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Pathways to International Publication in the Social Sciences: A Guide for Early Career and Non-Native English Researchers
by Insung JungThis guide offers a clear step-by-step approach for graduate students and early-career researchers, especially non-native English speakers, seeking to publish in international journals in the social sciences. It provides practical strategies for preparing, submitting, and refining research papers, helping researchers navigate the challenges of academic publishing. With 21 chapters, the guide covers every stage of writing, revising, and submission, while addressing the unique obstacles faced by non-native English speakers. The guide helps researchers identify reputable journals, avoid predatory ones, and use digital tools to meet international standards. It then provides a structured roadmap that simplifies the publication process, covering steps like journal selection, writing compelling abstracts, and drafting the methods and results sections. By the end of the guide, it is expected that researchers will have a strong first draft or, ideally, a submission-ready manuscript. The guide also addresses language barriers, cultural differences, and unfamiliarity with international conventions. It offers practical solutions for improving English writing, utilizing digital tools, responding to peer reviews, and managing revisions effectively. It emphasizes ethical guidelines like avoiding plagiarism, properly crediting co-authors, and ensuring research transparency to help researchers meet global standards. Unlike other research guides, this one is specifically tailored to early career and non-native English researchers working in social science disciplines. It offers practical strategies and real-world examples to equip researchers—and teachers of research methods and academic writing—with a framework for achieving publishing success in global academia.
Pathways to Math Literacy (Second Edition)
by Dave SobeckiWe're making the process of learning useful problem-solving skills through algebra more palatable for students, which at the end of the day is a significant part of the battle.
Pathwise Estimation and Inference for Diffusion Market Models
by Nikolai Dokuchaev Lin Yee HinPathwise estimation and inference for diffusion market models discusses contemporary techniques for inferring, from options and bond prices, the market participants' aggregate view on important financial parameters such as implied volatility, discount rate, future interest rate, and their uncertainty thereof. The focus is on the pathwise inference methods that are applicable to a sole path of the observed prices and do not require the observation of an ensemble of such paths. <P><P>This book is pitched at the level of senior undergraduate students undertaking research at honors year, and postgraduate candidates undertaking Master’s or PhD degree by research. From a research perspective, this book reaches out to academic researchers from backgrounds as diverse as mathematics and probability, econometrics and statistics, and computational mathematics and optimization whose interest lie in analysis and modelling of financial market data from a multi-disciplinary approach. Additionally, this book is also aimed at financial market practitioners participating in capital market facing businesses who seek to keep abreast with and draw inspiration from novel approaches in market data analysis. <P><P>The first two chapters of the book contains introductory material on stochastic analysis and the classical diffusion stock market models. The remaining chapters discuss more special stock and bond market models and special methods of pathwise inference for market parameter for different models. The final chapter describes applications of numerical methods of inference of bond market parameters to forecasting of short rate. <P><P>Nikolai Dokuchaev is an associate professor in Mathematics and Statistics at Curtin University. His research interests include mathematical and statistical finance, stochastic analysis, PDEs, control, and signal processing. <P><P>Lin Yee Hin is a practitioner in the capital market facing industry. His research interests include econometrics, non-parametric regression, and scientific computing.
Patient Care under Uncertainty
by Charles F. ManskiHow cutting-edge economics can improve decision-making methods for doctorsAlthough uncertainty is a common element of patient care, it has largely been overlooked in research on evidence-based medicine. Patient Care under Uncertainty strives to correct this glaring omission. Applying the tools of economics to medical decision making, Charles Manski shows how uncertainty influences every stage, from risk analysis to treatment, and how this can be reasonably confronted.In the language of econometrics, uncertainty refers to the inadequacy of available evidence and knowledge to yield accurate information on outcomes. In the context of health care, a common example is a choice between periodic surveillance or aggressive treatment of patients at risk for a potential disease, such as women prone to breast cancer. While these choices make use of data analysis, Manski demonstrates how statistical imprecision and identification problems often undermine clinical research and practice. Reviewing prevailing practices in contemporary medicine, he discusses the controversy regarding whether clinicians should adhere to evidence-based guidelines or exercise their own judgment. He also critiques the wishful extrapolation of research findings from randomized trials to clinical practice. Exploring ways to make more sensible judgments with available data, to credibly use evidence, and to better train clinicians, Manski helps practitioners and patients face uncertainties honestly. He concludes by examining patient care from a public health perspective and the management of uncertainty in drug approvals.Rigorously interrogating current practices in medicine, Patient Care under Uncertainty explains why predictability in the field has been limited and furnishes criteria for more cogent steps forward.
Patient-Reported Outcomes: Measurement, Implementation and Interpretation (Chapman & Hall/CRC Biostatistics Series)
by Joseph C. Cappelleri Demissie Alemayehu Kelly H. Zou Andrew G. Bushmakin Jose Ma. Alvir Tara SymondsHowever, exciting new developments are on the verge of changing the treatment of this debilitating disorder. Two anabolic agents, the parathyroid hormone (PTH) and the fluoride ion, show tremendous promise as tools for building and retaining bone - with no adverse side effects. Anabolic Treatments for Osteoporosis is a comprehensive account of the latest studies that have been carried out on these two agents, and a thorough assessment of their prospects as osteoporosis therapeutics. This unique book combines basic science and up-to-date clinical data to present a complete picture of this breakthrough in the treatment of a globally significant health issue.
Patrones (Math Counts, New and Updated)
by Henry PluckroseUna serie de libros para introducir a los lectores jovenes a conceptos matematicos fundamentales, ¡ahora en espanol!Los patrones estan a nuestro alrededor y encontramos muchos de ellos en la naturaleza: en las cabezas y petalos de las flores, en las hojas, en los pajaros, en las alas de las mariposas... ¡Hay patrones en casi todas partes! Con ejemplos del mundo real, fotografias convincentes y texto inspirador, ¡esta es la introduccion perfecta al concepto matematico de "patrones" para los lectores mas jovenes!Sobre la serie:Publicada originalmente en los anos 90 y actualizada recientemente, esta revolucionaria serie superventas inicia a los ninos en el camino de aprender a comunicarse y razonar matematicamente.La base de las matematicas son las ideas, y estos libros se han desarrollado para que los ninos vean, hablen, toquen y experimenten con estas ideas. Las fotografias atractivas y el texto sencillo y directo, hacen de esta serie una herramienta perfecta para leer individualmente o en voz alta. Diez conceptos matematicos fundamentales, uno para cada libro de la serie, estan desarrollados de forma excelente, y ofrecen un apoyo curricular ideal. Esta serie es la mejor manera de iniciar el camino hacia el dominio de las matematicas.
Patrones Crecientes (Growing Patterns): Los números de Fibonacci en la naturaleza
by Sarah C. CampbellAn ALSC Notable Children's BookA wondrous introduction to one of the most beautiful connections between mathematics and the natural world—the Fibonacci sequence—through a series of stunning nature photographs.Discover the biggest mathematical mystery in nature—Fibonacci numbers! Named after a famous mathematician, the number pattern is simple and starts with: 1, 1, 2, 3, 5, 8, 13. Each number in the sequence comes from adding the two numbers before it. What's the mystery? The pattern crops up in the most unexpected places. You'll find it in the disk of a sunflower, the skin of a pineapple, and the spiral of a nautilus shell. This book brings math to life, celebrates science, and inspires kids to see nature through new eyes.
Pattern Analysis and Machine Intelligence: First International Conference, ICPAMI 2024, Shanghai, China, August 30 – September 1, 2024, Proceedings (Communications in Computer and Information Science #2323)
by Jie Yang Yuanjie Zheng Chen GongThis book constitutes the referred proceedings of the First International Conference on Pattern Analysis and Machine Intelligence, ICPAMI 2024, held in Shanghai, China, from August 30 to September 01, 2024. The 28 papers presented here were carefully reviewed and selected from 56 submissions. These papers have been organized under the following topical sections: Computer Vision and Pattern Recognition; Natural Language Processing (NLP) and Machine Learning; Intelligent System and Optimization Algorithm.
Pattern Analysis of the Human Connectome
by Dewen Hu Ling-Li ZengThis book presents recent advances in pattern analysis of the human connectome. The human connectome, measured by magnetic resonance imaging at the macroscale, provides a comprehensive description of how brain regions are connected. Based on machine learning methods, multiviarate pattern analysis can directly decode psychological or cognitive states from brain connectivity patterns. Although there are a number of works with chapters on conventional human connectome encoding (brain-mapping), there are few resources on human connectome decoding (brain-reading). Focusing mainly on advances made over the past decade in the field of manifold learning, sparse coding, multi-task learning, and deep learning of the human connectome and applications, this book helps students and researchers gain an overall picture of pattern analysis of the human connectome. It also offers valuable insights for clinicians involved in the clinical diagnosis and treatment evaluation of neuropsychiatric disorders.
Pattern Classification
by Peter Hart Richard Duda David StorkThe first edition, published in 1973, has become a classic reference in the field. Now with the second edition, readers will find information on key new topics such as neural networks and statistical pattern recognition, the theory of machine learning, and the theory of invariances. Also included are worked examples, comparisons between different methods, extensive graphics, expanded exercises and computer project topics.
Pattern Discovery in Bioinformatics: Theory & Algorithms
by Laxmi ParidaThe computational methods of bioinformatics are being used more and more to process the large volume of current biological data. Promoting an understanding of the underlying biology that produces this data, Pattern Discovery in Bioinformatics: Theory and Algorithms provides the tools to study regularities in biological data.Taking a systema
Pattern Dynamics of Marine Plankton Behavior: Nonlinear Dynamics Applications
by Li Zhang Shu Tang LiuTo ultimately address this serious issue, this book begins with the nonlinear dynamic characteristics of marine plankton, focusing on the dynamic behavior of both two-dimensional and spatiotemporal patterns. As a critical foundation of marine ecosystems, the frequent outbreaks of marine phytoplankton and the toxicity of planktonic animals pose significant threats to marine ecological security and human health. One of the primary reasons we currently struggle to effectively manage the safety issues surrounding marine plankton is the extremely complex nature of their growth environment, which exhibits intricate dynamic and nonlinear characteristics. By constructing reaction-diffusion models and fractional diffusion systems of the planktonic ecosystem, the book characterizes the various factors in different environments and studies the nonlinear behavior of marine organisms. Employing linear stability theory, multi-scale analysis, comparison principle, analytical techniques, and the construction of Lyapunov functions, the book delves into the following topic: the stability of the plankton ecosystem, Hopf bifurcation, Turing bifurcation and other local bifurcations, spatial self-organization behavior of marine plankton, the formation of spatiotemporal patterns, and the persistence and extinction properties and characteristics. Marine ecology and the marine environment are currently hot research topics internationally, with the behavior of marine organisms being a core area of this research. The goal of exploring these issues is to scientifically understand the features of marine organisms, control their behavior, manage ocean pollution effectively, contribute to human development, and support social advancement. Additionally, the authors aime to make academic contributions and provide guidance to graduate students and researchers dedicated to this field.
Pattern Formation In The Physical And Biological Sciences (Santa Fe Institute Studies In The Sciences Of C... Ser.)
by H. Frederick NijhoutThis Lecture Notes Volume represents the first time any of the summer school lectures have been collected and published on a discrete subject rather than grouping all of a season's lectures together. This volume provides a broad survey of current thought on the problem of pattern formation. Spanning six years of summer school lectures, it includes articles which examine the origin and evolution of spatial patterns in physio-chemical and biological systems from a great diversity of theoretical and mechanistic perspectives. In addition, most of these pieces have been updated by their authors and three articles never previously published have been added.
Pattern Formation in Morphogenesis
by Vincenzo Capasso Annick Harel-Bellan Misha Gromov Linda Louise Pritchard Nadya MorozovaPattern Formation in Morphogenesis is a rich source of interesting and challenging mathematical problems. The volume aims at showing how a combination of new discoveries in developmental biology and associated modelling and computational techniques has stimulated or may stimulate relevant advances in the field. Finally it aims at facilitating the process of unfolding a mutual recognition between Biologists and Mathematicians of their complementary skills, to the point where the resulting synergy generates new and novel discoveries. It offers an interdisciplinary interaction space between biologists from embryology, genetics and molecular biology who present their own work in the perspective of the advancement of their specific fields, and mathematicians who propose solutions based on the knowledge grasped from biologists.
Pattern Mining with Evolutionary Algorithms
by Sebastián Ventura José María LunaThis book provides a comprehensive overview of the field of pattern mining with evolutionary algorithms. To do so, it covers formal definitions about patterns, patterns mining, type of patterns and the usefulness of patterns in the knowledge discovery process. As it is described within the book, the discovery process suffers from both high runtime and memory requirements, especially when high dimensional datasets are analyzed. To solve this issue, many pruning strategies have been developed. Nevertheless, with the growing interest in the storage of information, more and more datasets comprise such a dimensionality that the discovery of interesting patterns becomes a challenging process. In this regard, the use of evolutionary algorithms for mining pattern enables the computation capacity to be reduced, providing sufficiently good solutions. This book offers a survey on evolutionary computation with particular emphasis on genetic algorithms and genetic programming. Also included is an analysis of the set of quality measures most widely used in the field of pattern mining with evolutionary algorithms. This book serves as a review of the most important evolutionary algorithms for pattern mining. It considers the analysis of different algorithms for mining different type of patterns and relationships between patterns, such as frequent patterns, infrequent patterns, patterns defined in a continuous domain, or even positive and negative patterns. A completely new problem in the pattern mining field, mining of exceptional relationships between patterns, is discussed. In this problem the goal is to identify patterns which distribution is exceptionally different from the distribution in the complete set of data records. Finally, the book deals with the subgroup discovery task, a method to identify a subgroup of interesting patterns that is related to a dependent variable or target attribute. This subgroup of patterns satisfies two essential conditions: interpretability and interestingness.
Pattern Recognition Algorithms for Data Mining (Chapman & Hall/CRC Computer Science & Data Analysis)
by Sankar K. Pal Pabitra MitraThis valuable text addresses different pattern recognition (PR) tasks in a unified framework with both theoretical and experimental results. Tasks covered include data condensation, feature selection, case generation, clustering/classification, and rule generation and evaluation. Organized into eight chapters, the book begins by introducing PR, data mining, and knowledge discovery concepts. The authors proceed to analyze the tasks of multi-scale data condensation and dimensionality reduction. Then they explore the problem of learning with support vector machine (SVM), and conclude by highlighting the significance of granular computing for different mining tasks in a soft paradigm.
Pattern Recognition Applications and Methods: 8th International Conference, ICPRAM 2019, Prague, Czech Republic, February 19-21, 2019, Revised Selected Papers (Lecture Notes in Computer Science #11996)
by Ana Fred Maria De Marsico Gabriella Sanniti di BajaThis book contains revised and extended versions of selected papers from the 8th International Conference on Pattern Recognition, ICPRAM 2019, held in Prague, Czech Republic, in February 2019. The 25 full papers presented together 52 short papers and 32 poster sessions were carefully reviewed and selected from 138 initial submissions. Contributions describing applications of Pattern Recognition techniques to real-world problems, interdisciplinary research, experimental and/or theoretical studies yielding new insights that advance Pattern Recognition methods are especially encouraged.
Pattern Recognition Techniques Applied to Biomedical Problems (STEAM-H: Science, Technology, Engineering, Agriculture, Mathematics & Health)
by Martha Refugio Ortiz-PosadasThis book covers pattern recognition techniques applied to various areas of biomedicine, including disease diagnosis and prognosis, and several problems of classification, with a special focus on—but not limited to—pattern recognition modeling of biomedical signals and images. Multidisciplinary by definition, the book’s topic blends computing, mathematics and other technical sciences towards the development of computational tools and methodologies that can be applied to pattern recognition processes. In this work, the efficacy of such methods and techniques for processing medical information is analyzed and compared, and auxiliary criteria for determining the correct diagnosis and treatment strategies are recommended and applied. Researchers in applied mathematics, the computer sciences, engineering and related fields with a focus on medical applications will benefit from this book, as well as professionals with a special interest in state-of-the-art pattern recognition techniques as applied to biomedicine.
Pattern Recognition and Computational Intelligence Techniques Using Matlab (Transactions on Computational Science and Computational Intelligence)
by E. S. GopiThis book presents the complex topic of using computational intelligence for pattern recognition in a straightforward and applicable way, using Matlab to illustrate topics and concepts. The author covers computational intelligence tools like particle swarm optimization, bacterial foraging, simulated annealing, genetic algorithm, and artificial neural networks. The Matlab based illustrations along with the code are given for every topic. Readers get a quick basic understanding of various pattern recognition techniques using only the required depth in math. The Matlab program and algorithm are given along with the running text, providing clarity and usefulness of the various techniques.Presents pattern recognition and the computational intelligence using Matlab;Includes mixtures of theory, math, and algorithms, letting readers understand the concepts quickly;Outlines an array of classifiers, various regression models, statistical tests and the techniques for pattern recognition using computational intelligence.
Pattern Recognition and Computer Vision: 7th Chinese Conference, PRCV 2024, Urumqi, China, October 18–20, 2024, Proceedings, Part I (Lecture Notes in Computer Science #15031)
by Ran He Jie Zhou Cheng-Lin Liu Ming-Ming Cheng Kurban Ubul Hongbin Zha Zhouchen Lin Wushouer SilamuThis 15-volume set LNCS 15031-15045 constitutes the refereed proceedings of the 7th Chinese Conference on Pattern Recognition and Computer Vision, PRCV 2024, held in Urumqi, China, during October 18–20, 2024. The 579 full papers presented were carefully reviewed and selected from 1526 submissions. The papers cover various topics in the broad areas of pattern recognition and computer vision, including machine learning, pattern classification and cluster analysis, neural network and deep learning, low-level vision and image processing, object detection and recognition, 3D vision and reconstruction, action recognition, video analysis and understanding, document analysis and recognition, biometrics, medical image analysis, and various applications.
Pattern Recognition and Computer Vision: 7th Chinese Conference, PRCV 2024, Urumqi, China, October 18–20, 2024, Proceedings, Part II (Lecture Notes in Computer Science #15032)
by Ran He Jie Zhou Cheng-Lin Liu Ming-Ming Cheng Kurban Ubul Hongbin Zha Zhouchen Lin Wushouer SilamuThis 15-volume set LNCS 15031-15045 constitutes the refereed proceedings of the 7th Chinese Conference on Pattern Recognition and Computer Vision, PRCV 2024, held in Urumqi, China, during October 18–20, 2024. The 579 full papers presented were carefully reviewed and selected from 1526 submissions. The papers cover various topics in the broad areas of pattern recognition and computer vision, including machine learning, pattern classification and cluster analysis, neural network and deep learning, low-level vision and image processing, object detection and recognition, 3D vision and reconstruction, action recognition, video analysis and understanding, document analysis and recognition, biometrics, medical image analysis, and various applications.
Pattern Recognition and Computer Vision: 7th Chinese Conference, PRCV 2024, Urumqi, China, October 18–20, 2024, Proceedings, Part III (Lecture Notes in Computer Science #15033)
by Ran He Jie Zhou Cheng-Lin Liu Ming-Ming Cheng Kurban Ubul Hongbin Zha Zhouchen Lin Wushouer SilamuThis 15-volume set LNCS 15031-15045 constitutes the refereed proceedings of the 7th Chinese Conference on Pattern Recognition and Computer Vision, PRCV 2024, held in Urumqi, China, during October 18–20, 2024. The 579 full papers presented were carefully reviewed and selected from 1526 submissions. The papers cover various topics in the broad areas of pattern recognition and computer vision, including machine learning, pattern classification and cluster analysis, neural network and deep learning, low-level vision and image processing, object detection and recognition, 3D vision and reconstruction, action recognition, video analysis and understanding, document analysis and recognition, biometrics, medical image analysis, and various applications.
Pattern Recognition and Computer Vision: 7th Chinese Conference, PRCV 2024, Urumqi, China, October 18–20, 2024, Proceedings, Part IV (Lecture Notes in Computer Science #15034)
by Ran He Jie Zhou Cheng-Lin Liu Ming-Ming Cheng Kurban Ubul Hongbin Zha Zhouchen Lin Wushouer SilamuThis 15-volume set LNCS 15031-15045 constitutes the refereed proceedings of the 7th Chinese Conference on Pattern Recognition and Computer Vision, PRCV 2024, held in Urumqi, China, during October 18–20, 2024. The 579 full papers presented were carefully reviewed and selected from 1526 submissions. The papers cover various topics in the broad areas of pattern recognition and computer vision, including machine learning, pattern classification and cluster analysis, neural network and deep learning, low-level vision and image processing, object detection and recognition, 3D vision and reconstruction, action recognition, video analysis and understanding, document analysis and recognition, biometrics, medical image analysis, and various applications.
Pattern Recognition and Computer Vision: 7th Chinese Conference, PRCV 2024, Urumqi, China, October 18–20, 2024, Proceedings, Part IX (Lecture Notes in Computer Science #15039)
by Ran He Jie Zhou Cheng-Lin Liu Ming-Ming Cheng Kurban Ubul Hongbin Zha Zhouchen Lin Wushouer SilamuThis 15-volume set LNCS 15031-15045 constitutes the refereed proceedings of the 7th Chinese Conference on Pattern Recognition and Computer Vision, PRCV 2024, held in Urumqi, China, during October 18–20, 2024. The 579 full papers presented were carefully reviewed and selected from 1526 submissions. The papers cover various topics in the broad areas of pattern recognition and computer vision, including machine learning, pattern classification and cluster analysis, neural network and deep learning, low-level vision and image processing, object detection and recognition, 3D vision and reconstruction, action recognition, video analysis and understanding, document analysis and recognition, biometrics, medical image analysis, and various applications.
Pattern Recognition and Computer Vision: 7th Chinese Conference, PRCV 2024, Urumqi, China, October 18–20, 2024, Proceedings, Part V (Lecture Notes in Computer Science #15035)
by Ran He Jie Zhou Cheng-Lin Liu Ming-Ming Cheng Kurban Ubul Hongbin Zha Zhouchen Lin Wushouer SilamuThis 15-volume set LNCS 15031-15045 constitutes the refereed proceedings of the 7th Chinese Conference on Pattern Recognition and Computer Vision, PRCV 2024, held in Urumqi, China, during October 18–20, 2024. The 579 full papers presented were carefully reviewed and selected from 1526 submissions. The papers cover various topics in the broad areas of pattern recognition and computer vision, including machine learning, pattern classification and cluster analysis, neural network and deep learning, low-level vision and image processing, object detection and recognition, 3D vision and reconstruction, action recognition, video analysis and understanding, document analysis and recognition, biometrics, medical image analysis, and various applications.