Definition and solution of a new approximate variant of the order preserving matching problem

En esta tesis se combinan dos problemas de búsqueda de cadenas: la búsqueda aproximada de cadenas bajo parámetros δγ, y el emparejamiento con preservación de orden. Uno permite un nivel de error en la búsqueda, mientras que el otro considera la estructura interna de las cadenas en lugar de sus valores absolutos. Se define formalmente el Emparejamiento con preservación de orden bajo distancias δγ. Se diseñaron e implementaron en C++ cuatro algoritmos que resuelven el problema, y una configuración experimental para compararlos. El algoritmo más simple, tiene complejidad O(nm lg m). El segundo tiene una complejidad de O(nm). El tercero y el cuarto se basan en estructuras de datos: árbol de segmentos y árbol de fenwick respectivamente. Ambos tienen complejidad O(nm lg n). Los resultados experimentales muestran que los algoritmos basados en estructuras de datos tiene un mejor rendimiento en muchos casos. El de mejor rendimiento experimental es del basado en el árbol Fenwick, seguido por el basado en árboles de segmentos. Estos resultados se pueden explicar debido a su complejidad Ω(n lg n). Se muestran aplicaciones en música y finanzas.Abstract: In this thesis we combine two string searching related problems: the approximate string matching under parameters δ and γ, and the order preserving matching problem. Orderpreserving matching regards the internal structure of the strings rather than their absolute values while matching under δ and γ distances permit a level of error. We formally define the δγ–order-preserving matching problem. We designed and implement in C++ four algorithms that solve the proposed problem and an experimental setup to compare them. The first algorithm is the naive algorithm with complexity Θ(nm lg m) time. The second has a complexity of Θ(nm) time. The third and four algorithms are based on the segment tree and Fenwick tree data structures, respectively, and both have O(nm log n) time complexities. The data structure based algorithms show better experimental performance due to their better lower bound of Ω(n lg n) complexity. We show applications in music and finance.Maestrí

Introduction to Facial Micro Expressions Analysis Using Color and Depth Images: A Matlab Coding Approach (Second Edition, 2023)

The book attempts to introduce a gentle introduction to the field of Facial Micro Expressions Recognition (FMER) using Color and Depth images, with the aid of MATLAB programming environment. FMER is a subset of image processing and it is a multidisciplinary topic to analysis. So, it requires familiarity with other topics of Artifactual Intelligence (AI) such as machine learning, digital image processing, psychology and more. So, it is a great opportunity to write a book which covers all of these topics for beginner to professional readers in the field of AI and even without having background of AI. Our goal is to provide a standalone introduction in the field of MFER analysis in the form of theorical descriptions for readers with no background in image processing with reproducible Matlab practical examples. Also, we describe any basic definitions for FMER analysis and MATLAB library which is used in the text, that helps final reader to apply the experiments in the real-world applications. We believe that this book is suitable for students, researchers, and professionals alike, who need to develop practical skills, along with a basic understanding of the field. We expect that, after reading this book, the reader feels comfortable with different key stages such as color and depth image processing, color and depth image representation, classification, machine learning, facial micro-expressions recognition, feature extraction and dimensionality reduction. The book attempts to introduce a gentle introduction to the field of Facial Micro Expressions Recognition (FMER) using Color and Depth images, with the aid of MATLAB programming environment.Comment: This is the second edition of the boo