A Methodological Approach to Adjustment of Pedestrian Simulations to Live Scenarios: Example of a German Railway Station

2013 ◽  
pp. 161-170
Author(s):  
Maria Davidich ◽  
Gerta Köster
2006 ◽  
Vol 18 (4) ◽  
pp. 160-173 ◽  
Author(s):  
Maria Senokozlieva ◽  
Oliver Fischer ◽  
Gary Bente ◽  
Nicole Krämer

Abstract. TV news are essentially cultural phenomena. Previous research suggests that the often-overlooked formal and implicit characteristics of newscasts may be systematically related to culture-specific characteristics. Investigating these characteristics by means of a frame-by-frame content analysis is identified as a particularly promising methodological approach. To examine the relationship between culture and selected formal characteristics of newscasts, we present an explorative study that compares material from the USA, the Arab world, and Germany. Results indicate that there are many significant differences, some of which are in line with expectations derived from cultural specifics. Specifically, we argue that the number of persons presented as well as the context in which they are presented can be interpreted as indicators of Individualism/Collectivism. The conclusions underline the validity of the chosen methodological approach, but also demonstrate the need for more comprehensive and theory-driven category schemes.


2010 ◽  
Vol 72 (08/09) ◽  
Author(s):  
A Ahmad ◽  
R Krumkamp ◽  
S Mounier-Jack ◽  
R Reintjes ◽  
R Coker

2020 ◽  
Vol 39 (5) ◽  
pp. 6419-6430
Author(s):  
Dusan Marcek

To forecast time series data, two methodological frameworks of statistical and computational intelligence modelling are considered. The statistical methodological approach is based on the theory of invertible ARIMA (Auto-Regressive Integrated Moving Average) models with Maximum Likelihood (ML) estimating method. As a competitive tool to statistical forecasting models, we use the popular classic neural network (NN) of perceptron type. To train NN, the Back-Propagation (BP) algorithm and heuristics like genetic and micro-genetic algorithm (GA and MGA) are implemented on the large data set. A comparative analysis of selected learning methods is performed and evaluated. From performed experiments we find that the optimal population size will likely be 20 with the lowest training time from all NN trained by the evolutionary algorithms, while the prediction accuracy level is lesser, but still acceptable by managers.


Author(s):  
O. M. Korchazhkina

The article presents a methodological approach to studying iterative processes in the school course of geometry, by the example of constructing a Koch snowflake fractal curve and calculating a few characteristics of it. The interactive creative environment 1C:MathKit is chosen to visualize the method discussed. By performing repetitive constructions and algebraic calculations using ICT tools, students acquire a steady skill of work with geometric objects of various levels of complexity, comprehend the possibilities of mathematical interpretation of iterative processes in practice, and learn how to understand the dialectical unity between finite and infinite parameters of flat geometric figures. When students are getting familiar with such contradictory concepts and categories, that replenishes their experience of worldview comprehension of the subject areas they study through the concept of “big ideas”. The latter allows them to take a fresh look at the processes in the world around. The article is a matter of interest to schoolteachers of computer science and mathematics, as well as university scholars who teach the course “Concepts of modern natural sciences”.


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