Nature Inspired Optimization Algorithms

Nature Inspired Optimization Algorithms
Author: Xin-She Yang
Publsiher: Elsevier
Total Pages: 300
Release: 2014-02-17
ISBN 10: 0124167454
ISBN 13: 9780124167452
Language: EN, FR, DE, ES & NL

Nature Inspired Optimization Algorithms Book Review:

Nature-Inspired Optimization Algorithms provides a systematic introduction to all major nature-inspired algorithms for optimization. The book's unified approach, balancing algorithm introduction, theoretical background and practical implementation, complements extensive literature with well-chosen case studies to illustrate how these algorithms work. Topics include particle swarm optimization, ant and bee algorithms, simulated annealing, cuckoo search, firefly algorithm, bat algorithm, flower algorithm, harmony search, algorithm analysis, constraint handling, hybrid methods, parameter tuning and control, as well as multi-objective optimization. This book can serve as an introductory book for graduates, doctoral students and lecturers in computer science, engineering and natural sciences. It can also serve a source of inspiration for new applications. Researchers and engineers as well as experienced experts will also find it a handy reference. Discusses and summarizes the latest developments in nature-inspired algorithms with comprehensive, timely literature Provides a theoretical understanding as well as practical implementation hints Provides a step-by-step introduction to each algorithm

Nature Inspired Optimization Algorithms

Nature Inspired Optimization Algorithms
Author: Xin-She Yang
Publsiher: Unknown
Total Pages: 276
Release: 2016-07
ISBN 10: 9780128100608
ISBN 13: 0128100605
Language: EN, FR, DE, ES & NL

Nature Inspired Optimization Algorithms Book Review:

Nature-Inspired Optimization Algorithms provides a systematic introduction to all major nature-inspired algorithms for optimization. The book's unified approach, balancing algorithm introduction, theoretical background and practical implementation, complements extensive literature with well-chosen case studies to illustrate how these algorithms work. Topics include particle swarm optimization, ant and bee algorithms, simulated annealing, cuckoo search, firefly algorithm, bat algorithm, flower algorithm, harmony search, algorithm analysis, constraint handling, hybrid methods, parameter tuning and control, as well as multi-objective optimization. This book can serve as an introductory book for graduates, doctoral students and lecturers in computer science, engineering and natural sciences. It can also serve a source of inspiration for new applications. Researchers and engineers as well as experienced experts will also find it a handy reference. Discusses and summarizes the latest developments in nature-inspired algorithms with comprehensive, timely literature Provides a theoretical understanding as well as practical implementation hints Provides a step-by-step introduction to each algorithm

Nature Inspired Optimization Algorithms

Nature Inspired Optimization Algorithms
Author: Vasuki A
Publsiher: CRC Press
Total Pages: 260
Release: 2020-05-31
ISBN 10: 1000076601
ISBN 13: 9781000076608
Language: EN, FR, DE, ES & NL

Nature Inspired Optimization Algorithms Book Review:

Nature-Inspired Optimization Algorithms, a comprehensive work on the most popular optimization algorithms based on nature, starts with an overview of optimization going from the classical to the latest swarm intelligence algorithm. Nature has a rich abundance of flora and fauna that inspired the development of optimization techniques, providing us with simple solutions to complex problems in an effective and adaptive manner. The study of the intelligent survival strategies of animals, birds, and insects in a hostile and ever-changing environment has led to the development of techniques emulating their behavior. This book is a lucid description of fifteen important existing optimization algorithms based on swarm intelligence and superior in performance. It is a valuable resource for engineers, researchers, faculty, and students who are devising optimum solutions to any type of problem ranging from computer science to economics and covering diverse areas that require maximizing output and minimizing resources. This is the crux of all optimization algorithms. Features: Detailed description of the algorithms along with pseudocode and flowchart Easy translation to program code that is also readily available in Mathworks website for some of the algorithms Simple examples demonstrating the optimization strategies are provided to enhance understanding Standard applications and benchmark datasets for testing and validating the algorithms are included This book is a reference for undergraduate and post-graduate students. It will be useful to faculty members teaching optimization. It is also a comprehensive guide for researchers who are looking for optimizing resources in attaining the best solution to a problem. The nature-inspired optimization algorithms are unconventional, and this makes them more efficient than their traditional counterparts.

Nature Inspired Optimization Algorithms for Fuzzy Controlled Servo Systems

Nature Inspired Optimization Algorithms for Fuzzy Controlled Servo Systems
Author: Radu-Emil Precup,Radu-Codrut David
Publsiher: Butterworth-Heinemann
Total Pages: 220
Release: 2019-05-15
ISBN 10: 0128163585
ISBN 13: 9780128163580
Language: EN, FR, DE, ES & NL

Nature Inspired Optimization Algorithms for Fuzzy Controlled Servo Systems Book Review:

Nature-inspired Optimization Algorithms for Fuzzy Controlled Servo Systems suits the general need of a book that explains the major issues to fuzzy control in servo systems without any solid mathematical prerequisite. In addition, pertinent information on nature-inspired optimization algorithms is offered. The book is intended to rapidly make intelligible notions of fuzzy set theory and fuzzy control to readers with limited experience. The attractive analysis and design methodologies dedicated to fuzzy controllers are accompanied by applications to servo systems and case studies in fuzzy controlled servo systems are organized in a special chapter of this book, and allow simple implementations of low-cost automation solutions. The theoretical approaches presented throughout the book are validated by the illustration of digital simulation results and real-time experimental results as well. This book aims at a large category of audience including graduate students, engineers (designers, practitioners and researchers), and everyone who faces challenging control problems. Gives a merge between classical and modern approaches to fuzzy control Presents in a unified structure from the point of view of a control engineer the essential aspects regarding fuzzy control in servo systems Makes intelligible notions of fuzzy set theory and fuzzy control to readers with limited experience

Nature Inspired Algorithms and Applied Optimization

Nature Inspired Algorithms and Applied Optimization
Author: Xin-She Yang
Publsiher: Springer
Total Pages: 330
Release: 2017-10-08
ISBN 10: 3319676695
ISBN 13: 9783319676692
Language: EN, FR, DE, ES & NL

Nature Inspired Algorithms and Applied Optimization Book Review:

This book reviews the state-of-the-art developments in nature-inspired algorithms and their applications in various disciplines, ranging from feature selection and engineering design optimization to scheduling and vehicle routing. It introduces each algorithm and its implementation with case studies as well as extensive literature reviews, and also includes self-contained chapters featuring theoretical analyses, such as convergence analysis and no-free-lunch theorems so as to provide insights into the current nature-inspired optimization algorithms. Topics include ant colony optimization, the bat algorithm, B-spline curve fitting, cuckoo search, feature selection, economic load dispatch, the firefly algorithm, the flower pollination algorithm, knapsack problem, octonian and quaternion representations, particle swarm optimization, scheduling, wireless networks, vehicle routing with time windows, and maximally different alternatives. This timely book serves as a practical guide and reference resource for students, researchers and professionals.

Introduction to Nature Inspired Optimization

Introduction to Nature Inspired Optimization
Author: George Lindfield,John Penny
Publsiher: Academic Press
Total Pages: 256
Release: 2017-08-10
ISBN 10: 0128036664
ISBN 13: 9780128036662
Language: EN, FR, DE, ES & NL

Introduction to Nature Inspired Optimization Book Review:

Introduction to Nature-Inspired Optimization brings together many of the innovative mathematical methods for non-linear optimization that have their origins in the way various species behave in order to optimize their chances of survival. The book describes each method, examines their strengths and weaknesses, and where appropriate, provides the MATLAB code to give practical insight into the detailed structure of these methods and how they work. Nature-inspired algorithms emulate processes that are found in the natural world, spurring interest for optimization. Lindfield/Penny provide concise coverage to all the major algorithms, including genetic algorithms, artificial bee colony algorithms, ant colony optimization and the cuckoo search algorithm, among others. This book provides a quick reference to practicing engineers, researchers and graduate students who work in the field of optimization. Applies concepts in nature and biology to develop new algorithms for nonlinear optimization Offers working MATLAB® programs for the major algorithms described, applying them to a range of problems Provides useful comparative studies of the algorithms, highlighting their strengths and weaknesses Discusses the current state-of-the-field and indicates possible areas of future development

Nature inspired Metaheuristic Algorithms

Nature inspired Metaheuristic Algorithms
Author: Xin-She Yang
Publsiher: Luniver Press
Total Pages: 148
Release: 2010
ISBN 10: 1905986289
ISBN 13: 9781905986286
Language: EN, FR, DE, ES & NL

Nature inspired Metaheuristic Algorithms Book Review:

Modern metaheuristic algorithms such as bee algorithms and harmony search start to demonstrate their power in dealing with tough optimization problems and even NP-hard problems. This book reviews and introduces the state-of-the-art nature-inspired metaheuristic algorithms in optimization, including genetic algorithms, bee algorithms, particle swarm optimization, simulated annealing, ant colony optimization, harmony search, and firefly algorithms. We also briefly introduce the photosynthetic algorithm, the enzyme algorithm, and Tabu search. Worked examples with implementation have been used to show how each algorithm works. This book is thus an ideal textbook for an undergraduate and/or graduate course. As some of the algorithms such as the harmony search and firefly algorithms are at the forefront of current research, this book can also serve as a reference book for researchers.

Advanced Optimization by Nature Inspired Algorithms

Advanced Optimization by Nature Inspired Algorithms
Author: Omid Bozorg-Haddad
Publsiher: Springer
Total Pages: 159
Release: 2017-06-30
ISBN 10: 9811052212
ISBN 13: 9789811052217
Language: EN, FR, DE, ES & NL

Advanced Optimization by Nature Inspired Algorithms Book Review:

This book, compiles, presents, and explains the most important meta-heuristic and evolutionary optimization algorithms whose successful performance has been proven in different fields of engineering, and it includes application of these algorithms to important engineering optimization problems. In addition, this book guides readers to studies that have implemented these algorithms by providing a literature review on developments and applications of each algorithm. This book is intended for students, but can be used by researchers and professionals in the area of engineering optimization.

Nature Inspired Methods for Metaheuristics Optimization

Nature Inspired Methods for Metaheuristics Optimization
Author: Fouad Bennis,Rajib Kumar Bhattacharjya
Publsiher: Springer Nature
Total Pages: 502
Release: 2020-01-17
ISBN 10: 3030264580
ISBN 13: 9783030264581
Language: EN, FR, DE, ES & NL

Nature Inspired Methods for Metaheuristics Optimization Book Review:

This book gathers together a set of chapters covering recent development in optimization methods that are inspired by nature. The first group of chapters describes in detail different meta-heuristic algorithms, and shows their applicability using some test or real-world problems. The second part of the book is especially focused on advanced applications and case studies. They span different engineering fields, including mechanical, electrical and civil engineering, and earth/environmental science, and covers topics such as robotics, water management, process optimization, among others. The book covers both basic concepts and advanced issues, offering a timely introduction to nature-inspired optimization method for newcomers and students, and a source of inspiration as well as important practical insights to engineers and researchers.

Nature Inspired Optimization Algorithms

Nature Inspired Optimization Algorithms
Author: Aditya Khamparia,Ashish Khanna,Nhu Gia Nguyen,Bao Le Nguyen
Publsiher: Unknown
Total Pages: 250
Release: 2021-02-20
ISBN 10: 9783110676068
ISBN 13: 3110676060
Language: EN, FR, DE, ES & NL

Nature Inspired Optimization Algorithms Book Review:

This book will focus on the involvement of data mining and intelligent computing methods for recent advances in Biomedical applications and algorithms of nature-inspired computing for Biomedical systems. The proposed meta heuristic or nature-inspired techniques should be an enhanced, hybrid, adaptive or improved version of basic algorithms in terms of performance and convergence metrics. In this exciting and emerging interdisciplinary area a wide range of theory and methodologies are being investigated and developed to tackle complex and challenging problems. Today, analysis and processing of data is one of big focuses among researchers community and information society. Due to evolution and knowledge discovery of natural computing, related meta heuristic or bio-inspired algorithms have gained increasing popularity in the recent decade because of their significant potential to tackle computationally intractable optimization dilemma in medical, engineering, military, space and industry fields. The main reason behind the success rate of nature inspired algorithms is their capability to solve problems. The nature inspired optimization techniques provide adaptive computational tools for the complex optimization problems and diversified engineering applications. Tentative Table of Contents/Topic Coverage: - Neural Computation - Evolutionary Computing Methods - Neuroscience driven AI Inspired Algorithms - Biological System based algorithms - Hybrid and Intelligent Computing Algorithms - Application of Natural Computing - Review and State of art analysis of Optimization algorithms - Molecular and Quantum computing applications - Swarm Intelligence - Population based algorithm and other optimizations

Clever Algorithms

Clever Algorithms
Author: Jason Brownlee
Publsiher: Jason Brownlee
Total Pages: 438
Release: 2011-01
ISBN 10: 1446785068
ISBN 13: 9781446785065
Language: EN, FR, DE, ES & NL

Clever Algorithms Book Review:

This book provides a handbook of algorithmic recipes from the fields of Metaheuristics, Biologically Inspired Computation and Computational Intelligence that have been described in a complete, consistent, and centralized manner. These standardized descriptions were carefully designed to be accessible, usable, and understandable. Most of the algorithms described in this book were originally inspired by biological and natural systems, such as the adaptive capabilities of genetic evolution and the acquired immune system, and the foraging behaviors of birds, bees, ants and bacteria. An encyclopedic algorithm reference, this book is intended for research scientists, engineers, students, and interested amateurs. Each algorithm description provides a working code example in the Ruby Programming Language.

Harmony Search and Nature Inspired Optimization Algorithms

Harmony Search and Nature Inspired Optimization Algorithms
Author: Neha Yadav,Anupam Yadav,Jagdish Chand Bansal,Kusum Deep,Joong Hoon Kim
Publsiher: Springer
Total Pages: 1238
Release: 2018-10-20
ISBN 10: 9789811307607
ISBN 13: 9811307601
Language: EN, FR, DE, ES & NL

Harmony Search and Nature Inspired Optimization Algorithms Book Review:

The book covers different aspects of real-world applications of optimization algorithms. It provides insights from the Fourth International Conference on Harmony Search, Soft Computing and Applications held at BML Munjal University, Gurgaon, India on February 7–9, 2018. It consists of research articles on novel and newly proposed optimization algorithms; the theoretical study of nature-inspired optimization algorithms; numerically established results of nature-inspired optimization algorithms; and real-world applications of optimization algorithms and synthetic benchmarking of optimization algorithms.

Nature Inspired Optimization Algorithms for Fuzzy Controlled Servo Systems

Nature Inspired Optimization Algorithms for Fuzzy Controlled Servo Systems
Author: Radu-Emil Precup,Radu-Codrut David
Publsiher: Butterworth-Heinemann
Total Pages: 148
Release: 2019-04-19
ISBN 10: 0128166061
ISBN 13: 9780128166062
Language: EN, FR, DE, ES & NL

Nature Inspired Optimization Algorithms for Fuzzy Controlled Servo Systems Book Review:

Nature-inspired Optimization Algorithms for Fuzzy Controlled Servo Systems explains fuzzy control in servo systems in a way that doesn't require any solid mathematical prerequisite. Analysis and design methodologies are covered, along with specific applications to servo systems and representative case studies. The theoretical approaches presented throughout the book are validated by the illustration of digital simulation and real-time experimental results. This book is a great resource for a wide variety of readers, including graduate students, engineers (designers, practitioners and researchers), and everyone who faces challenging control problems. Merges classical and modern approaches to fuzzy control Presents, in a unified structure, the essential aspects regarding fuzzy control in servo systems Explains notions of fuzzy set theory and fuzzy control to readers with limited experience

Optimization Techniques and Applications with Examples

Optimization Techniques and Applications with Examples
Author: Xin-She Yang
Publsiher: John Wiley & Sons
Total Pages: 384
Release: 2018-08-30
ISBN 10: 111949060X
ISBN 13: 9781119490609
Language: EN, FR, DE, ES & NL

Optimization Techniques and Applications with Examples Book Review:

A guide to modern optimization applications and techniques in newly emerging areas spanning optimization, data science, machine intelligence, engineering, and computer sciences Optimization Techniques and Applications with Examples introduces the fundamentals of all the commonly used techniques in optimization that encompass the broadness and diversity of the methods (traditional and new) and algorithms. The author—a noted expert in the field—covers a wide range of topics including mathematical foundations, optimization formulation, optimality conditions, algorithmic complexity, linear programming, convex optimization, and integer programming. In addition, the book discusses artificial neural network, clustering and classifications, constraint-handling, queueing theory, support vector machine and multi-objective optimization, evolutionary computation, nature-inspired algorithms and many other topics. Designed as a practical resource, all topics are explained in detail with step-by-step examples to show how each method works. The book’s exercises test the acquired knowledge that can be potentially applied to real problem solving. By taking an informal approach to the subject, the author helps readers to rapidly acquire the basic knowledge in optimization, operational research, and applied data mining. This important resource: Offers an accessible and state-of-the-art introduction to the main optimization techniques Contains both traditional optimization techniques and the most current algorithms and swarm intelligence-based techniques Presents a balance of theory, algorithms, and implementation Includes more than 100 worked examples with step-by-step explanations Written for upper undergraduates and graduates in a standard course on optimization, operations research and data mining, Optimization Techniques and Applications with Examples is a highly accessible guide to understanding the fundamentals of all the commonly used techniques in optimization.

Discrete Problems in Nature Inspired Algorithms

Discrete Problems in Nature Inspired Algorithms
Author: Anupam Prof. Shukla,Ritu Tiwari
Publsiher: CRC Press
Total Pages: 310
Release: 2017-12-15
ISBN 10: 1351260871
ISBN 13: 9781351260879
Language: EN, FR, DE, ES & NL

Discrete Problems in Nature Inspired Algorithms Book Review:

This book includes introduction of several algorithms which are exclusively for graph based problems, namely combinatorial optimization problems, path formation problems, etc. Each chapter includes the introduction of the basic traditional nature inspired algorithm and discussion of the modified version for discrete algorithms including problems pertaining to discussed algorithms.

Nature Inspired Algorithms for Optimisation

Nature Inspired Algorithms for Optimisation
Author: Raymond Chiong
Publsiher: Springer
Total Pages: 516
Release: 2009-05-02
ISBN 10: 3642002676
ISBN 13: 9783642002670
Language: EN, FR, DE, ES & NL

Nature Inspired Algorithms for Optimisation Book Review:

Nature-Inspired Algorithms have been gaining much popularity in recent years due to the fact that many real-world optimisation problems have become increasingly large, complex and dynamic. The size and complexity of the problems nowadays require the development of methods and solutions whose efficiency is measured by their ability to find acceptable results within a reasonable amount of time, rather than an ability to guarantee the optimal solution. This volume 'Nature-Inspired Algorithms for Optimisation' is a collection of the latest state-of-the-art algorithms and important studies for tackling various kinds of optimisation problems. It comprises 18 chapters, including two introductory chapters which address the fundamental issues that have made optimisation problems difficult to solve and explain the rationale for seeking inspiration from nature. The contributions stand out through their novelty and clarity of the algorithmic descriptions and analyses, and lead the way to interesting and varied new applications.

Nature Inspired Computation and Swarm Intelligence

Nature Inspired Computation and Swarm Intelligence
Author: Xin-She Yang
Publsiher: Academic Press
Total Pages: 442
Release: 2020-04-24
ISBN 10: 0128197145
ISBN 13: 9780128197141
Language: EN, FR, DE, ES & NL

Nature Inspired Computation and Swarm Intelligence Book Review:

Nature-inspired computation and swarm intelligence have become popular and effective tools for solving problems in optimization, computational intelligence, soft computing and data science. Recently, the literature in the field has expanded rapidly, with new algorithms and applications emerging. Nature-Inspired Computation and Swarm Intelligence: Algorithms, Theory and Applications is a timely reference giving a comprehensive review of relevant state-of-the-art developments in algorithms, theory and applications of nature-inspired algorithms and swarm intelligence. It reviews and documents the new developments, focusing on nature-inspired algorithms and their theoretical analysis, as well as providing a guide to their implementation. The book includes case studies of diverse real-world applications, balancing explanation of the theory with practical implementation. Nature-Inspired Computation and Swarm Intelligence: Algorithms, Theory and Applications is suitable for researchers and graduate students in computer science, engineering, data science, and management science, who want a comprehensive review of algorithms, theory and implementation within the fields of nature inspired computation and swarm intelligence. Introduces nature-inspired algorithms and their fundamentals, including: particle swarm optimization, bat algorithm, cuckoo search, firefly algorithm, flower pollination algorithm, differential evolution and genetic algorithms as well as multi-objective optimization algorithms and others Provides a theoretical foundation and analyses of algorithms, including: statistical theory and Markov chain theory on the convergence and stability of algorithms, dynamical system theory, benchmarking of optimization, no-free-lunch theorems, and a generalized mathematical framework Includes a diversity of case studies of real-world applications: feature selection, clustering and classification, tuning of restricted Boltzmann machines, travelling salesman problem, classification of white blood cells, music generation by artificial intelligence, swarm robots, neural networks, engineering designs and others

Nature Inspired Optimization for Image Processing

Nature Inspired Optimization for Image Processing
Author: Vasuki A
Publsiher: CRC Press
Total Pages: 280
Release: 2020-07-09
ISBN 10: 9780367255985
ISBN 13: 0367255987
Language: EN, FR, DE, ES & NL

Nature Inspired Optimization for Image Processing Book Review:

Nature Inspired Optimization Algorithms is a comprehensive book on the most popular optimization algorithms that are based on nature. It starts with an overview of optimization and goes from the classical to the latest swarm intelligence algorithm. Nature has a rich abundance of flora and fauna that inspired the development of nature inspired optimization techniques. The study of the intelligent survival strategies of animals, birds and insects in a hostile and ever-changing environment has led to the development of techniques emulating their behaviour. Nature provides us with simple solutions to complex problems in an effective and adaptive manner. This book is a valuable resource for engineers, researchers, faculty and students who are devising optimum solutions to any type of problem. The problems range from computer science to economics covering diverse areas that require maximizing output and minimizing resources and this is the crux of all optimization algorithms. The book is a lucid description of fifteen of the existing important optimization algorithms that are based on swarm intelligence and superior in performance. Features: Detailed description of the algorithms along with pseudocode and flowchart Easily translatable to program code that is also readily available in Mathworks website for some of the algorithms Simple examples to demonstrate the optimization strategies have been given wherever possible that makes understanding easier Standard applications and benchmark datasets for testing and validating the algorithms have been enumerated This book is a reference for under-graduate and post-graduate students. It will be useful to faculty members teaching the subject on optimization. It also a comprehensive guide for researchers who are looking for optimizing resources in attaining the best solution to a problem. The nature inspired optimization algorithms are unconventional and this makes them more efficient than their traditional counterparts.

Computational Intelligence

Computational Intelligence
Author: Dinesh C.S. Bisht,Mangey Ram
Publsiher: Walter de Gruyter GmbH & Co KG
Total Pages: 280
Release: 2020-08-10
ISBN 10: 3110671352
ISBN 13: 9783110671353
Language: EN, FR, DE, ES & NL

Computational Intelligence Book Review:

Computational intelligence (CI) lies at the interface between engineering and computer science; control engineering, where problems are solved using computer-assisted methods. Thus, it can be regarded as an indispensable basis for all artificial intelligence (AI) activities. This book collects surveys of most recent theoretical approaches focusing on fuzzy systems, neurocomputing, and nature inspired algorithms. It also presents surveys of up-to-date research and application with special focus on fuzzy systems as well as on applications in life sciences and neuronal computing.

Mathematical Foundations of Nature Inspired Algorithms

Mathematical Foundations of Nature Inspired Algorithms
Author: Xin-She Yang,Xing-Shi He
Publsiher: Springer
Total Pages: 107
Release: 2019-05-08
ISBN 10: 3030169367
ISBN 13: 9783030169367
Language: EN, FR, DE, ES & NL

Mathematical Foundations of Nature Inspired Algorithms Book Review:

This book presents a systematic approach to analyze nature-inspired algorithms. Beginning with an introduction to optimization methods and algorithms, this book moves on to provide a unified framework of mathematical analysis for convergence and stability. Specific nature-inspired algorithms include: swarm intelligence, ant colony optimization, particle swarm optimization, bee-inspired algorithms, bat algorithm, firefly algorithm, and cuckoo search. Algorithms are analyzed from a wide spectrum of theories and frameworks to offer insight to the main characteristics of algorithms and understand how and why they work for solving optimization problems. In-depth mathematical analyses are carried out for different perspectives, including complexity theory, fixed point theory, dynamical systems, self-organization, Bayesian framework, Markov chain framework, filter theory, statistical learning, and statistical measures. Students and researchers in optimization, operations research, artificial intelligence, data mining, machine learning, computer science, and management sciences will see the pros and cons of a variety of algorithms through detailed examples and a comparison of algorithms.