical Analysis ◽  
Numerical Examples ◽  
Pedestrian Evacuation ◽  
Mean And Variance ◽  
The Mean

We study a class of pedestrian evacuation process in rooms without visibility by analytical and simulative methods. First, the moving distance of pedestrians for leaving the rooms is analyzed using the mean and variance theory. A microscopic pedestrian model is then extended to simulate pedestrian evacuation in the rooms. By numerical examples, the distributions of single individual’s evacuation efficiency in the rooms and the improvement by increasing the number of exits for the individual’s evacuation efficiency are demonstrated. Pedestrians’ moving distances obtained by analytical and simulative methods are also compared. The study is helpful for assessing the efficiency of evacuation and the safety of buildings under conditions of invisibility.

First-order stochastic chemical reactions and oscillations in the variance

1980 ◽  
Vol 17 (04) ◽  
pp. 1087-1093 ◽  
Author(s):  
Richard C. Hertzberg ◽  
Vincent F. Gallucci
Keyword(s):  
General Solution ◽  
Markov Model ◽  
Random Processes ◽  
Numerical Examples ◽  
First Order ◽  
Variance Functions ◽  
First Order Kinetics ◽  
Component Systems ◽  
Mean And Variance ◽  
The Mean

The general solution of a Markov model for first-order kinetics is developed as a sum of independent, multinomially distributed random processes. Fluctuations in the mean and variance functions are discussed and shown to be unrelated in time during the early phase of the reaction. Numerical examples are presented for two- and three-component systems.

First-order stochastic chemical reactions and oscillations in the variance

1980 ◽  
Vol 17 (4) ◽  
pp. 1087-1093 ◽  
Author(s):  
Richard C. Hertzberg ◽  
Vincent F. Gallucci
Keyword(s):  
General Solution ◽  
Markov Model ◽  
Random Processes ◽  
Numerical Examples ◽  
First Order ◽  
Variance Functions ◽  
First Order Kinetics ◽  
Component Systems ◽  
Mean And Variance ◽  
The Mean

The general solution of a Markov model for first-order kinetics is developed as a sum of independent, multinomially distributed random processes. Fluctuations in the mean and variance functions are discussed and shown to be unrelated in time during the early phase of the reaction. Numerical examples are presented for two- and three-component systems.

scholarly journals Robust Inventory Financing Model with Partial Information

2014 ◽  
Vol 2014 ◽  
pp. 1-9 ◽  
Author(s):  
Yong Wang ◽  
Jixiang Zhou ◽  
Hailei Sun ◽  
Lin Jiang
Keyword(s):  
Partial Information ◽  
Robust Method ◽  
Worst Case ◽  
Numerical Examples ◽  
Demand Distribution ◽  
Demand Information ◽  
Mean And Variance ◽  
The Mean ◽  
Financing Model ◽  
Inventory Financing

Given current fast-changing market conditions and difficulty in obtaining financing for small- and medium-sized enterprises, this paper studies the robust inventory financing model under partial information, that is, where the demand distribution is partly known. Two demand information cases are discussed: (1) the mean and variance and (2) the support of the demand distribution. In this setting, the robust method that maximizes the worst-case profit and minimizes the firm’s maximum possible regret of not acting optimally would be used to formulate the optimal sales quantity. We show that the approach used in this paper is tractable, and we provide an explicit expression for the robust optimal policy. We then use numerical examples to compare the firm’s losses under two demand information cases with those occurring under demand certainty. More importantly, the numerical examples indicate that our robust inventory financing model can obtain a robust but not conservative solution.

scholarly journals Weighted statistical binary patterns for facial feature representation

2021 ◽  
Author(s):  
Hung Phuoc Truong ◽  
Thanh Phuong Nguyen ◽  
Yong-Guk Kim
Keyword(s):  
Comprehensive Evaluation ◽  
Facial Feature ◽  
Input Image ◽  
Feature Representation ◽  
Illumination Variation ◽  
Straight Line ◽  
Mean And Variance ◽  
The Mean ◽  
Face Datasets ◽  
Degraded Images

AbstractWe present a novel framework for efficient and robust facial feature representation based upon Local Binary Pattern (LBP), called Weighted Statistical Binary Pattern, wherein the descriptors utilize the straight-line topology along with different directions. The input image is initially divided into mean and variance moments. A new variance moment, which contains distinctive facial features, is prepared by extracting root k-th. Then, when Sign and Magnitude components along four different directions using the mean moment are constructed, a weighting approach according to the new variance is applied to each component. Finally, the weighted histograms of Sign and Magnitude components are concatenated to build a novel histogram of Complementary LBP along with different directions. A comprehensive evaluation using six public face datasets suggests that the present framework outperforms the state-of-the-art methods and achieves 98.51% for ORL, 98.72% for YALE, 98.83% for Caltech, 99.52% for AR, 94.78% for FERET, and 99.07% for KDEF in terms of accuracy, respectively. The influence of color spaces and the issue of degraded images are also analyzed with our descriptors. Such a result with theoretical underpinning confirms that our descriptors are robust against noise, illumination variation, diverse facial expressions, and head poses.

scholarly journals Groups and Individuals: Optical Flow Patterns of Broiler Chicken Flocks Are Correlated with the Behavior of Individual Birds

Animals ◽  
2021 ◽  
Vol 11 (2) ◽  
pp. 568
Author(s):  
Sabine G. Gebhardt-Henrich ◽  
Ariane Stratmann ◽  
Marian Stamp Dawkins
Keyword(s):  
Optical Flow ◽  
Broiler Chicken ◽  
Average Length ◽  
Flow Patterns ◽  
Group Level ◽  
Positive Correlation ◽  
Water Test ◽  
Mean And Variance ◽  
The Mean

Group level measures of welfare flocks have been criticized on the grounds that they give only average measures and overlook the welfare of individual animals. However, we here show that the group-level optical flow patterns made by broiler flocks can be used to deliver information not just about the flock averages but also about the proportion of individuals in different movement categories. Mean optical flow provides information about the average movement of the whole flock while the variance, skew and kurtosis quantify the variation between individuals. We correlated flock optical flow patterns with the behavior and welfare of a sample of 16 birds per flock in two runway tests and a water (latency-to-lie) test. In the runway tests, there was a positive correlation between the average time taken to complete the runway and the skew and kurtosis of optical flow on day 28 of flock life (on average slow individuals came from flocks with a high skew and kurtosis). In the water test, there was a positive correlation between the average length of time the birds remained standing and the mean and variance of flock optical flow (on average, the most mobile individuals came from flocks with the highest mean). Patterns at the flock level thus contain valuable information about the activity of different proportions of the individuals within a flock.

scholarly journals A New Model for the Stochastic Point Reactor: Development and Comparison with Available Models

Energies ◽  
2021 ◽  
Vol 14 (4) ◽  
pp. 955
Author(s):  
Alamir Elsayed ◽  
Mohamed El-Beltagy ◽  
Amnah Al-Juhani ◽  
Shorooq Al-Qahtani
Keyword(s):  
Kinetic Model ◽  
Differential Equations ◽  
Test Cases ◽  
System Of Differential Equations ◽  
Reactor Model ◽  
Time System ◽  
New Model ◽  
Reactor Dynamics ◽  
Mean And Variance ◽  
The Mean

The point kinetic model is a system of differential equations that enables analysis of reactor dynamics without the need to solve coupled space-time system of partial differential equations (PDEs). The random variations, especially during the startup and shutdown, may become severe and hence should be accounted for in the reactor model. There are two well-known stochastic models for the point reactor that can be used to estimate the mean and variance of the neutron and precursor populations. In this paper, we reintroduce a new stochastic model for the point reactor, which we named the Langevin point kinetic model (LPK). The new LPK model combines the advantages, accuracy, and efficiency of the available models. The derivation of the LPK model is outlined in detail, and many test cases are analyzed to investigate the new model compared with the results in the literature.

A model for random instantaneous growth on an interval

1991 ◽  
Vol 28 (3) ◽  
pp. 529-538
Author(s):  
M. P. Quine
Keyword(s):  
Asymptotic Normality ◽  
Instantaneous Growth ◽  
Mean And Variance ◽  
The Mean

Points arrive in succession on an interval and immediately ‘cover' a region of length ½ to each side (less if they are close to the boundary or to a covered part). The location of a new point is uniformly distributed on the uncovered parts. We study the mean and variance of the total number of points ever formed, in particular as a → 0, in which case we also establish asymptotic normality.

Stochastic Analysis of Temperature Distribution in a Solid With Random Heat Conductivity

1988 ◽  
Vol 110 (1) ◽  
pp. 23-29 ◽  
Author(s):  
Da Yu Tzou
Keyword(s):  
Thermal Conductivity ◽  
Temperature Distribution ◽  
Heat Conductivity ◽  
Stochastic Analysis ◽  
Solid Medium ◽  
Mean Value ◽  
Random Response ◽  
Thermal Failure ◽  
Numerical Examples ◽  
The Mean

Stochastic temperature distribution in a solid medium with random heat conductivity is investigated by the method of perturbation. The intrinsic randomness of the thermal conductivity k(x) is considered to be a distribution function with random amplitude in the solid, and several typical stochastic processes are considered in the numerical examples. The formulation used in the present analysis describes a situation that the statistical orders of the random response of the system are the same as those of the intrinsic random excitations, which is characteristic for the problem with extrinsic randomness. The maximum standard deviation of the temperature distribution from the mean value in the solid medium reveals the amount of unexpected energy experienced by the solid continuum, which should be carefully inspected in the thermal-failure design of structures with intrinsic randomness.

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