A Sociocybernetics Data Analysis Using Causality in Tourism Networks

The aim of this paper is to propose a mathematical model to determine invariant sets, set covering, orbits and, in particular, attractors in the set of tourism variables. Analysis was carried out based on a pre-designed algorithm and applying our interpretation of chaos theory developed in the context of General Systems Theory. This article sets out the causal relationships associated with tourist flows in order to enable the formulation of appropriate strategies. Our results can be applied to numerous cases. For example, in the analysis of tourist flows, these findings can be used to determine whether the behaviour of certain groups affects that of other groups and to analyse tourist behaviour in terms of the most relevant variables. Unlike statistical analyses that merely provide information on current data, our method uses orbit analysis to forecast, if attractors are found, the behaviour of tourist variables in the immediate future.

Convergence analysis and validation of low cost distance metrics for computational cost reduction of the Iterative Closest Point algorithm

The Iterative Closest Point algorithm (ICP) is commonly used in engineering applications to solve the rigid registration problem of partially overlapped point sets which are pre-aligned with a coarse estimate of their relative positions. This iterative algorithm is applied in many areas such as the medicine for volumetric reconstruction of tomography data, in robotics to reconstruct surfaces or scenes using range sensor information, in industrial systems for quality control of manufactured objects or even in biology to study the structure and folding of proteins. One of the algorithm’s main problems is its high computational complexity (quadratic in the number of points with the non-optimized original variant) in a context where high density point sets, acquired by high resolution scanners, are processed. Many variants have been proposed in the literature whose goal is the performance improvement either by reducing the number of points or the required iterations or even enhancing the complexity of the most expensive phase: the closest neighbor search. In spite of decreasing its complexity, some of the variants tend to have a negative impact on the final registration precision or the convergence domain thus limiting the possible application scenarios. The goal of this work is the improvement of the algorithm’s computational cost so that a wider range of computationally demanding problems from among the ones described before can be addressed. For that purpose, an experimental and mathematical convergence analysis and validation of point-to-point distance metrics has been performed taking into account those distances with lower computational cost than the Euclidean one, which is used as the de facto standard for the algorithm’s implementations in the literature. In that analysis, the functioning of the algorithm in diverse topological spaces, characterized by different metrics, has been studied to check the convergence, efficacy and cost of the method in order to determine the one which offers the best results. Given that the distance calculation represents a significant part of the whole set of computations performed by the algorithm, it is expected that any reduction of that operation affects significantly and positively the overall performance of the method. As a result, a performance improvement has been achieved by the application of those reduced cost metrics whose quality in terms of convergence and error has been analyzed and validated experimentally as comparable with respect to the Euclidean distance using a heterogeneous set of objects, scenarios and initial situations.

Application of the Hidden Markov Model for Innovative Projects "Viability" Analysis

This master thesis deals with determining of innovative projects "viability". "Viability" is the probability of innovative project being implemented. Hidden Markov Models are used for evaluation of this factor. The problem of determining parameters of model, which produce given data sequence with the highest probability, are solving in this research. Data about innovative projects contained in reports of Russian programs "UMNIK", "START" and additional data obtained during study are used as input data for determining of model parameters. The Baum-Welch algorithm which is one implementation of expectation-maximization algorithm is used at this research for calculating model parameters. At the end part of the master thesis mathematical basics for practical implementation are given (in particular mathematical description of the algorithm and implementation methods for Markov models).

Methods of visualization and analysis of cardiac depolarization in the three dimensional space

The master thesis presents methods for intellectual analysis and visualization 3D EKG in order to increase the efficiency of ECG analysis by extracting additional data. Visualization is presented as part of the signal analysis tasks considered imaging techniques and their mathematical description. Have been developed algorithms for calculating and visualizing the signal attributes are described using mathematical methods and tools for mining signal. The model of patterns searching for comparison purposes of accuracy of methods was constructed, problems of a clustering and classification of data are solved, the program of visualization of data is also developed. This approach gives the largest accuracy in a task of the intellectual analysis that is confirmed in this work. Considered visualization and analysis techniques are also applicable to the multi-dimensional signals of a different kind.

Analysis of coastal sediment transport processes from Wrightsville Beach to Fort Fisher, North Carolina /

A comprehensive engineering analysis of the coastal sediment transport processes along a 42-kilometer segment of the North Carolina shoreline from Wrightsville Beach to Fort Fisher is presented. Included in the analysis is an interpretation of the littoral processes, longshore transport, and the behavior and success of beach nourishment projects at Wrightsville Beach and Carolina Beach, North Carolina. The historical position of the MLW, MSL, and MHW contours, relative to a fixed base line, is plotted for the period between 1964 and 1975. An equivalent volumetric erosion or accretion between successive surveys is determined by multiplying the average excursion distance of the contours by a constant of proportionality. The plots of excursion distance versus time for the MLW, MSL, and MHW contours also show the time response of the beach fills. This response is described by a mathematical function. The alongshore components of wave-induced energy flux are also determined within the study area through wave refraction analysis. This information, together with the information on volumetric change, is used in a sediment budget analysis to determine the coefficient of alongshore sediment transport and the inlet trapping characteristics. (Author).

Statistical analysis of the goodness of classical factor analysis regression (CFAR) /

Cover title.

Long Beach Harbor numerical analysis of harbor oscillations :

"September 1976."

Long Beach Harbor numerical analysis of harbor oscillations :

"September 1976."

Long Beach Harbor numerical analysis of harbor oscillations :

"February 1977."

Mathematical reconstruction of highway accidents. Interim technical report.

National Highway Traffic Safety Administration, Washington, D.C.

Sensitivity analysis for heuristic algorithms /

"UILU-ENG 78 1731."

NBS-INA, The Institute for Numerical Analysis, UCLA 1947-1954 /

"August 1991."

The analysis of economic time series.

"Originally published as Monograph no.6 of the Cowles Commission for Research in Economics."

Reactor analysis

Mode of access: Internet.

Statistical analysis and optimization of systems.

Bibliography: p. 185-187.