Big Data in Cognitive Science

The primary goal of this volume is to present cutting-edge examples of mining large-scale and naturalistic data to discover important principles of cognition and evaluate theories that would not be possible without such a scale.

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Author: Michael N. Jones

Publisher: Psychology Press

ISBN: 9781315413563

Category: Computers

Page: 382

View: 112

While laboratory research is the backbone of collecting experimental data in cognitive science, a rapidly increasing amount of research is now capitalizing on large-scale and real-world digital data. Each piece of data is a trace of human behavior and offers us a potential clue to understanding basic cognitive principles. However, we have to be able to put the pieces together in a reasonable way, which necessitates both advances in our theoretical models and development of new methodological techniques. The primary goal of this volume is to present cutting-edge examples of mining large-scale and naturalistic data to discover important principles of cognition and evaluate theories that would not be possible without such a scale. This book also has a mission to stimulate cognitive scientists to consider new ways to harness big data in order to enhance our understanding of fundamental cognitive processes. Finally, this book aims to warn of the potential pitfalls of using, or being over-reliant on, big data and to show how big data can work alongside traditional, rigorously gathered experimental data rather than simply supersede it. In sum, this groundbreaking volume presents cognitive scientists and those in related fields with an exciting, detailed, stimulating, and realistic introduction to big data – and to show how it may greatly advance our understanding of the principles of human memory, perception, categorization, decision-making, language, problem-solving, and representation.

Exam Prep for Big Data in Cognitive Science

This book provides over 2,000 Exam Prep questions and answers to accompany the text Big Data in Cognitive Science Items include highly probable exam items: Ford, Stock market, online, yield, Data Definition Language, utility, Savepoint, ...

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The Oxford Handbook of Cognitive Science

The Oxford Handbook of Cognitive Science emphasizes the research and theory most central to modern cognitive science: computational theories of complex human cognition.

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Author: Susan E. F. Chipman

Publisher: Oxford University Press

ISBN: 9780199842193

Category: Language Arts & Disciplines

Page: 375

View: 919

Cognitive Science is an avowedly multidisciplinary field, drawing upon many traditional disciplines or research areas--including Linguistics, Neuroscience, Philosophy, Psychology, Anthropology, Artificial Intelligence, and Education--that contribute to our understanding of cognition. Just as learning and memory cannot truly prove effective as disconnected studies, practical applications of cognitive research, such as the improvement of education and human-computer interaction, require dealing with more complex cognitive phenomena by integrating the methods and insights from multiple traditional disciplines. The societal need for such applications has played an important role in the development of cognitive science. The Oxford Handbook of Cognitive Science emphasizes the research and theory that is most central to modern cognitive science. Sections of the volume address computational theories of human cognitive architecture; cognitive functioning, such as problem solving and decision making as they have been studied with both experimental methods and formal modeling approaches; and cognitive linguistics and the advent of big data. Chapters provide concise introductions to the present achievements of cognitive science, supplemented by references to suggested reading, and additional facets of cognitive science are discussed in the handbook's introductory chapter, complementing other key publications to access for further study. With contributions from among the best representatives in their fields, this volume will appeal as the critical resource for the students in training who determine the future of cognitive science.

Big Data Analytics for Cloud IoT and Cognitive Computing

The definitive guide to successfully integrating social, mobile, Big-Data analytics, cloud and IoT principles and technologies The main goal of this book is to spur the development of effective big-data computing operations on smart clouds ...

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Author: Kai Hwang

Publisher: John Wiley & Sons

ISBN: 9781119247029

Category: Computers

Page: 432

View: 479

The definitive guide to successfully integrating social, mobile, Big-Data analytics, cloud and IoT principles and technologies The main goal of this book is to spur the development of effective big-data computing operations on smart clouds that are fully supported by IoT sensing, machine learning and analytics systems. To that end, the authors draw upon their original research and proven track record in the field to describe a practical approach integrating big-data theories, cloud design principles, Internet of Things (IoT) sensing, machine learning, data analytics and Hadoop and Spark programming. Part 1 focuses on data science, the roles of clouds and IoT devices and frameworks for big-data computing. Big data analytics and cognitive machine learning, as well as cloud architecture, IoT and cognitive systems are explored, and mobile cloud-IoT-interaction frameworks are illustrated with concrete system design examples. Part 2 is devoted to the principles of and algorithms for machine learning, data analytics and deep learning in big data applications. Part 3 concentrates on cloud programming software libraries from MapReduce to Hadoop, Spark and TensorFlow and describes business, educational, healthcare and social media applications for those tools. The first book describing a practical approach to integrating social, mobile, analytics, cloud and IoT (SMACT) principles and technologies Covers theory and computing techniques and technologies, making it suitable for use in both computer science and electrical engineering programs Offers an extremely well-informed vision of future intelligent and cognitive computing environments integrating SMACT technologies Fully illustrated throughout with examples, figures and approximately 150 problems to support and reinforce learning Features a companion website with an instructor manual and PowerPoint slides www.wiley.com/go/hwangIOT Big-Data Analytics for Cloud, IoT and Cognitive Computing satisfies the demand among university faculty and students for cutting-edge information on emerging intelligent and cognitive computing systems and technologies. Professionals working in data science, cloud computing and IoT applications will also find this book to be an extremely useful working resource.

Big Data Analytics and Computing for Digital Forensic Investigations

This book investigates the areas of digital forensics, digital investigation and data analysis procedures as they apply to computer fraud and cybercrime, with the main objective of describing a variety of digital crimes and retrieving ...

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Author: Suneeta Satpathy

Publisher: CRC Press

ISBN: 9781000045055

Category: Computers

Page: 214

View: 376

Digital forensics has recently gained a notable development and become the most demanding area in today’s information security requirement. This book investigates the areas of digital forensics, digital investigation and data analysis procedures as they apply to computer fraud and cybercrime, with the main objective of describing a variety of digital crimes and retrieving potential digital evidence. Big Data Analytics and Computing for Digital Forensic Investigations gives a contemporary view on the problems of information security. It presents the idea that protective mechanisms and software must be integrated along with forensic capabilities into existing forensic software using big data computing tools and techniques. Features Describes trends of digital forensics served for big data and the challenges of evidence acquisition Enables digital forensic investigators and law enforcement agencies to enhance their digital investigation capabilities with the application of data science analytics, algorithms and fusion technique This book is focused on helping professionals as well as researchers to get ready with next-generation security systems to mount the rising challenges of computer fraud and cybercrimes as well as with digital forensic investigations. Dr Suneeta Satpathy has more than ten years of teaching experience in different subjects of the Computer Science and Engineering discipline. She is currently working as an associate professor in the Department of Computer Science and Engineering, College of Bhubaneswar, affiliated with Biju Patnaik University and Technology, Odisha. Her research interests include computer forensics, cybersecurity, data fusion, data mining, big data analysis and decision mining. Dr Sachi Nandan Mohanty is an associate professor in the Department of Computer Science and Engineering at ICFAI Tech, ICFAI Foundation for Higher Education, Hyderabad, India. His research interests include data mining, big data analysis, cognitive science, fuzzy decision-making, brain–computer interface, cognition and computational intelligence.

Cloud Computing for Machine Learning and Cognitive Applications

The book will also be very useful as a reference for professionals who want to work in cloud computing and data science.

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Author: Kai Hwang

Publisher: MIT Press

ISBN: 9780262036412

Category: Computers

Page: 624

View: 840

The first textbook to teach students how to build data analytic solutions on large data sets using cloud-based technologies.

First International Conference on Artificial Intelligence and Cognitive Computing

This book presents original research works by researchers, engineers and practitioners in the field of artificial intelligence and cognitive computing.

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Author: Raju Surampudi Bapi

Publisher: Springer

ISBN: 9789811315800

Category: Technology & Engineering

Page: 716

View: 536

This book presents original research works by researchers, engineers and practitioners in the field of artificial intelligence and cognitive computing. The book is divided into two parts, the first of which focuses on artificial intelligence (AI), knowledge representation, planning, learning, scheduling, perception-reactive AI systems, evolutionary computing and other topics related to intelligent systems and computational intelligence. In turn, the second part focuses on cognitive computing, cognitive science and cognitive informatics. It also discusses applications of cognitive computing in medical informatics, structural health monitoring, computational intelligence, intelligent control systems, bio-informatics, smart manufacturing, smart grids, image/video processing, video analytics, medical image and signal processing, and knowledge engineering, as well as related applications.

Cognitive Computing for Big Data Systems Over IoT

This book brings a high level of fluidity to analytics and addresses recent trends, innovative ideas, challenges and cognitive computing solutions in big data and the Internet of Things (IoT).

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Author: Arun Kumar Sangaiah

Publisher: Springer

ISBN: 9783319706887

Category: Computers

Page: 375

View: 816

This book brings a high level of fluidity to analytics and addresses recent trends, innovative ideas, challenges and cognitive computing solutions in big data and the Internet of Things (IoT). It explores domain knowledge, data science reasoning and cognitive methods in the context of the IoT, extending current data science approaches by incorporating insights from experts as well as a notion of artificial intelligence, and performing inferences on the knowledge The book provides a comprehensive overview of the constituent paradigms underlying cognitive computing methods, which illustrate the increased focus on big data in IoT problems as they evolve. It includes novel, in-depth fundamental research contributions from a methodological/application in data science accomplishing sustainable solution for the future perspective. Mainly focusing on the design of the best cognitive embedded data science technologies to process and analyze the large amount of data collected through the IoT, and aid better decision making, the book discusses adapting decision-making approaches under cognitive computing paradigms to demonstrate how the proposed procedures as well as big data and IoT problems can be handled in practice. This book is a valuable resource for scientists, professionals, researchers, and academicians dealing with the new challenges and advances in the specific areas of cognitive computing and data science approaches.

Cognitive Science and Artificial Intelligence

This book presents interdisciplinary research on cognition, mind and behavior from an information processing perspective.

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Author: Sasikumar Gurumoorthy

Publisher: Springer

ISBN: 9789811066986

Category: Computers

Page: 112

View: 974

This book presents interdisciplinary research on cognition, mind and behavior from an information processing perspective. It includes chapters on Artificial Intelligence, Decision Support Systems, Machine Learning, Data Mining and Support Vector Machines, chiefly with regard to the data obtained and analyzed in Medical Informatics, Bioinformatics and related disciplines. The book reflects the state-of-the-art in Artificial Intelligence and Cognitive Science, and covers theory, algorithms, numerical simulation, error and uncertainty analysis, as well novel applications of new processing techniques in Biomedical Informatics, Computer Science and its applied areas. As such, it offers a valuable resource for students and researchers from the fields of Computer Science and Engineering in Medicine and Biology.

Machine Learning and Cognitive Computing for Mobile Communications and Wireless Networks

Because it is an amalgamation of theory, mathematics, and examples of the discussed technologies, this book will also be relevant to all levels of students—from undergraduate and postgraduate to research students—studying computer ...

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Author: Krishna Kant Singh

Publisher: John Wiley & Sons

ISBN: 9781119640363

Category: Computers

Page: 268

View: 297

Communication and network technology has witnessed recent rapid development and numerous information services and applications have been developed globally. These technologies have high impact on society and the way people are leading their lives. The advancement in technology has undoubtedly improved the quality of service and user experience yet a lot needs to be still done. Some areas that still need improvement include seamless wide-area coverage, high-capacity hot-spots, low-power massive-connections, low-latency and high-reliability and so on. Thus, it is highly desirable to develop smart technologies for communication to improve the overall services and management of wireless communication. Machine learning and cognitive computing have converged to give some groundbreaking solutions for smart machines. With these two technologies coming together, the machines can acquire the ability to reason similar to the human brain. The research area of machine learning and cognitive computing cover many fields like psychology, biology, signal processing, physics, information theory, mathematics, and statistics that can be used effectively for topology management. Therefore, the utilization of machine learning techniques like data analytics and cognitive power will lead to better performance of communication and wireless systems.

Cognitive Analytics Concepts Methodologies Tools and Applications

Highlighting a range of topics such as natural language processing, big data, and pattern recognition, this multi-volume book is ideally designed for information technology professionals, software developers, data analysts, graduate-level ...

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Author: Management Association, Information Resources

Publisher: IGI Global

ISBN: 9781799824619

Category: Science

Page: 1961

View: 602

Due to the growing use of web applications and communication devices, the use of data has increased throughout various industries, including business and healthcare. It is necessary to develop specific software programs that can analyze and interpret large amounts of data quickly in order to ensure adequate usage and predictive results. Cognitive Analytics: Concepts, Methodologies, Tools, and Applications provides emerging perspectives on the theoretical and practical aspects of data analysis tools and techniques. It also examines the incorporation of pattern management as well as decision-making and prediction processes through the use of data management and analysis. Highlighting a range of topics such as natural language processing, big data, and pattern recognition, this multi-volume book is ideally designed for information technology professionals, software developers, data analysts, graduate-level students, researchers, computer engineers, software engineers, IT specialists, and academicians.

The Cognitive Approach in Cloud Computing and Internet of Things Technologies for Surveillance Tracking Systems

This book presents all of these concepts, with a goal of creating automated IT systems that are capable of resolving problems without demanding human aid.

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Author: Dinesh Peter

Publisher: Academic Press

ISBN: 9780128166093

Category: Science

Page: 202

View: 752

The Cognitive Approach in Cloud Computing and Internet of Things Technologies for Surveillance Tracking Systems discusses the recent, rapid development of Internet of things (IoT) and its focus on research in smart cities, especially on surveillance tracking systems in which computing devices are widely distributed and huge amounts of dynamic real-time data are collected and processed. Efficient surveillance tracking systems in the Big Data era require the capability of quickly abstracting useful information from the increasing amounts of data. Real-time information fusion is imperative and part of the challenge to mission critical surveillance tasks for various applications. This book presents all of these concepts, with a goal of creating automated IT systems that are capable of resolving problems without demanding human aid. Examines the current state of surveillance tracking systems, cognitive cloud architecture for resolving critical issues in surveillance tracking systems, and research opportunities in cognitive computing for surveillance tracking systems Discusses topics including cognitive computing architectures and approaches, cognitive computing and neural networks, complex analytics and machine learning, design of a symbiotic agent for recognizing real space in ubiquitous environments, and more Covers supervised regression and classification methods, clustering and dimensionality reduction methods, model development for machine learning applications, intelligent machines and deep learning networks includes coverage of cognitive computing models for scalable environments, privacy and security aspects of surveillance tracking systems, strategies and experiences in cloud architecture and service platform design

Big Data in Psychiatry and Neurology

This book will help researchers, students and clinicians implement new methods for collecting big datasets from various patient populations.

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Author: Ahmed A. Moustafa

Publisher: Academic Press

ISBN: 9780128230022

Category: Medical

Page: 400

View: 976

Big Data in Psychiatry and Neurology provides an up-to-date overview of achievements in the field of big data in Psychiatry and Medicine, including applications of big data methods to aging disorders (e.g., Alzheimer’s disease and Parkinson’s disease), mood disorders (e.g., major depressive disorder), and drug addiction. This book will help researchers, students and clinicians implement new methods for collecting big datasets from various patient populations. Further, it will demonstrate how to use several algorithms and machine learning methods to analyze big datasets, thus providing individualized treatment for psychiatric and neurological patients. As big data analytics is gaining traction in psychiatric research, it is an essential component in providing predictive models for both clinical practice and public health systems. As compared with traditional statistical methods that provide primarily average group-level results, big data analytics allows predictions and stratification of clinical outcomes at an individual subject level. Discusses longitudinal big data and risk factors surrounding the development of psychiatric disorders Analyzes methods in using big data to treat psychiatric and neurological disorders Describes the role machine learning can play in the analysis of big data Demonstrates the various methods of gathering big data in medicine Reviews how to apply big data to genetics

Bim Enabled Cognitive Computing for Smart Built Environment

"This book explicitly brings together the BIM-enabled cognitive computing for smart built environment, and focuses on the potential, requirements and implementation of cognitive Internet of Things (CIoT) paradigm to buildings, Augmented ...

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Author: Ibrahim Yitmen

Publisher:

ISBN: 0367861836

Category: Building information modeling

Page: 256

View: 927

"This book explicitly brings together the BIM-enabled cognitive computing for smart built environment, and focuses on the potential, requirements and implementation of cognitive Internet of Things (CIoT) paradigm to buildings, Augmented Reality/Mixed Reality into cognitive building concepts, cognitive smart cities in its complexity, heterogeneity, and scope, and challenges of utilizing the big data generated by smart cities from a machine learning perspective. This book offers contributions to the processing, analysis, management, modeling, and simulation of big data and the associated applicability to BIM-enabled cognitive systems that will advance different aspects of future cognitive cities"--

Philosophy and Theory of Artificial Intelligence 2017

This book reports on the results of the third edition of the premier conference in the field of philosophy of artificial intelligence, PT-AI 2017, held on November 4 - 5, 2017 at the University of Leeds, UK. It covers: advanced knowledge on ...

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Author: Vincent C. Müller

Publisher: Springer

ISBN: 9783319964485

Category: Computers

Page: 316

View: 387

This book reports on the results of the third edition of the premier conference in the field of philosophy of artificial intelligence, PT-AI 2017, held on November 4 - 5, 2017 at the University of Leeds, UK. It covers: advanced knowledge on key AI concepts, including complexity, computation, creativity, embodiment, representation and superintelligence; cutting-edge ethical issues, such as the AI impact on human dignity and society, responsibilities and rights of machines, as well as AI threats to humanity and AI safety; and cutting-edge developments in techniques to achieve AI, including machine learning, neural networks, dynamical systems. The book also discusses important applications of AI, including big data analytics, expert systems, cognitive architectures, and robotics. It offers a timely, yet very comprehensive snapshot of what is going on in the field of AI, especially at the interfaces between philosophy, cognitive science, ethics and computing.

EAI International Conference on Big Data Innovation for Sustainable Cognitive Computing

The papers feature detail on cognitive computing and its self-learning systems that use data mining, pattern recognition and natural language processing (NLP) to mirror the way the human brain works.

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Author: Anandakumar Haldorai

Publisher: Springer Nature

ISBN: 9783030195625

Category: Technology & Engineering

Page: 412

View: 549

This proceeding features papers discussing big data innovation for sustainable cognitive computing. The papers feature detail on cognitive computing and its self-learning systems that use data mining, pattern recognition and natural language processing (NLP) to mirror the way the human brain works. This international conference focuses on cognitive computing technologies, from knowledge representation techniques and natural language processing algorithms to dynamic learning approaches. Topics covered include Data Science for Cognitive Analysis, Real-Time Ubiquitous Data Science, Platform for Privacy Preserving Data Science, and Internet-Based Cognitive Platform. The EAI International Conference on Big Data Innovation for Sustainable Cognitive Computing (BDCC 2018), took place on 13 – 15 December 2018 in Coimbatore, India.

Automata s Inner Movie Science and Philosophy of Mind

This book brings together researchers from a variety of fields to jointly present and discuss some of the most relevant problems around the conscious mind.

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Author: Steven S. Gouveia

Publisher: Vernon Press

ISBN: 9781622737482

Category: Psychology

Page: 387

View: 139

This book brings together researchers from a variety of fields to jointly present and discuss some of the most relevant problems around the conscious mind. This academic plurality perfectly characterizes the complexity with which a current researcher is confronted to discuss and work on this topic. The volume is organized as follows: Part I introduces the general problems of Philosophy of Mind and some historical perspectives. Part II focuses on understanding the input that the empirical sciences can offer to the theoretical problems. Part III discusses some of the core concepts of the field, namely, perception, memory and experience. Part IV debates human and artificial intelligence and, finally, Part V deliberates about the computation and the ethics of big data and artificial intelligence. The book contains valuable material for researchers in several fields such as Cognitive Science and Neuroscience, Psychology and Artificial Intelligence, and Philosophy. It can also be used as a guide to some courses at various levels, from BAs to MAs and PhD courses of several fields. It is our belief, as it is claimed in the preface by Georg Northoff, that there is an urgent need for a truly transdisciplinary exchange between philosophy and the sciences in order to stimulate some real progress. We hope that this book will become a sound step for such an interdisciplinary enterprise.

Cognitive Big Data Intelligence with a Meta Heuristic Approach

Various real-time case studies and implemented works are discussed in this book for better understanding and additional clarity. This book presents an essential platform for the use of cognitive technology in the field of Data Science.

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Author: Gyoo-Soo Chae

Publisher: Academic Press

ISBN: 0323851177

Category: Computers

Page: 370

View: 609

Cognitive Big Data Intelligence with Meta-Heuristic Approach presents an exact and compact organization of contents related to the latest meta-heuristics methodologies based on new challenging big data application domains and cognitive computing with proper explanation wherever required. The combined model of cognitive big data intelligence with meta-heuristics methods can be used to analyze emerging patterns, spot business opportunities, and take care of critical process-centric issues in real-time. It can be further used to enhance customer interactions with the help of robotic process automation. It presents other technical aspects and alternatives to traditional tools, algorithms, and methodologies. Various real-time case studies and implemented works will be discussed in this book for better understanding and more clarity to readers. This book presents an essential platform for the use of cognitive technology in the field of Data Science. It covers meta-heuristic methodologies that can be successful in a wide variety of problem settings in big data frameworks. Provides a unique opportunity to present the work on the state-of-the-art of meta heuristics approach in the area of big data processing developing automated and intelligent models Explains different feasible applications and case studies where cognitive computing can be successfully implemented in big data analytics using meta heuristics algorithms Provides a snapshot of the latest advances in the contribution of meta heuristics frameworks in cognitive big data applications to solve optimization problems

Data Science and Its Applications

The book on Data Science and its applications discusses about data science overview, scientific methods, data processing, extraction of meaningful information from data, and insight for developing the concept from different domains, ...

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Author: Taylor & Francis Group

Publisher: CRC Press

ISBN: 0367608863

Category:

Page: 408

View: 991

The term "data" being mostly used, experimented, analyzed, and researched, "Data Science and its Applications" finds relevance in all domains of research studies including science, engineering, technology, management, mathematics, and many more in wide range of applications such as sentiment analysis, social medial analytics, signal processing, gene analysis, market analysis, healthcare, bioinformatics etc. The book on Data Science and its applications discusses about data science overview, scientific methods, data processing, extraction of meaningful information from data, and insight for developing the concept from different domains, highlighting mathematical and statistical models, operations research, computer programming, machine learning, data visualization, pattern recognition and others. The book also highlights data science implementation and evaluation of performance in several emerging applications such as information retrieval, cognitive science, healthcare, and computer vision. The data analysis covers the role of data science depicting different types of data such as text, image, biomedical signal etc. useful for a wide range of real time applications. The salient features of the book are: Overview, Challenges and Opportunities in Data Science and Real Time Applications Addressing Big Data Issues Useful Machine Learning Methods Disease Detection and Healthcare Applications utilizing Data Science Concepts and Deep Learning Applications in Stock Market, Education, Behavior Analysis, Image Captioning, Gene Analysis and Scene Text Analysis Data Optimization Due to multidisciplinary applications of data science concepts, the book is intended for wide range of readers that include Data Scientists, Big Data Analysists, Research Scholars engaged in Data Science and Machine Learning applications.