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Unsolved Problems in Mathematical Systems and Control Theory
by Vincent D. Blondel & Alexandre MegretskiThis book provides clear presentations of more than sixty important unsolved problems in mathematical systems and control theory. Each of the problems included here is proposed by a leading expert and set forth in an accessible manner. Covering a wide range of areas, the book will be an ideal reference for anyone interested in the latest developments in the field, including specialists in applied mathematics, engineering, and computer science. The book consists of ten parts representing various problem areas, and each chapter sets forth a different problem presented by a researcher in the particular area and in the same way: description of the problem, motivation and history, available results, and bibliography. It aims not only to encourage work on the included problems but also to suggest new ones and generate fresh research. The reader will be able to submit solutions for possible inclusion on an online version of the book to be updated quarterly on the Princeton University Press website, and thus also be able to access solutions, updated information, and partial solutions as they are developed.
Unstable Systems (Mathematical Physics Studies)
by Lawrence Horwitz Yosef StraussThis book focuses on unstable systems both from the classical and the quantum mechanical points of view and studies the relations between them. The first part deals with quantum systems. Here the main generally used methods today, such as the Gamow approach, and the Wigner-Weisskopf method, are critically discussed. The quantum mechanical Lax-Phillips theory developed by the authors, based on the dilation theory of Nagy and Foias and its more general extension to approximate semigroup evolution is explained.The second part provides a description of approaches to classical stability analysis and introduces geometrical methods recently developed by the authors, which are shown to be highly effective in diagnosing instability and, in many cases, chaotic behavior. It is then shown that, in the framework of the theory of symplectic manifolds, there is a systematic algorithm for the construction of a canonical transformation of any standard potential model Hamiltonian to geometric form, making accessible powerful geometric methods for stability analysis in a wide range of applications.
Unsteady Supersonic Combustion
by Mingbo Sun Hongbo Wang Zun Cai Jiajian ZhuThis book describes the unsteady phenomena needed to understand supersonic combustion. Following an initial chapter that introduces readers to the basic concepts in and classical studies on unsteady supersonic combustion, the book highlights recent studies on unsteady phenomena, which offer insights on e.g. interactions between acoustic waves and flames, flow dominating instability, ignition instability, flame flashback, and near-blowout-limit combustion. In turn, the book discusses in detail the fundamental mechanisms of these phenomena, and puts forward practical suggestions for future scramjet design.
Unsupervised Domain Adaptation: Recent Advances and Future Perspectives (Machine Learning: Foundations, Methodologies, and Applications)
by Jingjing Li Lei Zhu Zhekai DuUnsupervised domain adaptation (UDA) is a challenging problem in machine learning where the model is trained on a source domain with labeled data and tested on a target domain with unlabeled data. In recent years, UDA has received significant attention from the research community due to its applicability in various real-world scenarios. This book provides a comprehensive review of state-of-the-art UDA methods and explores new variants of UDA that have the potential to advance the field. The book begins with a clear introduction to the UDA problem and is mainly organized into four technical sections, each focused on a specific piece of UDA research. The first section covers criterion optimization-based UDA, which aims to learn domain-invariant representations by minimizing the discrepancy between source and target domains. The second section discusses bi-classifier adversarial learning-based UDA, which creatively leverages adversarial learning by conducting a minimax game between the feature extractor and two task classifiers. The third section introduces source-free UDA, a novel UDA setting that does not require any raw data from the source domain. The fourth section presents active learning for UDA, which combines domain adaptation and active learning to reduce the amount of labeled data needed for adaptation. This book is suitable for researchers, graduate students, and practitioners who are interested in UDA and its applications in various fields, primarily in computer vision. The chapters are authored by leading experts in the field and provide a comprehensive and in-depth analysis of the current UDA methods and new directions for future research. With its broad coverage and cutting-edge research, this book is a valuable resource for anyone looking to advance their knowledge of UDA.
Unsupervised Feature Extraction Applied to Bioinformatics: A PCA Based and TD Based Approach (Unsupervised and Semi-Supervised Learning)
by Y-h. TaguchiThis updated book proposes applications of tensor decomposition to unsupervised feature extraction and feature selection. The author posits that although supervised methods including deep learning have become popular, unsupervised methods have their own advantages. He argues that this is the case because unsupervised methods are easy to learn since tensor decomposition is a conventional linear methodology. This book starts from very basic linear algebra and reaches the cutting edge methodologies applied to difficult situations when there are many features (variables) while only small number of samples are available. The author includes advanced descriptions about tensor decomposition including Tucker decomposition using high order singular value decomposition as well as higher order orthogonal iteration, and train tensor decomposition. The author concludes by showing unsupervised methods and their application to a wide range of topics.
Unsupervised Learning Algorithms
by M. Emre Celebi Kemal AydinThis book summarizes the state-of-the-art in unsupervised learning. The contributors discuss how with the proliferation of massive amounts of unlabeled data, unsupervised learning algorithms, which can automatically discover interesting and useful patterns in such data, have gained popularity among researchers and practitioners. The authors outline how these algorithms have found numerous applications including pattern recognition, market basket analysis, web mining, social network analysis, information retrieval, recommender systems, market research, intrusion detection, and fraud detection. They present how the difficulty of developing theoretically sound approaches that are amenable to objective evaluation have resulted in the proposal of numerous unsupervised learning algorithms over the past half-century. The intended audience includes researchers and practitioners who are increasingly using unsupervised learning algorithms to analyze their data. Topics of interest include anomaly detection, clustering, feature extraction, and applications of unsupervised learning. Each chapter is contributed by a leading expert in the field.
Unsupervised Learning Approaches for Dimensionality Reduction and Data Visualization
by B.K. Tripathy Anveshrithaa Sundareswaran Shrusti GhelaUnsupervised Learning Approaches for Dimensionality Reduction and Data Visualization describes such algorithms as Locally Linear Embedding (LLE), Laplacian Eigenmaps, Isomap, Semidefinite Embedding, and t-SNE to resolve the problem of dimensionality reduction in the case of non-linear relationships within the data. Underlying mathematical concepts, derivations, and proofs with logical explanations for these algorithms are discussed, including strengths and limitations. The book highlights important use cases of these algorithms and provides examples along with visualizations. Comparative study of the algorithms is presented to give a clear idea on selecting the best suitable algorithm for a given dataset for efficient dimensionality reduction and data visualization. FEATURES Demonstrates how unsupervised learning approaches can be used for dimensionality reduction Neatly explains algorithms with a focus on the fundamentals and underlying mathematical concepts Describes the comparative study of the algorithms and discusses when and where each algorithm is best suitable for use Provides use cases, illustrative examples, and visualizations of each algorithm Helps visualize and create compact representations of high dimensional and intricate data for various real-world applications and data analysis This book is aimed at professionals, graduate students, and researchers in Computer Science and Engineering, Data Science, Machine Learning, Computer Vision, Data Mining, Deep Learning, Sensor Data Filtering, Feature Extraction for Control Systems, and Medical Instruments Input Extraction.
Unsupervised Learning in Space and Time: A Modern Approach for Computer Vision using Graph-based Techniques and Deep Neural Networks (Advances in Computer Vision and Pattern Recognition)
by Marius LeordeanuThis book addresses one of the most important unsolved problems in artificial intelligence: the task of learning, in an unsupervised manner, from massive quantities of spatiotemporal visual data that are available at low cost. The book covers important scientific discoveries and findings, with a focus on the latest advances in the field. Presenting a coherent structure, the book logically connects novel mathematical formulations and efficient computational solutions for a range of unsupervised learning tasks, including visual feature matching, learning and classification, object discovery, and semantic segmentation in video. The final part of the book proposes a general strategy for visual learning over several generations of student-teacher neural networks, along with a unique view on the future of unsupervised learning in real-world contexts. Offering a fresh approach to this difficult problem, several efficient, state-of-the-art unsupervised learning algorithms are reviewed in detail, complete with an analysis of their performance on various tasks, datasets, and experimental setups. By highlighting the interconnections between these methods, many seemingly diverse problems are elegantly brought together in a unified way. Serving as an invaluable guide to the computational tools and algorithms required to tackle the exciting challenges in the field, this book is a must-read for graduate students seeking a greater understanding of unsupervised learning, as well as researchers in computer vision, machine learning, robotics, and related disciplines.
Unsupervised Learning with R
by Erik Rodriguez PachecoWork with over 40 packages to draw inferences from complex datasets and find hidden patterns in raw unstructured data About This Book * Unlock and discover how to tackle clusters of raw data through practical examples in R * Explore your data and create your own models from scratch * Analyze the main aspects of unsupervised learning with this comprehensive, practical step-by-step guide Who This Book Is For This book is intended for professionals who are interested in data analysis using unsupervised learning techniques, as well as data analysts, statisticians, and data scientists seeking to learn to use R to apply data mining techniques. Knowledge of R, machine learning, and mathematics would help, but are not a strict requirement. What You Will Learn * Load, manipulate, and explore your data in R using techniques for exploratory data analysis such as summarization, manipulation, correlation, and data visualization * Transform your data by using approaches such as scaling, re-centering, scale [0-1], median/MAD, natural log, and imputation data * Build and interpret clustering models using K-Means algorithms in R * Build and interpret clustering models by Hierarchical Clustering Algorithm's in R * Understand and apply dimensionality reduction techniques * Create and use learning association rules models, such as recommendation algorithms * Use and learn about the techniques of feature selection * Install and use end-user tools as an alternative to programming directly in the R console In Detail The R Project for Statistical Computing provides an excellent platform to tackle data processing, data manipulation, modeling, and presentation. The capabilities of this language, its freedom of use, and a very active community of users makes R one of the best tools to learn and implement unsupervised learning. If you are new to R or want to learn about unsupervised learning, this book is for you. Packed with critical information, this book will guide you through a conceptual explanation and practical examples programmed directly into the R console. Starting from the beginning, this book introduces you to unsupervised learning and provides a high-level introduction to the topic. We quickly move on to discuss the application of key concepts and techniques for exploratory data analysis. The book then teaches you to identify groups with the help of clustering methods or building association rules. Finally, it provides alternatives for the treatment of high-dimensional datasets, as well as using dimensionality reduction techniques and feature selection techniques. By the end of this book, you will be able to implement unsupervised learning and various approaches associated with it in real-world projects. Style and approach This book takes a step-by-step approach to unsupervised learning concepts and tools, explained in a conversational and easy-to-follow style. Each topic is explained sequentially, explaining the theory and then putting it into practice by using specialized R packages for each topic.
Untangling Complex Systems: A Grand Challenge for Science
by Pier GentiliComplex Systems are natural systems that science is unable to describe exhaustively. Examples of Complex Systems are both unicellular and multicellular living beings; human brains; human immune systems; ecosystems; human societies; the global economy; the climate and geology of our planet. This book is an account of a marvelous interdisciplinary journey the author made to understand properties of the Complex Systems. He has undertaken his trip, equipped with the fundamental principles of physical chemistry, in particular, the Second Law of Thermodynamics that describes the spontaneous evolution of our universe, and the tools of Non-linear dynamics. By dealing with many disciplines, in particular, chemistry, biology, physics, economy, and philosophy, the author demonstrates that Complex Systems are intertwined networks, working in out-of-equilibrium conditions, which exhibit emergent properties, such as self-organization phenomena and chaotic behaviors in time and space.
Unterrichtsmethoden für MINT-Fächer
by Andreas ZendlerMathematik, Informatik, Naturwissenschaften (Biologie, Chemie, Physik) und Technik - seit Jahren findet in der breiten Öffentlichkeit eine angeregte Diskussion über diese sogenannten MINT-Fächer statt. Denn das in den MINT-Fächern vermittelte Wissen ist die unverzichtbare Grundlage für die Ausbildung der in Deutschland dringend benötigten Fachkräfte. Darum fordern Politik und Wirtschaft eine stärkere Gewichtung der Fächer, aber auch eine Verbesserung der Unterrichtsqualität. Dieses Buch stellt 20 verschiedene, wissenschaftlich fundierte Methoden für den MINT-Unterricht vor und erläutert die Rolle der digitalen Medien als fächerübergreifendes Element. Die interdisziplinäre Betrachtungsweise bietet Lehrern einen umfassenden Überblick über die verschiedenen Möglichkeiten und Ansätze für den eigenen Unterricht. Für jede der vorgestellten Methoden geben die Autoren wissenschaftliche fundierte Einschätzungen zu ihrer Lerneffektivität und erleichtern so Lehrkräften die Auswahl der geeignetsten Methoden für den eigenen Unterricht. Detaillierte Unterrichtsmodelle helfen bei der Umsetzung in der Praxis. Damit erhalten Lehrer und Lehramtsstudenten einen umfassenden Einblick in die effektivsten Unterrichtsmodelle für ein prozess- und ergebnisorientiertes Lernen in den MINT-Fächern. Dieses Buch lässt sich ideal fächerübergreifend einsetzen und dient dazu, die Lerneffektivität speziell im MINT-Unterricht bei Schülerinnen und Schülern zu verbessern.
Unterrichtsqualität im sprachbildenden Mathematikunterricht: Eine quantitative Studie zum Prozente-Unterricht (Dortmunder Beiträge zur Entwicklung und Erforschung des Mathematikunterrichts #48)
by Philipp NeugebauerZiel dieser Arbeit ist die Entwicklung und Anwendung eines Instruments zur Erfassung der Unterrichtsqualität von sprachbildendem Unterricht. Dazu wird das Erfassungsinstrument L-TRU durch Adaption des TRU-Frameworks entwickelt, nachdem der Stand der Instrumente zur Erfassung von Unterrichtsqualität im Hinblick auf Sprachbildung im Mathematikunterricht aufgearbeitet wurde. Die Unterrichtsqualitätsdimensionen lassen sich (trotz naheliegender inhaltlicher Abhängigkeiten) als inhaltlich relevante und empirisch nicht komplett zusammenfallende Größen identifizieren. Besonders die neu ergänzten Dimensionen des L-TRU ermöglichen die Erfassung weiterer Phänomene, die bisher nicht berücksichtigt wurden. Einige dieser Unterrichtsqualitätsdimensionen erweisen sich sogar bei gleichem Unterrichtsmaterial als signifikante Einflussfaktoren auf den Lernzuwachs der Lernenden. Insgesamt trägt dieses Buch dazu bei, die qualitative Beforschung des sprachbildenden Unterrichts unter Rückgriff auf Methoden der Unterrichtsqualitätsforschung auch quantitativ anzureichern. Damit wird erreicht, Hypothesen zu Gelingensbedingungen für sprachbildenden Mathematikunterricht nicht mehr nur in Fallstudien qualitativ zu generieren, sondern in mehr Klassen auch quantitativ überprüfen zu können.
Unterstützungsmaßnahmen in mathematikbezogenen Studiengängen: Konzepte, Praxisbeispiele und Untersuchungsergebnisse (Konzepte und Studien zur Hochschuldidaktik und Lehrerbildung Mathematik)
by Reinhard Hochmuth Rolf Biehler Michael Liebendörfer Niclas SchaperDie Gestaltung und Wirkung mathematikbezogener Unterstützungsmaßnahmen für Studierende vor Beginn des Studiums und während des ersten Studienjahrs beschäftigt nicht nur die an den Hochschulen lehrenden Mathematiker*innen, sondern auch Fachdidaktiker*innen, Hochschuldidaktiker*innen, Hochschulleitungen sowie die Bildungspolitik. Die Beiträge dieses Bandes resultieren aus einer langjährigen engen Kooperation zwischen Lehrenden aus 17 Universitäten und dem WiGeMath-Team. Den Mittelpunkt bilden konkrete Darstellungen einschlägiger Good-Practice-Beispiele, deren Ziele und Gestaltung jeweils um Evaluationsergebnisse ergänzt werden. Darüber hinaus finden sich praxisorientierte Überblickskapitel zu zentralen im WiGeMath-Projekt entwickelten Instrumenten: ein Rahmenmodell, das u. a. der systematischen Einordnung und Reflektion konkreter Maßnahmen dient, und ein Inventar bewährter quantitativer Erhebungsinstrumente. Ergänzend werden die am häufigsten umgesetzten Maßnahmentypen Vorkurse, Brückenvorlesungen und Lernzentren in informativen Kapiteln hinsichtlich ihrer jeweiligen Charakteristika und Wirkungen vorgestellt. Damit trägt der vorliegende Band dazu bei, folgende Fragen zu beantworten:Welche Gestaltungsmöglichkeiten von Vorkursen, Brückenvorlesungen und Lernzentren gibt es, und welche haben sich bewährt?Was weiß man über Wirkungszusammenhänge?Wie lassen sich mathematikbezogene Unterstützungsmaßnahmen evaluieren, und welche Instrumente zur Evaluation mathematikbezogener Unterstützungsmaßnahmen stehen aktuell zur Verfügung?Welche zentralen Fragen sind derzeit offen und bedürfen weiterer Forschung?Auf ein ausführliches Skalenhandbuch der Erhebungsinstrumente des Projekts WiGeMath kann über https://www.khdm.de/publikationen zugegriffen werden. Es dokumentiert insbesondere psychometrische Eigenschaften der Instrumente und stellt auf Basis der WiGeMath-Erhebungen Vergleichsdaten zur Verfügung und bietet damit eine Möglichkeit selbst erhobene Datensätze einzuordnen.
The Untold Story of Everything Digital: Bright Boys, Revisited (AK Peters/CRC Recreational Mathematics Series)
by Tom GreenThe Untold Story of Everything Digital: Bright Boys, Revisited celebrates the 70th anniversary (1949-2019) of the world "going digital" for the very first time—real-time digital computing’s genesis story. That genesis story is taken from the 2010 edition of Bright Boys: The Making of Information Technology, 1938-1958, and substantially expanded upon for this special, anniversary edition. Please join us for the incredible adventure that is The Untold Story of Everything Digital, when a band of misfit engineers, led by MIT's Jay Forrester and Bob Everett, birthed the digital revolution. The bright boys were the first to imagine an electronic landscape of computing machines and digital networks, and the first to blaze its high-tech trails.
Up and Running with DAX for Power BI: A Concise Guide for Non-Technical Users
by Alison BoxTake a concise approach to learning how DAX, the function language of Power BI and PowerPivot, works. This book focuses on explaining the core concepts of DAX so that ordinary folks can gain the skills required to tackle complex data analysis problems. But make no mistake, this is in no way an introductory book on DAX. A number of the topics you will learn, such as the concepts of context transition and table expansion, are considered advanced and challenging areas of DAX.While there are numerous resources on DAX, most are written with developers in mind, making learning DAX appear an overwhelming challenge, especially for those who are coming from an Excel background or with limited coding experience. The reality is, to hit the ground running with DAX, it’s not necessary to wade through copious pages on rarified DAX functions and the technical aspects of the language. There are just a few mandatory concepts that must be fully understood before DAX can be mastered. Knowledge of everything else in DAX is built on top of these mandatory aspects. Author Alison Box has been teaching and working with DAX for over eight years, starting with DAX for PowerPivot, the Excel add-in, before moving into the Power BI platform. The guide you hold in your hands is an outcome of these years of experience explaining difficult concepts in a way that people can understand. Over the years she has refined her approach, distilling down the truth of DAX which is “you can take people through as many functions as you like, but it’s to no avail if they don’t truly understand how it all works.” You will learn to use DAX to gain powerful insights into your data by generating complex and challenging business intelligence calculations including, but not limited to:Calculations to control the filtering of information to gain better insight into the data that matters to youCalculations across dates such as comparing data for the same period last year or the previous periodFinding rolling averages and rolling totalsComparing data against targets and KPIs or against average and maximum valuesUsing basket analysis, such as “of customers who bought product X who also bought product Y”Using “what if” analysis and scenariosFinding “like for like” salesDynamically showing TopN/BottomN percent of customers or products by salesFinding new and returning customers or sales regions in each month or each year Who This Book Is ForExcel users and non-technical users of varying levels of ability or anyone who wants to learn DAX for Power BI but lacks the confidence to do so
Up, Down, and Around the City (The World Around You)
by Christianne JonesZoom! The elevator zips from the bottom floor to the top floor of a tall building. Beep! Beep! The subway stops for people to get on and off. Using bright photographs and interactive, rhyming text, this picture book will help young readers discover position words while exploring the city.
Up for Debate!: Exploring Math Through Argument
by Chris LuzniakIn Up for Debate!: Exploring Math Through Argument, high school math teacher and debate coach Chris Luzniak shares stories, examples, and step-by-step routines that will help you build a classroom culture where students do the talking, explain their thinking, and critique each other's reasoning, all in the context of the math content you're expected to teach. Inside, you'll find: Inspirational stories of students debating math in real classroomsConcrete structures and routines that will get your students talking, listening, and debatingSpecific techniques you can use to transform existing math problems into debatable ones You'll begin with short speaking and listening routines that take just a few minutes to introduce. When you and your students are ready, you can layer on additional debate routines, until your class is engaged in full-class debates using mathematical reasoning. With this easy-to-read guide, you don't need to wait any longer. You will be able to start debating in your classroom, tomorrow.
Upper and Lower Bounds for Stochastic Processes
by Michel TalagrandThe book develops modern methods and in particular the "generic chaining" to bound stochastic processes. This methods allows in particular to get optimal bounds for Gaussian and Bernoulli processes. Applications are given to stable processes, infinitely divisible processes, matching theorems, the convergence of random Fourier series, of orthogonal series, and to functional analysis. The complete solution of a number of classical problems is given in complete detail, and an ambitious program for future research is laid out.
Upper Bound Limit Load Solutions for Welded Joints with Cracks
by Sergey AlexandrovThe present short monograph concerns analytic and semi-analytic techniques for finding an approximate value of the limit load. The limit load is an essential input parameter of flaw assessment procedures. In most cases, finding the limit load involves some numerical calculations of different levels of complexity, including numerical minimization of functions of one or several arguments, the slip-line technique and the finite element method. This book shows in particular how to use singular behavior of the real velocity field in the vicinity of bi-material interfaces in kinematically admissible velocity fields to increase the accuracy of upper bound solutions. An approach to recalculate the limit load for a class of structures with defects with the use of its value for the corresponding structure with no defect is discussed. The upper bound technique is applied to evaluate the limit load of overmatched and undermatched welded joints with cracks subject to various loading conditions of practical importance in conjunction with the aforementioned special techniques.
Upper Bounds for Grothendieck Constants, Quantum Correlation Matrices and CCP Functions (Lecture Notes in Mathematics #2349)
by Frank OertelThis book concentrates on the famous Grothendieck inequality and the continued search for the still unknown best possible value of the real and complex Grothendieck constant (an open problem since 1953). It describes in detail the state of the art in research on this fundamental inequality, including Krivine's recent contributions, and sheds light on related questions in mathematics, physics and computer science, particularly with respect to the foundations of quantum theory and quantum information theory. Unifying the real and complex cases as much as possible, the monograph introduces the reader to a rich collection of results in functional analysis and probability. In particular, it includes a detailed, self-contained analysis of the multivariate distribution of complex Gaussian random vectors. The notion of Completely Correlation Preserving (CCP) functions plays a particularly important role in the exposition.The prerequisites are a basic knowledge of standard functional analysis, complex analysis, probability, optimisation and some number theory and combinatorics. However, readers missing some background will be able to consult the generous bibliography, which contains numerous references to useful textbooks. The book will be of interest to PhD students and researchers in functional analysis, complex analysis, probability, optimisation, number theory and combinatorics, in physics (particularly in relation to the foundations of quantum mechanics) and in computer science (quantum information and complexity theory).
Upside: Profiting from the Profound Demographic Shifts Ahead
by John Zogby Kenneth W. Gronbach M. J. MoyeDemographics not only define who we are, where we live, and how our numbers change, but—for those who can read beyond the raw figures—they open up hidden business opportunities that lie ahead.What will happen when retiring Boomers free up jobs? How will Generation Y alter housing and transportation? Which states will have the most dynamic workforces? Will American manufacturing rebound as Asia’s population boom stalls?Upside puts this powerful yet little-understood science to work finding answers. Demographer Kenneth Gronbach synthesizes reams of data to show how generations impact markets and economies, and how to target promising trends. Lively and full of surprises, the book explains:What each age cohort is likely to buy now and in coming decades How profits dovetail with consumer numbers What sectors are likely to grow or lag How to make sense of the numbers to chart your own path And moreAs waves of people are born and age, fortunes and futures are determined. Whether you’re an investor, marketer executive, or entrepreneur, Upside helps you spot the potential for profits in ever-shifting demographics.
The Urban Commons: How Data and Technology Can Rebuild Our Communities
by Daniel T. O'BrienThrough voicemail, apps, websites, and Twitter, Boston’s sophisticated 311 system allows citizens to report potholes, broken streetlights, graffiti, and vandalism that affect everyone’s quality of life. Drawing on Boston’s rich data, Daniel T. O’Brien offers a model of what smart technology can do for cities seeking both growth and sustainability.
Urban Daily Labour Markets in Gujarat, Western India
by Kanchan Bharati LANCY LOBO Dhananjay KumarThis volume explores one of the most complex labour landscapes of India - the urban daily labour market. These markets form an important sector of the urban informal labour market and contribute significantly to the Indian economy. This book presents an empirical, comparative picture of daily labour markets, in Gujarat, Western India. These markets consist mostly of intra-state and interstate migrant workers who suffer from layered multiple marginalities based on markers of informality, migrant status, caste, ethnicity, gender and poor agency and often live in the peripheries of the cities without any rights and entitlements to their spaces and services. This study, based on an extensive survey of three cities in Gujarat, contains descriptions and analyses of the places of migration and their causes as well as the working and living conditions of the workers along with their spending patterns on food, health, education and leisure. It mirrors the work, life and issues of these workers on the regional level while contributing to a better understanding for future policy interventions. An in-depth study, the book will be of interest to students and researchers of labour economics, labour studies, urban planning, social work, sociology, anthropology, and demography. It will also be useful to NGOs/trade unions working with migrant workers, civil servants in Labour department and other related departments, city planners and policy makers.
Urban Decline: The British Experience (Routledge Revivals)
by David ClarkIn the twentieth century, urban growth was one of the most powerful catalysts of geographical, social and demographic change in the Western world. When this book was first published in 1989, however, a massive process of counter-urbanization was underway, which saw the loss of population and jobs in cities and a pronounced urban to rural shift. This book analyses the causes and consequences of urban decline in Britain and the developed world during this period and beyond, and assesses the implications for urban planning and policy. David Clark’s relevant and comprehensive title will be of value to students with a particular interest in urban geography and development.
Urban Geography: An Introductory Guide (Routledge Revivals)
by David ClarkThis book, first published in 1982, addressed the need for a fresh and comprehensive guide to the rapidly expanding area of urban geography. Drawing on examples from cities in a number of countries, including the U.S.A., David Clark outlines the contribution of geographers to the understanding of the city and urban society, and analyses the growth of the urban environment alongside planning and policy. A thorough and unique study, this title will be of particular value to undergraduate students, as well as laying the foundations for a more advanced study in urban geography and planning.