Описание: This book outlines the transitions between cultured and natural land cover/vegetation types and their implications in the search for alternatives to reverse the trend of anthropogenic environmental degradation. It also elaborates on the proposed “standardized hierarchical Mexican vegetation classification system” and geobotanical mapping, a critical transversal environmental issue. The first chapter consists of an historical review of the common approaches to the study of vegetation both in Mexico and in other regions of the world. The second chapter concisely analyzes the existing schools of thought that have led to the development of vegetation classification systems based on physiognomic, structural and floristic approaches. The focal point of the book is the “standardized hierarchical Mexican vegetation classification system” (SECLAVEMEX – “Sistema jer?rquico estandarizado para la clasificaci?n de la vegetaci?n de M?xico”). Chapter 3 describes the system’s organizational levels along with the criteria defining them and the nomenclatural basis for the denomination of each type of vegetation. It also includes a series of tables explaining and precisely defining the meaning of each concept, criterion, character and element used to help readers successfully identify the type of vegetation in a determined area. The fourth chapter highlights SECLAVEMEX's inclusive character as evidenced through its compatibility with other systems currently used around the globe. Three concepts are critically reviewed: land cover, land use and vegetation. These are often the study subject of the contrasting disciplines geography, agronomy and ecology, which all rely upon plant species assemblages. As such, the final chapter focuses on a critical transversal environmental issue – geobotanical mapping. Geobotanical mapping offers a baseline for land cover/use planning and provides critical information on ecological, economic and cultural attributes, which can be used as a basis for environmental-policy decisions. The proposed SECLAVEMEX was applied to Mexico as an example of land cover, land use and vegetation patterns intermingling as the result of a long human influence. SECLAVEMEX, however, can be adapted and hopefully adopted globally as a baseline for consistently comparing geobotanical patterns and their transitions.
Описание: This book discusses several recent theoretic advancements in interdisciplinary and transdisciplinary integration in the field of evolution. While exploring novel views, the text maintains a close link with one of the most broadly held views on evolution, namely that of “Darwinian evolution.” This work puts forth a new point of view which allows researchers to define in detail the concept of evolution. To create this conceptual definition, the text applies a stringent object-based focus. With this focus, the editor has been able to develop an object-based pattern of evolution at the smallest scale. Subsequently, this smallest scale pattern is used as an innovative basis for generalizations. These generalizations create links between biological Darwinism and generalized Darwinism. The object-based approach that was used to suggest innovations in the field of Darwinian evolution also allowed for contributions to other topics, such as major evolutionary transitions theory, the definition of life and the relationships between evolution, self-organization and thermodynamics. Together, the chapters of this book and the multidisciplinary reflections and comments of various specialists on these chapters offer an exciting palette of innovative ideas.
Автор: Wan, Cen Название: Hierarchical feature selection for knowledge discovery ISBN: 3319979183 ISBN-13(EAN): 9783319979182 Издательство: Springer Рейтинг: Цена: 13974.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This book is the first work that systematically describes the procedure of data mining and knowledge discovery on Bioinformatics databases by using the state-of-the-art hierarchical feature selection algorithms. The novelties of this book are three-fold. To begin with, this book discusses the hierarchical feature selection in depth, which is generally a novel research area in Data Mining/Machine Learning. Seven different state-of-the-art hierarchical feature selection algorithms are discussed and evaluated by working with four types of interpretable classification algorithms (i.e. three types of Bayesian network classification algorithms and the k-nearest neighbours classification algorithm). Moreover, this book discusses the application of those hierarchical feature selection algorithms on the well-known Gene Ontology database, where the entries (terms) are hierarchically structured. Gene Ontology database that unifies the representations of gene and gene products annotation provides the resource for mining valuable knowledge about certain biological research topics, such as the Biology of Ageing. Furthermore, this book discusses the mined biological patterns by the hierarchical feature selection algorithms relevant to the ageing-associated genes. Those patterns reveal the potential ageing-associated factors that inspire future research directions for the Biology of Ageing research.
Описание: While machine learning and robotics recognize the fundamental importance of the hierarchical organization of behavior for building robots that scale up to solve complex tasks, research in psychology and neuroscience shows increasing evidence that modularity and hierarchy are pivotal organization principles of behavior and of the brain.
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