Global ETD Search

1	Exploring Ways of Identifying Outliers in Spatial Point Patterns Liu, Jie 01 May 2015 (has links) This work discusses alternative methods to detect outliers in spatial point patterns. Outliers are defined based on location only and also with respect to associated variables. Throughout the thesis we discuss five case studies, three of them come from experiments with spiders and bees, and the other two are data from earthquakes in a certain region. One of the main conclusions is that when detecting outliers from the point of view of location we need to take into consideration both the degree of clustering of the events and the context of the study. When detecting outliers from the point of view of an associated variable, outliers can be identified from a global or local perspective. For global outliers, one of the main questions addressed is whether the outliers tend to be clustered or randomly distributed in the region. All the work was done using the R programming language. spatial data outlier distance method statistics. Mathematics
2	A multi-exchange heuristic for formation of balanced disjoint rings Sasi Kumar, Sarath K 30 October 2006 (has links) Telecommunication networks form an integral part of life. Avoiding failures on these networks is always not possible. Designing network structures that survive these failures have become important in ensuring the reliability of these network structures. With the introduction of SONET (Synchronous Optical Network) technology, rings have become the preferred survivable network structure. This network configuration has a set of disjoint rings (each node being a part of single ring), and these disjoint rings are connected via another main ring. In this research, we present a mathematical model for the design of such disjoint rings with node number balance criterion among the rings. When, given a set of nodes and distances between them, the Balanced Disjoint Rings (BDR) problem is the minimum total link length clustering of nodes into a given number of disjoint rings in such a way that there is almost the same number of nodes in each ring. The BDR problem is a class of the standard Traveling Salesman Problem (TSP). It is clear from this observation that the BDR problem becomes a TSP when the number of rings required is set to one. Hence BDR is NP-Hard, and we do not expect to obtain a polynomial time algorithm for its solution. To overcome this problem, we developed a set of construction heuristics (Break-MST, Distance Method, Hybrid Method, GRASP-Based Distance Method) and improvement heuristics (Multi-Exchange, Single Move). Different combinations of construction and improvement heuristics were implemented and the quality of solution thus obtained was compared to the standard Branch and Cut Technique. It was found that the algorithm with GRASP-Based Distance Method as the construction heuristic and multi-exchange - single-move combination as the improvement heuristic performed better than other combinations. All combinations performed better in general than the standard Branch and Cut technique in terms of solution time. Multi-Exchange Distance Method Hybrid Method GRASP
3	Analysis of Heuristic Validity, Efficiency and Applicability of the Profile Distance Method for Implementation in Decision Support Systems Bernroider, Edward, Obwegeser, Nikolaus, Stix, Volker 05 1900 (has links) (PDF) This article seeks to enhance acceptance of the profile distance method (PDM) in decision support systems. The PDM is a multiple attributive based decision making as well as a multiple method approach to support complex decision making and uses a heuristic to avoid computationally complex global optimization. We elaborate on the usability of the method and question the heuristic used. We present a bisection algorithm, which efficiently supports the discovery of transition profiles needed in a user-friendly and practical application of the method. Additionally, we provide empirical evidence showing that the proposed heuristic is efficient and delivers results within 5% of the global optimizer for a wide range of data sets.
4	A Likelihood Method to Estimate/Detect Gene Flow and A Distance Method to Estimate Species Trees in the Presence of Gene Flow Cui, Lingfei January 2014 (has links) No description available. Bioinformatics Biology Evolution and Development Biostatistics population genetics demographic parameter inference evolution phylogenetic inference isolation-with-migration gene flow distance method
5	Process capability assessment for univariate and multivariate non-normal correlated quality characteristics Ahmad, Shafiq, Shafiq.ahmad@rmit.edu.au January 2009 (has links) In today's competitive business and industrial environment, it is becoming more crucial than ever to assess precisely process losses due to non-compliance to customer specifications. To assess these losses, industry is extensively using Process Capability Indices for performance evaluation of their processes. Determination of the performance capability of a stable process using the standard process capability indices such as and requires that the underlying quality characteristics data follow a normal distribution. However it is an undisputed fact that real processes very often produce non-normal quality characteristics data and also these quality characteristics are very often correlated with each other. For such non-normal and correlated multivariate quality characteristics, application of standard capability measures using conventional methods can lead to erroneous results. The research undertaken in this PhD thesis presents several capability assessment methods to estimate more precisely and accurately process performances based on univariate as well as multivariate quality characteristics. The proposed capability assessment methods also take into account the correlation, variance and covariance as well as non-normality issues of the quality characteristics data. A comprehensive review of the existing univariate and multivariate PCI estimations have been provided. We have proposed fitting Burr XII distributions to continuous positively skewed data. The proportion of nonconformance (PNC) for process measurements is then obtained by using Burr XII distribution, rather than through the traditional practice of fitting different distributions to real data. Maximum likelihood method is deployed to improve the accuracy of PCI based on Burr XII distribution. Different numerical methods such as Evolutionary and Simulated Annealing algorithms are deployed to estimate parameters of the fitted Burr XII distribution. We have also introduced new transformation method called Best Root Transformation approach to transform non-normal data to normal data and then apply the traditional PCI method to estimate the proportion of non-conforming data. Another approach which has been introduced in this thesis is to deploy Burr XII cumulative density function for PCI estimation using Cumulative Density Function technique. The proposed approach is in contrast to the approach adopted in the research literature i.e. use of best-fitting density function from known distributions to non-normal data for PCI estimation. The proposed CDF technique has also been extended to estimate process capability for bivariate non-normal quality characteristics data. A new multivariate capability index based on the Generalized Covariance Distance (GCD) is proposed. This novel approach reduces the dimension of multivariate data by transforming correlated variables into univariate ones through a metric function. This approach evaluates process capability for correlated non-normal multivariate quality characteristics. Unlike the Geometric Distance approach, GCD approach takes into account the scaling effect of the variance-covariance matrix and produces a Covariance Distance variable that is based on the Mahanalobis distance. Another novelty introduced in this research is to approximate the distribution of these distances by a Burr XII distribution and then estimate its parameters using numerical search algorithm. It is demonstrates that the proportion of nonconformance (PNC) using proposed method is very close to the actual PNC value. Process Capability Indices ( and ) Non-normal multivariate data proportion of non-conformance (PNC) Correlated data Burr XII distribution Best Root Transformation approach Cumulative Density Function technique Simulated Annealing Evolutionary algorithm Geometric Distance method (GD) Generalized Covariance Distance (GCD).
6	Channel Probing for an Indoor Wireless Communications Channel Hunter, Brandon 13 March 2003 (has links) (PDF) The statistics of the amplitude, time and angle of arrival of multipaths in an indoor environment are all necessary components of multipath models used to simulate the performance of spatial diversity in receive antenna configurations. The model presented by Saleh and Valenzuela, was added to by Spencer et. al., and included all three of these parameters for a 7 GHz channel. A system was built to measure these multipath parameters at 2.4 GHz for multiple locations in an indoor environment. Another system was built to measure the angle of transmission for a 6 GHz channel. The addition of this parameter allows spatial diversity at the transmitter along with the receiver to be simulated. The process of going from raw measurement data to discrete arrivals and then to clustered arrivals is analyzed. Many possible errors associated with discrete arrival processing are discussed along with possible solutions. Four clustering methods are compared and their relative strengths and weaknesses are pointed out. The effects that errors in the clustering process have on parameter estimation and model performance are also simulated. multipath multipath propagation propagation environment indoor propagation indoor multipath indoor multipath propagation channel probing channel probing indoor wireless communications channel indoor wireless communications indoor wireless communications wireless communications wireless communications channel MIMO SISO multiple input multiple output single input single output antenna diversity antenna diversity antenna array channel modeling modeling model wireless propagation clustering methods clustering algorithms clustering parameter estimation parameter channel matrix h matrix ray tracing point spread function psf deconvolution clean algorithm clean algorithm antenna pattern network analyzer temporal pattern 2.4 ghz system 6 ghz system channel capacity capacity estimate channel capacity estimate propagation environment scattering transfer matrix matrix water filling solution water filling method water filling Saleh Valenzuela Saleh and Valenzuela Model arrival time of arrival angle of arrival direction of arrival arrival amplitude arrivals antenna positioner data simulations measurements angle of departure direction of departure correlation convolution errors error CFA CFAD constant false alarm constant false alarm detection signal signal dependent clutter clutter returns transmitter transmit receive receiver transmit antenna receive antenna spatial correlation system PSF system point spread function mapping fuzzy c-means clustering fuzzy clustering c-means clustering c-means fuzzy k-means euclidean distance time amplitude delay performance prediction performance prediction errors fuzzy weighted distance method rectangular method weighted rectangular method statistics statistical statistical model Electrical and Computer Engineering

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