Recent advances in the theory and practice of logical analysis of data

Logical Analysis of Data (LAD) is a data analysis methodology introduced by Peter L. Hammer in 1986. LAD distinguishes itself from other classification and machine learning methods by the fact that it analyzes a significant subset of combinations of variables to describe the positive or negative nature of an observation and uses combinatorial techniques to extract models defined in terms of patterns. In recent years, the methodology has tremendously advanced through numerous theoretical developments and practical applications. In the present paper, we review the methodology and its recent advances, describe novel applications in engineering, finance, health care, and algorithmic techniques for some stochastic optimization problems, and provide a comparative description of LAD with well-known classification methods

Experiments with two-stage iterative solvers and preconditioned Krylov subspace methods on nearly completely decomposable Markov chains

Ankara : Department of Computer Engineering and Information Science and the Institute of Engineering and Science of Bilkent University, 1997.Thesis (Master's) -- Bilkent University, 1997.Includes bibliographical references leaves 121-124Gueaieb, WailM.S

完全可換クイバーの区間近似とその応用

京都大学新制・課程博士博士(理学)甲第25087号理博第4994号京都大学大学院理学研究科数学・数理解析専攻(主査)教授 平岡 裕章, 教授 COLLINSBenoit Vincent Pierre, 教授 坂上 貴之学位規則第4条第1項該当Doctor of ScienceKyoto UniversityDFA

Transient seasonal and chronic poverty of peasants: Evidence from Rwanda

Using panel data from Rwanda, we estimate seasonal transient and chronic poverty indices, for different poverty lines, poverty indicators, equivalence scales, and with and without corrections for price variability and for the sampling scheme. We also estimate sampling standard errors for the poverty indices. The worst poverty crises occur after the dry season at the end of the year. Most of the severity of poverty comes from the seasonal transient component of annual poverty, while the seasonal component of the incidence of poverty is much smaller. Thus the actual differences in the severity of poverty, either between developing and industrial countries or between rural and urban areas in LDCs, may be much worse than is shown by the usual chronic annual poverty measures or by measures of seasonal incidence of poverty. The importance of the transient component suggests a need for an income stabilisation policy. However, the contribution of the global transient seasonal poverty is important for households clustered around the poverty line, but low for the poorest part of the chronically poor. Thus, policies fighting seasonal transient poverty are likely to concern the moderately poor rather than the very poor, as compared with policies against chronic poverty, which affect the very poor. The probability transition analysis across seasonal living standard distributions shows that mobility across quintiles is always very strong. The poverty crisis in the last season is more the result of many peasants falling into poverty than a decrease in the flow out of poverty. A ‘safety net’ policy aimed at the poor and the non-poor at this period would then be appropriate. We estimate equations of quantiles for household chronic and transient seasonal poverty. The agricultural choices of peasants are found to affect differently the two components of annual poverty that could therefore be addressed by a combination of policies specific to each component.

Data-Driven Fault Detection and Reasoning for Industrial Monitoring

This open access book assesses the potential of data-driven methods in industrial process monitoring engineering. The process modeling, fault detection, classification, isolation, and reasoning are studied in detail. These methods can be used to improve the safety and reliability of industrial processes. Fault diagnosis, including fault detection and reasoning, has attracted engineers and scientists from various fields such as control, machinery, mathematics, and automation engineering. Combining the diagnosis algorithms and application cases, this book establishes a basic framework for this topic and implements various statistical analysis methods for process monitoring. This book is intended for senior undergraduate and graduate students who are interested in fault diagnosis technology, researchers investigating automation and industrial security, professional practitioners and engineers working on engineering modeling and data processing applications. This is an open access book

Data-Driven Fault Detection and Reasoning for Industrial Monitoring

This open access book assesses the potential of data-driven methods in industrial process monitoring engineering. The process modeling, fault detection, classification, isolation, and reasoning are studied in detail. These methods can be used to improve the safety and reliability of industrial processes. Fault diagnosis, including fault detection and reasoning, has attracted engineers and scientists from various fields such as control, machinery, mathematics, and automation engineering. Combining the diagnosis algorithms and application cases, this book establishes a basic framework for this topic and implements various statistical analysis methods for process monitoring. This book is intended for senior undergraduate and graduate students who are interested in fault diagnosis technology, researchers investigating automation and industrial security, professional practitioners and engineers working on engineering modeling and data processing applications. This is an open access book

Irreversibility, coherence and quantum fluctuation theorems

Irreversible processes have long been the focus of much attention in physics, forming cornerstones of thermodynamics and the foundations of quantum mechanics (principally the measurement problem). Recent interest in the marriage of these two fields has laid bare the partial inadequacy of definitions of thermodynamic work in a quantum context. Its problems are fundamental to quantum mechanics, in that projective measurements irreversibly destroy coherence in a state. To attempt to resolve this incompatibility, we begin with a deterministic quantum work process that adequately generalises the Newtonian framework for deterministic work processes. In doing so, we uncover a structure that has strong links to an old problem in probability theory on the decomposability of random variables. Crucially, we define coherent work as a state and Hamiltonian pair, sidestepping the measurement problem. We then look to fluctuation theorems which detail the thermodynamic irreversibility, and further develop a recent framework to show how our coherent work state appears just as Newtonian work appears in Crooks’ fluctuation theorem – providing an infinite hierarchy of correction terms. To round this off, we discuss the implications of incorporating additional observables, both commuting and complementary, on work processes and thermodynamics.Open Acces

North American Fuzzy Logic Processing Society (NAFIPS 1992), volume 2

This document contains papers presented at the NAFIPS '92 North American Fuzzy Information Processing Society Conference. More than 75 papers were presented at this Conference, which was sponsored by NAFIPS in cooperation with NASA, the Instituto Tecnologico de Morelia, the Indian Society for Fuzzy Mathematics and Information Processing (ISFUMIP), the Instituto Tecnologico de Estudios Superiores de Monterrey (ITESM), the International Fuzzy Systems Association (IFSA), the Japan Society for Fuzzy Theory and Systems, and the Microelectronics and Computer Technology Corporation (MCC). The fuzzy set theory has led to a large number of diverse applications. Recently, interesting applications have been developed which involve the integration of fuzzy systems with adaptive processes such a neural networks and genetic algorithms. NAFIPS '92 was directed toward the advancement, commercialization, and engineering development of these technologies

Topics in multidimensional persistence

A multiparameter persistence module is a representation of the lattice quiver Nd, where maps along all squares commute. When d = 1, Gabriel’s theorem applies and these modules admit interval decompositions, allowing us to classify one dimen- sional persistence modules through their associated barcode, a combinatorial invariant first introduced in by Carlsson and Zomorodian. When d > 1, no such classification is possible. In this thesis we study these higher dimensional persistence modules, seeking to over- come their lack of simple classification by defining discrete invariants with as much discriminative power as possible. The thesis is composed of three parts. First, we give an in depth analysis of barcode bases. These are bases of one-dimensional persistence modules that realise the interval decom- position given by Gabriel’s theorem. We present a novel algorithm that computes these barcode bases, and give theoretical results that characterise the set of barcode bases of a given persistence module. This allows for a decomposition results of certain types of ladder persistence modules. We generalise all these results to zigzag persistence. Second, we consider Harder-Narasimhan filtrations for quiver representations and define the skyscraper invariant, a novel discrete invariant for multidimensional persistence which is finer than the rank invariant. We further show the skyscraper invariant can be refined to create a complete invariant on certain families of ladder persistence modules. Finally, we discuss computation methods for the skyscraper invariant. We exhibit an algorithm that computes the skyscraper invariant for ladder persistence modules. This is done by leveraging the decomposition result for ladder persistence modules from the first chapter. In doing so, we introduce the ladder invariant, which is computable and more discriminative than the rank invariant. It coincides with the skyscraper invariant on ladder persistence modules and is non-comparable to the skyscraper invariant in general. Algorithms from the first chapter are given as pseudo-code. These were later implemented as a python package and we give an overview of this package in the appendix