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| boston university data science acceptance rate: Foundations of Data Science Avrim Blum, John Hopcroft, Ravindran Kannan, 2020-01-23 This book provides an introduction to the mathematical and algorithmic foundations of data science, including machine learning, high-dimensional geometry, and analysis of large networks. Topics include the counterintuitive nature of data in high dimensions, important linear algebraic techniques such as singular value decomposition, the theory of random walks and Markov chains, the fundamentals of and important algorithms for machine learning, algorithms and analysis for clustering, probabilistic models for large networks, representation learning including topic modelling and non-negative matrix factorization, wavelets and compressed sensing. Important probabilistic techniques are developed including the law of large numbers, tail inequalities, analysis of random projections, generalization guarantees in machine learning, and moment methods for analysis of phase transitions in large random graphs. Additionally, important structural and complexity measures are discussed such as matrix norms and VC-dimension. This book is suitable for both undergraduate and graduate courses in the design and analysis of algorithms for data. |
| boston university data science acceptance rate: Proceedings of the Second Seattle Symposium in Biostatistics Danyu Lin, Patrick J. Heagerty, 2012-12-06 This volume contains a selection of papers presented at the Second Seattle Symposium in Biostatistics: Analysis of Correlated Data. The symposium was held in 2000 to celebrate the 30th anniversary of the University of Washington School of Public Health and Community Medicine. It featured keynote lectures by Norman Breslow, David Cox and Ross Prentice and 16 invited presentations by other prominent researchers. The papers contained in this volume encompass recent methodological advances in several important areas, such as longitudinal data, multivariate failure time data and genetic data, as well as innovative applications of the existing theory and methods. This volume is a valuable reference for researchers and practitioners in the field of correlated data analysis. |
| boston university data science acceptance rate: Roundtable on Data Science Postsecondary Education National Academies of Sciences, Engineering, and Medicine, Division of Behavioral and Social Sciences and Education, Division on Engineering and Physical Sciences, Board on Science Education, Computer Science and Telecommunications Board, Committee on Applied and Theoretical Statistics, Board on Mathematical Sciences and Analytics, 2020-10-02 Established in December 2016, the National Academies of Sciences, Engineering, and Medicine's Roundtable on Data Science Postsecondary Education was charged with identifying the challenges of and highlighting best practices in postsecondary data science education. Convening quarterly for 3 years, representatives from academia, industry, and government gathered with other experts from across the nation to discuss various topics under this charge. The meetings centered on four central themes: foundations of data science; data science across the postsecondary curriculum; data science across society; and ethics and data science. This publication highlights the presentations and discussions of each meeting. |
| boston university data science acceptance rate: Data Science and Human-Environment Systems Steven M. Manson, 2023-01-31 Transformation of the Earth's social and ecological systems is occurring at a rate and magnitude unparalleled in human experience. Data science is a revolutionary new way to understand human-environment relationships at the heart of pressing challenges like climate change and sustainable development. However, data science faces serious shortcomings when it comes to human-environment research. There are challenges with social and environmental data, the methods that manipulate and analyze the information, and the theory underlying the data science itself; as well as significant legal, ethical and policy concerns. This timely book offers a comprehensive, balanced, and accessible account of the promise and problems of this work in terms of data, methods, theory, and policy. It demonstrates the need for data scientists to work with human-environment scholars to tackle pressing real-world problems, making it ideal for researchers and graduate students in Earth and environmental science, data science and the environmental social sciences. |
| boston university data science acceptance rate: Algorithms and Law Martin Ebers, Susana Navas, 2020-07-23 Exploring issues from big-data to robotics, this volume is the first to comprehensively examine the regulatory implications of AI technology. |
| boston university data science acceptance rate: Elgar Encyclopedia of Law and Data Science Comandé, Giovanni, 2022-02-18 This Encyclopedia brings together jurists, computer scientists, and data analysts to map the emerging field of data science and law for the first time, uncovering the challenges, opportunities, and fault lines that arise as these groups are increasingly thrown together by expanding attempts to regulate and adapt to a data-driven world. It explains the concepts and tools at the crossroads of the many disciplines involved in data science and law, bridging scientific and applied domains. Entries span algorithmic fairness, consent, data protection, ethics, healthcare, machine learning, patents, surveillance, transparency and vulnerability. |
| boston university data science acceptance rate: Data Science Analytics and Applications Shriram R, Mak Sharma, 2018-02-23 This book constitutes the refereed proceedings of the First International Conference on Data Science Analytics and Applications, DaSAA 2017, held in Chennai, India, in January 2017. The 16 revised full papers and 4 revised short papers presented were carefully reviewed and selected from 77 submissions. The papers address issues such as data analytics, data mining, cloud computing, machine learning, text classification and analysis, information retrieval, DSS, security, image and video processing. |
| boston university data science acceptance rate: Principles of Data Science Hamid R. Arabnia, Kevin Daimi, Robert Stahlbock, Cristina Soviany, Leonard Heilig, Kai Brüssau, 2020-07-08 This book provides readers with a thorough understanding of various research areas within the field of data science. The book introduces readers to various techniques for data acquisition, extraction, and cleaning, data summarizing and modeling, data analysis and communication techniques, data science tools, deep learning, and various data science applications. Researchers can extract and conclude various future ideas and topics that could result in potential publications or thesis. Furthermore, this book contributes to Data Scientists’ preparation and to enhancing their knowledge of the field. The book provides a rich collection of manuscripts in highly regarded data science topics, edited by professors with long experience in the field of data science. Introduces various techniques, methods, and algorithms adopted by Data Science experts Provides a detailed explanation of data science perceptions, reinforced by practical examples Presents a road map of future trends suitable for innovative data science research and practice |
| boston university data science acceptance rate: Analytics and Knowledge Management Suliman Hawamdeh, Hsia-Ching Chang, 2018-08-06 The process of transforming data into actionable knowledge is a complex process that requires the use of powerful machines and advanced analytics technique. Analytics and Knowledge Management examines the role of analytics in knowledge management and the integration of big data theories, methods, and techniques into an organizational knowledge management framework. Its chapters written by researchers and professionals provide insight into theories, models, techniques, and applications with case studies examining the use of analytics in organizations. The process of transforming data into actionable knowledge is a complex process that requires the use of powerful machines and advanced analytics techniques. Analytics, on the other hand, is the examination, interpretation, and discovery of meaningful patterns, trends, and knowledge from data and textual information. It provides the basis for knowledge discovery and completes the cycle in which knowledge management and knowledge utilization happen. Organizations should develop knowledge focuses on data quality, application domain, selecting analytics techniques, and on how to take actions based on patterns and insights derived from analytics. Case studies in the book explore how to perform analytics on social networking and user-based data to develop knowledge. One case explores analyze data from Twitter feeds. Another examines the analysis of data obtained through user feedback. One chapter introduces the definitions and processes of social media analytics from different perspectives as well as focuses on techniques and tools used for social media analytics. Data visualization has a critical role in the advancement of modern data analytics, particularly in the field of business intelligence and analytics. It can guide managers in understanding market trends and customer purchasing patterns over time. The book illustrates various data visualization tools that can support answering different types of business questions to improve profits and customer relationships. This insightful reference concludes with a chapter on the critical issue of cybersecurity. It examines the process of collecting and organizing data as well as reviewing various tools for text analysis and data analytics and discusses dealing with collections of large datasets and a great deal of diverse data types from legacy system to social networks platforms. |
| boston university data science acceptance rate: Data Science in Context Alfred Z. Spector, Peter Norvig, Chris Wiggins, Jeannette M. Wing, 2022-10-20 Four leading experts convey the promise of data science and examine challenges in achieving its benefits and mitigating some harms. |
| boston university data science acceptance rate: Insights in Neurocognitive Aging and Behavior: 2021 Kristy A. Nielson, Ian M. McDonough, Anja Soldan, 2023-03-13 |
| boston university data science acceptance rate: Data Science and Analytics Usha Batra, Nihar Ranjan Roy, Brajendra Panda, 2020-05-27 This two-volume set (CCIS 1229 and CCIS 1230) constitutes the refereed proceedings of the 5th International Conference on Recent Developments in Science, Engineering and Technology, REDSET 2019, held in Gurugram, India, in November 2019. The 74 revised full papers presented were carefully reviewed and selected from total 353 submissions. The papers are organized in topical sections on data centric programming; next generation computing; social and web analytics; security in data science analytics; big data analytics. |
| boston university data science acceptance rate: Engineering Translational Models of Lung Homeostasis and Disease Chelsea M. Magin, 2023-05-17 Cutting-edge engineering approaches towards modelling lung homeostasis and disease have created dynamic new opportunities for interdisciplinary collaboration and unprecedented progress toward understanding and treating lung disease. This text connects established research in lung biology and physiology to innovative engineering strategies for pulmonary modelling. This unique approach aims to encourage and facilitate progress among a greater audience of basic and translational scientists, clinicians, and medical practitioners. Engineering Translational Models of Lung Homeostasis and Disease illustrates the advances in lung tissue characterization, revealing dynamic changes in the structure, mechanics, and composition of the extracellular matrix. This information paves the way for tissue-informed engineering models of pulmonary tissue, improved design of clinical materials, and advances against a variety of common pathologies. Current translational challenges are highlighted, as are engineering opportunities to overcome these barriers. This foundational text holds valuable lessons for researchers and clinicians throughout the fields of engineering, materials science, cell biology, pulmonary medicine, and clinical science. · Each section focuses on a specific region of the lung, presenting either the biological or clinical perspective along with complimentary engineering approaches · Covers the interface of engineering and lung biology · Highlights emerging new models to study lung disease and repair Chapter 4 is available open access under a Creative Commons Attribution 4.0 International License via link.springer.com |
| boston university data science acceptance rate: Advanced Studies in Classification and Data Science Tadashi Imaizumi, Akinori Okada, Sadaaki Miyamoto, Fumitake Sakaori, Yoshiro Yamamoto, Maurizio Vichi, 2020-09-25 This edited volume focuses on the latest developments in classification and data science and covers a wide range of topics in the context of data analysis and related areas, e.g. the analysis of complex data, analysis of qualitative data, methods for high-dimensional data, dimensionality reduction, data visualization, multivariate statistical methods, and various applications to real data in the social sciences, medical sciences, and other disciplines. In addition to sharing theoretical and methodological findings, the book shows how to apply the proposed methods to a variety of problems — e.g. in consumer behavior, decision-making, marketing data and social network structures. Both methodological aspects and applications to a wide range of areas such as economics, behavioral science, marketing science, management science and the social sciences are covered. The book is chiefly intended for researchers and practitioners who are interested in the latest developments and practical applications in these fields, as well as applied statisticians and data analysts. Its combination of methodological advances with a wide range of real-world applications gathered from several fields makes it of unique value in helping readers solve their research problems. |
| boston university data science acceptance rate: Ecological Forecasting Michael C. Dietze, 2017-05-30 An authoritative and accessible introduction to the concepts and tools needed to make ecology a more predictive science Ecologists are being asked to respond to unprecedented environmental challenges. How can they provide the best available scientific information about what will happen in the future? Ecological Forecasting is the first book to bring together the concepts and tools needed to make ecology a more predictive science. Ecological Forecasting presents a new way of doing ecology. A closer connection between data and models can help us to project our current understanding of ecological processes into new places and times. This accessible and comprehensive book covers a wealth of topics, including Bayesian calibration and the complexities of real-world data; uncertainty quantification, partitioning, propagation, and analysis; feedbacks from models to measurements; state-space models and data fusion; iterative forecasting and the forecast cycle; and decision support. Features case studies that highlight the advances and opportunities in forecasting across a range of ecological subdisciplines, such as epidemiology, fisheries, endangered species, biodiversity, and the carbon cycle Presents a probabilistic approach to prediction and iteratively updating forecasts based on new data Describes statistical and informatics tools for bringing models and data together, with emphasis on: Quantifying and partitioning uncertainties Dealing with the complexities of real-world data Feedbacks to identifying data needs, improving models, and decision support Numerous hands-on activities in R available online |
| boston university data science acceptance rate: Sustainable Investing: Problems And Solutions Anatoly B Schmidt, 2024-08-08 This book covers multifaceted problems and their possible solutions in sustainable investing. Written by experts in the field from academia and industry, the book includes three main topics. The general problems of sustainable investing are addressed in Part 1. They include the discussion of the concept of double materiality, current ESG legal framework and its specifics for private equity, the reviews of the sustainable investment indexes and funds, as well as the machine learning techniques for deriving and analysing the ESG ratings.Part 2 is devoted to the climate change. It covers net-zero portfolios being the means of reducing the investment carbon footprint, estimation of the Scope 3 greenhouse gas emissions, venture investments in carbon dioxide removal technologies, and an optimization problem of fuel production in carbon trading.Finally, Part 3 describes several sustainable investing strategies based on including sustainability indices and factors into the portfolio choice framework. It also introduces new portfolio performance measures relevant for sustainable investing. |
| boston university data science acceptance rate: Higher Education and SDG11 Julio Lumbreras, Jaime Moreno-Serna, 2024-11-05 Articulating a shared vision of climate-neutral cities, this installment in the Higher Education and the Sustainable Development Goals series asserts the unique position of HEIs to facilitate and unlock the much-needed alignment of research and education with SDG-oriented action. |
| boston university data science acceptance rate: Advances and Innovations in Statistics and Data Science Wenqing He, Liqun Wang, Jiahua Chen, Chunfang Devon Lin, 2022-10-27 This book highlights selected papers from the 4th ICSA-Canada Chapter Symposium, as well as invited articles from established researchers in the areas of statistics and data science. It covers a variety of topics, including methodology development in data science, such as methodology in the analysis of high dimensional data, feature screening in ultra-high dimensional data and natural language ranking; statistical analysis challenges in sampling, multivariate survival models and contaminated data, as well as applications of statistical methods. With this book, readers can make use of frontier research methods to tackle their problems in research, education, training and consultation. |
| boston university data science acceptance rate: Physical and Medical Conditions Associated with Autism Martina Micai, Mila Vulchanova, Valentina Riva , David Saldaña, 2024-07-02 Some specific physical and medical conditions are well recognized to be more common in autistic individuals compared to the general population (e.g., sleep-wake disorders, epilepsy, sensory impairments). However, the prevalence and the impact on autistic individuals and their families of other physical and medical conditions, such as cardiovascular conditions, cancer, musculoskeletal conditions, food intolerance, allergies, autoimmune problems, diabetes, and neurocutaneous disorders have yet to be established. The presence of such co-occurring conditions affects the success of treatment and worsens the quality of life of autistic individuals and their carers. Importantly, the awareness of the presence of specific physical and medical conditions associated with autism allows for targeted interventions and better outcomes. |
| boston university data science acceptance rate: Deep Learning Techniques for Automation and Industrial Applications Pramod Singh Rathore, Sachin Ahuja, Srinivasa Rao Burri, Ajay Khunteta, Anupam Baliyan, Abhishek Kumar, 2024-07-23 This book provides state-of-the-art approaches to deep learning in areas of detection and prediction, as well as future framework development, building service systems and analytical aspects in which artificial neural networks, fuzzy logic, genetic algorithms, and hybrid mechanisms are used. Deep learning algorithms and techniques are found to be useful in various areas, such as automatic machine translation, automatic handwriting generation, visual recognition, fraud detection, and detecting developmental delays in children. “Deep Learning Techniques for Automation and Industrial Applications” presents a concise introduction to the recent advances in this field of artificial intelligence (AI). The broad-ranging discussion covers the algorithms and applications in AI, reasoning, machine learning, neural networks, reinforcement learning, and their applications in various domains like agriculture, manufacturing, and healthcare. Applying deep learning techniques or algorithms successfully in these areas requires a concerted effort, fostering integrative research between experts from diverse disciplines from data science to visualization. This book provides state-of-the-art approaches to deep learning covering detection and prediction, as well as future framework development, building service systems, and analytical aspects. For all these topics, various approaches to deep learning, such as artificial neural networks, fuzzy logic, genetic algorithms, and hybrid mechanisms, are explained. Audience The book will be useful to researchers and industry engineers working in information technology, data analytics network security, and manufacturing. Graduate and upper-level undergraduate students in advanced modeling and simulation courses will find this book very useful. |
| boston university data science acceptance rate: The Routledge Handbook of Evolutionary Approaches to Religion Yair Lior, Justin Lane, 2022-11-30 The past two decades have seen a growing interest in evolutionary and scientific approaches to religion. The Routledge Handbook of Evolutionary Approaches to Religion is an outstanding reference source to the key topics, problems and debates in this exciting and emerging field. Comprising over thirty chapters by a team of international contributors the handbook pulls together scholarship in the following areas: evolutionary psychology and the cognitive science of religion (CSR) cultural evolution the complementarity of evolutionary psychology, cognitive science and cultural evolution Within these sections central issues, debates and problems are examined, including: Cliodynamics, cultural group selection, costly signaling, dual inheritance theory, literacy, transmitting narratives, prosociality, supernatural punishment, cognition and ritual, meme theory, fusion theory, sexual selection, agency detection, evoked culture, social brain hypothesis, theory of mind, developmental psychology, emergence theory, social learning, cultural cybernetics, cultural epidemiology, evolutionary and cultural psychology, memetics, by-product and adaptationist theories of religion, systems and information theory, and computer modeling. This Handbook is essential reading for students and researchers in religious studies and anthropology. It will also be very useful to those in related fields, such as psychology, sociology of religion, cognitive biology, and evolutionary biology. |
| boston university data science acceptance rate: MEDINFO 2023 — The Future Is Accessible J. Bichel-Findlay, P. Otero, P. Scott, 2024-04-02 Science-fiction author William Gibson is famously quoted as saying, “The future is already here – it's just not very evenly distributed.” During the Covid pandemic, telehealth and remote monitoring were elevated from interesting innovations to essential tools in many healthcare systems, but not all countries had the infrastructure necessary to pivot quickly, amply demonstrating the negative consequences of the digital divide. This book presents the proceedings of MedInfo 2023, the 19th World Congress on Medical and Health Informatics, held from 8 – 12 July 2023 in Sydney, Australia. This series of biennial conferences provides a platform for the discussion of applied approaches to data, information, knowledge, and wisdom in health and wellness. The theme and title of MedInfo 2023 was The Future is Accessible, but the digital divide is a major concern for health and care-informatics professionals, whether because of global economic disparities, digital literacy gaps, or limited access to reliable information about health. A total of 935 submissions were received for the conference, of which 228 full papers, 43 student papers and 117 posters were accepted following a thorough peer-review process involving 279 reviewers. Topics covered include: information and knowledge management; quality, safety and outcomes; health data science; human, organizational and social aspects; and global health informatics. Significant advances in artificial intelligence, machine learning, augmented reality, virtual reality, and genomics hold great hope for future healthcare planning, delivery, management, education, evaluation, and research, and this book will be of interest to all those working to not only exploit the benefits of these technologies, but also to identify ways to overcome their associated challenges. |
| boston university data science acceptance rate: The Handbook of Continuing Professional Development for the Health Informatics Professional JoAnn Klinedinst, 2022-03-10 Engaging in ongoing, continuing professional development (CPD) is a strategic imperative for the health informatics professional. In our global economy, healthcare is fast-paced, dynamic, and ever-changing. While this rapid change is both exciting and exhausting, digital health transformation is positively impacting lives, today and every day, in ways not previously imagined. Faced with a COVID-19 pandemic that has forever changed the landscape of health and care delivery, global health and care stakeholders must ensure that our ecosystem continues to rapidly evolve through innovation, government and ministry incentives, and technological advancements to reach citizens everywhere. For these reasons, health informaticists must embrace lifelong learning to ensure they have the professional competencies to advance initiatives that positively impact patient care. The Handbook of Continuing Professional Development for the Health Informatics Professional, Second Edition has adapted to the evolving needs of health and care professionals everywhere. The Handbook provides the rationale and the resources to do so and serves as a reference to enhance one’s career. No other comprehensive resource exists to assist health informaticists in developing and maintaining their professional competencies. Written as a contributed compilation of topics by leading practitioners, the book discusses the most critical competencies needed to ensure understanding of the vast health and care ecosystem while also highlighting industry influences that shape the very evolution of health information and technology. About HIMSS The Healthcare Information and Management Systems Society (HIMSS) is a global advisor, thought leader, and member association committed to transforming the health ecosystem. As a mission-driven non-profit, HIMSS offers a unique depth and breadth of expertise in health innovation, public policy, workforce development, research, and analytics to advise leaders, stakeholders, and influencers from across the ecosystem on best practices. With a community-centric approach, our innovation engine delivers key insights, education, and engaging events to healthcare providers, payers, governments, startups, life sciences, and other health services organizations, ensuring they have the right information at the point of decision. HIMSS has served the global health community for more than 60 years with focused operations across North America, Europe, the United Kingdom, the Middle East, and Asia-Pacific. |
| boston university data science acceptance rate: Research Handbook on Energy, Law and Ethics Malik R. Dahlan, Rosa M. Lastra, Gustavo Rochette, 2022-11-22 This Research Handbook offers crucial ethical perspectives on navigating the increasingly complex and contested landscape of contemporary energy law. Taking an interdisciplinary approach, it brings together diverse scholarship and expertise from academia, international organizations, legal practice and the judiciary to address wide-ranging issues linking energy and law to ethical drivers such as wealth, peace and war, development, climate change, and use and abuse of natural resources. |
| boston university data science acceptance rate: Advances in Data Science and Information Engineering Robert Stahlbock, Gary M. Weiss, Mahmoud Abou-Nasr, Cheng-Ying Yang, Hamid R. Arabnia, Leonidas Deligiannidis, 2021-10-29 The book presents the proceedings of two conferences: the 16th International Conference on Data Science (ICDATA 2020) and the 19th International Conference on Information & Knowledge Engineering (IKE 2020), which took place in Las Vegas, NV, USA, July 27-30, 2020. The conferences are part of the larger 2020 World Congress in Computer Science, Computer Engineering, & Applied Computing (CSCE'20), which features 20 major tracks. Papers cover all aspects of Data Science, Data Mining, Machine Learning, Artificial and Computational Intelligence (ICDATA) and Information Retrieval Systems, Information & Knowledge Engineering, Management and Cyber-Learning (IKE). Authors include academics, researchers, professionals, and students. Presents the proceedings of the 16th International Conference on Data Science (ICDATA 2020) and the 19th International Conference on Information & Knowledge Engineering (IKE 2020); Includes papers on topics from data mining to machine learning to informational retrieval systems; Authors include academics, researchers, professionals and students. |
| boston university data science acceptance rate: Principles of Statistical Analysis Ery Arias-Castro, 2022-08-25 This concise course in data analysis and inference for the mathematically literate builds on survey sampling and designed experiments. |
| boston university data science acceptance rate: Bad Data Handbook Q. Ethan McCallum, 2012-11-07 What is bad data? Some people consider it a technical phenomenon, like missing values or malformed records, but bad data includes a lot more. In this handbook, data expert Q. Ethan McCallum has gathered 19 colleagues from every corner of the data arena to reveal how they’ve recovered from nasty data problems. From cranky storage to poor representation to misguided policy, there are many paths to bad data. Bottom line? Bad data is data that gets in the way. This book explains effective ways to get around it. Among the many topics covered, you’ll discover how to: Test drive your data to see if it’s ready for analysis Work spreadsheet data into a usable form Handle encoding problems that lurk in text data Develop a successful web-scraping effort Use NLP tools to reveal the real sentiment of online reviews Address cloud computing issues that can impact your analysis effort Avoid policies that create data analysis roadblocks Take a systematic approach to data quality analysis |
| boston university data science acceptance rate: The Big Unlock Paddy Padmanabhan, 2017-11-17 Along with a shift towards value-based care, a digital transformation is under way in health care. However, health care enterprises are having a hard time keeping up with advances in information technology. Organizations that could once spend months or years developing a strategy to deliver solutions now must implement changes on a near real-time basis. Complicating matters is the emergence of new data sources, new technology architectures and models, and new methods to analyze an avalanche of data. This book provides a framework for understanding the competitive landscape for digital health and advanced analytics solutions that are harnessing data to unlock insights. It reveals a set of key principles, or universal themes, for success in the digital health marketplace. Whether youre a health care information technology specialist, a digital health startup or technology firm with a strategic focus on health care, a venture capitalist, or just interested in the industry structure and the emerging technology landscape in health care, youll learn how to grow revenue and profits while creating a sustainable competitive advantage. Take a key step in navigating the exciting transformation of health care, and harness the power of data and analytics with The Big Unlock. |
| boston university data science acceptance rate: Digital Therapeutics: Using Software to Treat, Manage, and Prevent Disease Louis N. Awad, Kirsten Smayda, Sabrina R. Taylor, Terry D. Ellis, Tim Campellone, 2023-10-20 |
| boston university data science acceptance rate: Polarization Dynamics of Mode-Locked Fiber Lasers Sergey V. Sergeyev, Chengbo Mou, 2023-04-20 This book provides a comprehensive review of the latest research on the science, technology, and applications of mode-locked fiber lasers generating pulse trains with the evolving state of polarization at time scales ranging from a few pulse widths to 10,000 laser cavity round-trip times. It supports readers with a timely source of information on the current novel scientific concepts, and cost-effective schematics, in addition to an overview of the feasible applications. The book aims to demonstrate for the nonlinear science community a newly emerging field of nonlinear science, and so stimulates the development of new theoretical approaches and opens new horizons for the photonics community by pushing boundaries of the existing laser systems towards new applications. The new classes of optical sources and photonic devices explored in this book will be relevant with applications to other fields, including medicine, bio-photonics, metrology, and environmental safety. Key Features • Provides a cutting edge review of the latest emerging science, technology and applications in the field. • Tackles a topic with fast growing interest in USA, Europe and China. • Explores the simple and cheap design and tests of lasers, and outlines the feasible applications. |
| boston university data science acceptance rate: Health Communication in the 21st Century Kevin B. Wright, Lisa Sparks, H. Dan O'Hair, 2012-11-05 This popular and engaging text on health communication is now revised and updated in a second edition that incorporates recent research and boasts new material on topics such as crisis communication, social disparities in health, and systemic reform. Fully revised second edition of this popular and authoritative text Includes fresh material on topics such as crisis communication, health care reform, global health issues, and political issues in health communication New case studies, examples, and updated glossary keep the work relevant and student-friendly Provides effective strategies for healthcare organizations and individuals in communicating with patients Updated and enhanced online resources, including PowerPoint slides, test bank, and instructors manual, available upon publication at www.wiley.com/go/wright |
| boston university data science acceptance rate: Statistics for Data Scientists Maurits Kaptein, Edwin van den Heuvel, 2022-02-02 This book provides an undergraduate introduction to analysing data for data science, computer science, and quantitative social science students. It uniquely combines a hands-on approach to data analysis – supported by numerous real data examples and reusable [R] code – with a rigorous treatment of probability and statistical principles. Where contemporary undergraduate textbooks in probability theory or statistics often miss applications and an introductory treatment of modern methods (bootstrapping, Bayes, etc.), and where applied data analysis books often miss a rigorous theoretical treatment, this book provides an accessible but thorough introduction into data analysis, using statistical methods combining the two viewpoints. The book further focuses on methods for dealing with large data-sets and streaming-data and hence provides a single-course introduction of statistical methods for data science. |
| boston university data science acceptance rate: Fusion Payette, Kevin Sullivan, 2020-06-30 Fusion: The Performance of Architecture explores the work of award-winning, Boston-based architecture firm Payette, a leader in the design of complex settings for science and healthcare. Payette’s work embodies the integration of design and performance that is essential to the creation of humane and sustainable buildings of any type. To achieve this integration amidst the programmatic intricacy, technological complexity, and intense energy use of hospitals and laboratories, the firm draws on its almost ninety-year history of progressive innovation. It draws, as well, on an inclusive, collaborative, research-oriented culture that is a model for the profession. Fusion presents Payette’s philosophy and traces the firm’s contributions through concise histories of laboratory and hospital design. It explores the core principles that underlie its work—Identity and Transformation, Materiality and Craft, Taming Complexity and Measuring Performance—and digs deeply into seven of the firm’s most recent projects. Other chapters describe the process of nurturing the design excellence and practice culture that earned Payette the 2019 AIA Architecture Firm Award. The monograph’s 400 diagrams, drawings, and photographs reveal the firm’s principles and methods, along with the open-source tools it has developed to enable it to design, not “by the numbers,” but with the numbers. A gallery of architectural “fingerprints” presents plan views of more than 100 of Payette’s projects, drawn to a common scale. With a preface by Z Smith, Director of Sustainability and Building Performance at EskewDumezRipple, and an introduction from Kevin Sullivan, President of Payette, Fusion includes essays by Sullivan and partners James Collins, George Marsh, Leon Drachman, Andrea Love and Peter Vieira, as well as a critical reflection by Mark Lee, Chair of the Department of Architecture at the Harvard Graduate School of Design. |
| boston university data science acceptance rate: Data Science for Librarians Yunfei Du, Hammad Rauf Khan, 2020-03-26 This unique textbook intersects traditional library science with data science principles that readers will find useful in implementing or improving data services within their libraries. Data Science for Librarians introduces data science to students and practitioners in library services. Writing for academic, public, and school library managers; library science students; and library and information science educators, authors Yunfei Du and Hammad Rauf Khan provide a thorough overview of conceptual and practical tools for data librarian practice. Partially due to how quickly data science evolves, libraries have yet to recognize core competencies and skills required to perform the job duties of a data librarian. As society transitions from the information age into the era of big data, librarians and information professionals require new knowledge and skills to stay current and take on new job roles, such as data librarianship. Such skills as data curation, research data management, statistical analysis, business analytics, visualization, smart city data, and learning analytics are relevant in library services today and will become increasingly so in the near future. This text serves as a tool for library and information science students and educators working on data science curriculum design. |
| boston university data science acceptance rate: Big Data, Big Analytics Michael Minelli, Michele Chambers, Ambiga Dhiraj, 2012-12-27 Unique prospective on the big data analytics phenomenon for both business and IT professionals The availability of Big Data, low-cost commodity hardware and new information management and analytics software has produced a unique moment in the history of business. The convergence of these trends means that we have the capabilities required to analyze astonishing data sets quickly and cost-effectively for the first time in history. These capabilities are neither theoretical nor trivial. They represent a genuine leap forward and a clear opportunity to realize enormous gains in terms of efficiency, productivity, revenue and profitability. The Age of Big Data is here, and these are truly revolutionary times. This timely book looks at cutting-edge companies supporting an exciting new generation of business analytics. Learn more about the trends in big data and how they are impacting the business world (Risk, Marketing, Healthcare, Financial Services, etc.) Explains this new technology and how companies can use them effectively to gather the data that they need and glean critical insights Explores relevant topics such as data privacy, data visualization, unstructured data, crowd sourcing data scientists, cloud computing for big data, and much more. |
| boston university data science acceptance rate: Research Handbook on University Rankings Hazelkorn, Ellen, Mihut, Georgiana, 2021-12-10 Gathering unique and thoughtful contributions from leading international scholars, this timely Research Handbook offers diverse perspectives on university rankings twenty years after the first global rankings emerged. It presents an in-depth analysis that reflects the current state of research on rankings, their influence and impact. |
| boston university data science acceptance rate: Data Science and Complex Networks Guido Caldarelli, Alessandro Chessa, 2016-11-10 This book provides a comprehensive yet short description of the basic concepts of Complex Network theory. In contrast to other books the authors present these concepts through real case studies. The application topics span from Foodwebs, to the Internet, the World Wide Web and the Social Networks, passing through the International Trade Web and Financial time series. The final part is devoted to definition and implementation of the most important network models. The text provides information on the structure of the data and on the quality of available datasets. Furthermore it provides a series of codes to allow immediate implementation of what is theoretically described in the book. Readers already used to the concepts introduced in this book can learn the art of coding in Python by using the online material. To this purpose the authors have set up a dedicated web site where readers can download and test the codes. The whole project is aimed as a learning tool for scientists and practitioners, enabling them to begin working instantly in the field of Complex Networks. |
| boston university data science acceptance rate: Analyzing the Analyzers Harlan Harris, Sean Murphy, Marck Vaisman, 2013-06-10 Despite the excitement around data science, big data, and analytics, the ambiguity of these terms has led to poor communication between data scientists and organizations seeking their help. In this report, authors Harlan Harris, Sean Murphy, and Marck Vaisman examine their survey of several hundred data science practitioners in mid-2012, when they asked respondents how they viewed their skills, careers, and experiences with prospective employers. The results are striking. Based on the survey data, the authors found that data scientists today can be clustered into four subgroups, each with a different mix of skillsets. Their purpose is to identify a new, more precise vocabulary for data science roles, teams, and career paths. This report describes: Four data scientist clusters: Data Businesspeople, Data Creatives, Data Developers, and Data Researchers Cases in miscommunication between data scientists and organizations looking to hire Why T-shaped data scientists have an advantage in breadth and depth of skills How organizations can apply the survey results to identify, train, integrate, team up, and promote data scientists |
| boston university data science acceptance rate: The Urban Commons Daniel T. O'Brien, 2018-12-03 The future of smart cities has arrived, courtesy of citizens and their phones. To prove it, Daniel T. O’Brien explains the transformative insights gleaned from years researching Boston’s 311 reporting system, a sophisticated city management tool that has revolutionized how ordinary Bostonians use and maintain public spaces. Through its phone service, mobile app, website, and Twitter account, 311 catalogues complaints about potholes, broken street lights, graffiti, litter, vandalism, and other issues that are no one citizen’s responsibility but affect everyone’s quality of life. The Urban Commons offers a pioneering model of what modern digital data and technology can do for cities like Boston that seek both prosperous growth and sustainability. Analyzing a rich trove of data, O’Brien discovers why certain neighborhoods embrace the idea of custodianship and willingly invest their time to monitor the city’s common environments and infrastructure. On the government’s side of the equation, he identifies best practices for implementing civic technologies that engage citizens, for deploying public services in collaborative ways, and for utilizing the data generated by these efforts. Boston’s 311 system has narrowed the gap between residents and their communities, and between constituents and local leaders. The result, O’Brien shows, has been the creation of more effective policy and practices that reinvigorate the way citizens and city governments approach their mutual interests. By unpacking when, why, and how the 311 system has worked for Boston, The Urban Commons reveals the power and potential of this innovative system, and the lessons learned that other cities can adapt. |
| boston university data science acceptance rate: Data Science Vijay Kotu, Bala Deshpande, 2018-11-27 Learn the basics of Data Science through an easy to understand conceptual framework and immediately practice using RapidMiner platform. Whether you are brand new to data science or working on your tenth project, this book will show you how to analyze data, uncover hidden patterns and relationships to aid important decisions and predictions. Data Science has become an essential tool to extract value from data for any organization that collects, stores and processes data as part of its operations. This book is ideal for business users, data analysts, business analysts, engineers, and analytics professionals and for anyone who works with data. You'll be able to: - Gain the necessary knowledge of different data science techniques to extract value from data. - Master the concepts and inner workings of 30 commonly used powerful data science algorithms. - Implement step-by-step data science process using using RapidMiner, an open source GUI based data science platform Data Science techniques covered: Exploratory data analysis, Visualization, Decision trees, Rule induction, k-nearest neighbors, Naïve Bayesian classifiers, Artificial neural networks, Deep learning, Support vector machines, Ensemble models, Random forests, Regression, Recommendation engines, Association analysis, K-Means and Density based clustering, Self organizing maps, Text mining, Time series forecasting, Anomaly detection, Feature selection and more... - Contains fully updated content on data science, including tactics on how to mine business data for information - Presents simple explanations for over twenty powerful data science techniques - Enables the practical use of data science algorithms without the need for programming - Demonstrates processes with practical use cases - Introduces each algorithm or technique and explains the workings of a data science algorithm in plain language - Describes the commonly used setup options for the open source tool RapidMiner |
Boston.com: Local breaking news, sports, weather, and things to do
What Boston cares about right now: Get breaking updates on news, sports, and weather. Local alerts, things to do, and more on Boston.com.
Boston - Wikipedia
Boston [a] is the capital and most populous city in the Commonwealth of Massachusetts in the United States. The city serves as the cultural and financial center of New England, a region of …
30 Top-Rated Things to Do in Boston | U.S. News Travel
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Visiting Boston | Boston.gov
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Boston | History, Population, Map, Climate, & Facts | Britannica
6 days ago · Boston, city, capital of the commonwealth of Massachusetts, and seat of Suffolk county, in the northeastern United States. It lies on Massachusetts Bay, an arm of the Atlantic …
Meet Boston | Your Official Guide to Boston
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Boston Bucket List: 30 Best Things To Do in Boston - Earth …
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Boston - Explore Culture & Historical Sites in Boston ... - Visit The …
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Boston, Massachusetts - WorldAtlas
Apr 9, 2022 · Boston is a city in the northeastern United States that serves as the capital of the Commonwealth of Massachusetts and the seat of Suffolk County. It has an area of 46 square …
UMass Amherst
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ADMISSION RATES BY PROGRAM BETWEEN AS REPORTED …
Program Name Percentage of applicants offered admission among all applicants, past 5 years Link Yale University (PhD) 1.46% http://pantheon.yale.edu/~bbl2/talks ...
MASTER OF ARTS MENTAL HEALTH COUNSELING
o An official transcript from each college or university attended o Three letters of recommendation from individuals who can attest to the likelihood of your academic and career success ...
A. General Information - Office of the Provost
Duke University Chapel Drive Durham, NC 27708 919-684-8111 www.duke.edu 919-684-3214 2138 Campus Drive; Box 90586 Durham, NC 27708 ... The items in this section correspond to …
Medical School Admission Requirements™ (MSAR®) Report …
CA California University of Science and Medicine-School of Medicine N/A All applicants placed on the wait list will be informed by a letter from the Office of Admissions via U.S. mail within 2 …
Fact Sheet 2023-24 Updated Final - Augusta University
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Medical School Cumulative Data 2022 - uConnect
Medical School Cumulative Data 2022 Accepted Students' Averages School Applications Acceptances Matriculations Science GPA Total GPA Total MCATs 101 Alabama 6 0 102 …
Boston University Common Data Set
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As a Master of Data Science student, you have the option of focusing on one of the following four distinct tracks: (1) Applied Data Science; (2) Big Data Systems; (3) Computational and …
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Boston University’s medical school and teaching hospital offer access to tremendous resources for clinical. experiences, with a diverse patient population, making this . the only program to be …
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Boston University Common Data Set
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UNDERGRADUATE ADMISSIONS PROFILE - Rutgers University
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Graduate Study in Psychology Summary Report: …
other psychology, which had higher medians. Figure 5 plots the interquartile master’s-level acceptance rates (the ratio of acceptances to applications). Median acceptance rates for most …
2001-04 2000-2001 Fact Sheet - open.bu.edu
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New England Law | Boston - 2024 Standard 509 Information …
Acceptance Rate (Percent) 76.27 Enrollees from Applicant pool 400 Enrollment rate from Completed Applications 11.79 Enrollment rate from Offers of Admission 15.46 Other first-year …
NEW INTERNATIONAL STUDENTS BY EDUCATIONAL LEVEL
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Boston University Computer Science Masters Acceptance Rate Barnes, Stuart J.,Scornavacca, Eusebio. Boston University Computer Science Masters Acceptance Rate: Programming with …
Boston University Common Data Set
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ANNUAL REPORT 2022-23 - Northeastern University College …
of data, technology, and human literacies, uniquely preparing graduates ... First-Year Acceptance Rate, from 12,727 apps (Fall 2022) vs. 36.9%, from 8,680 apps (2017) GPA (Fall 2022) ... a …
ANNUAL ADMISSIONS STATISTICAL REPORT - University of …
Computer Science 20 Mathematics 10.6 Economics and Management 19.7 Law* 9.3 Mathematics and Computer Science 12.8 History and Politics 9.1 Medicine 12.6 Physics 8.9 Biomedical …
Class of 2025 Profile - Columbia Undergraduate Admissions
Combined Data for Columbia College and Columbia Engineering First-Year Applicant Overview 1490 to 1560 SAT SCORE RANGE FOR MIDDLE 50% OF ADMITTED STUDENTS WHO …
Early Decision and Regular Decision Acceptance Rates - Class …
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Two-Year First-Time Pass Rates by School Physical Therapist
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PRE-ACCEPTED STUDENTS (2023-2024) - MEAN GPAs and …
Pre-acceptance rate Bachelor's Applied Computer Science and Artificial Intelligence 91,97 7,83 18,8% Bachelor's Classics 87,97 8,52 16,9% Bachelor's Global Humanities 91,23 7,91 11,5% …
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July 2023 Uniform Bar Examination Results by Law School
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20 First Destination Experiential Education - Case Western …
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Medical School Applications - Career Engagement
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ADMISSION RATES BY PROGRAM BETWEEN AS REPORTED …
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A. General Information - Boston College
Six-year graduation rate for 2015 cohort (G divided by C) 85%. 92%: 91%. For Two-Year Institutions. 2019 Cohort 2018 Cohort B12. Please provide data for the . 2019. cohort if …
William F. Connell School of Nursing Undergraduate
electives, and all nursing courses and nursing-specific science courses (e.g., Anatomy & Physiology, Microbiology, Statistics, and Life Science Chemistry). For nursing courses, the …
FREQUENTLY ASKED QUESTIONS - Undergraduate Admissions
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course evaluations 13 student advising 13 academic advisors 13 academic services center (asc) 13 educational resource center (erc) 13 petition and appeals process 13 department of physical …
Undergraduate and Graduate Admissions Applications, …
Oct 18, 2024 · Acceptance Rate: The percent of applicants who were accepted in the . 1st choice . major or in total to the university. Yield: The percent of accepted students who enrolled in the . …
2023˝24 UNDERGRADUATE ADMISSIONS BULLETIN
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Boston’s People and Economy
Apr 6, 2022 · Center, Tufts Medical Center, and Boston Children’s Hospital, as well as community-based health centers. In total, there are 22 inpatient hospitals in the city with a …
Boston University Common Data Set
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Tufts University Fact Book 2023 2024 - Office of the Provost …
Tufts University Fact Book 2023 2024 SAT Reasoning/ACT Test Scores of Entering Class Fall of Year Shown Verbal/Critical Reading SAT Scores—Average Scores* Year National All Entering …
Data Science, Master's Degree - Johns Hopkins University
Data Science, Master's Degree 1 DATA SCIENCE, MASTER'S DEGREE ... The Data Science Master’s program at the Johns Hopkins University is a fully residential program which will …
Table A-23: MCAT and GPA Grid for Applicants and Acceptees …
Acceptance rate % 0.7 1.3 3.6 11.6 20.9 31.9 41.7 57.1 68.0 78.1 41.9 Notes: The means and SDs of MCAT scores are calculated based on data from applicants who applied with MCAT scores …
Massachusetts Academy of Math and Science
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LATE ENTRY ACCELERATED PROGRAM (LEAP) - BU Engineering
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Undergraduate and Graduate Admissions Applications, …
Fall 2014 through 2023 2014 2015 2016 2017 2018 2019 2020 2021 2022 2023 State-Supported Graduate Master's Applications 5,218 4,918 4,665 4,977 5,150 4,676 5,012 ...
2022 Master of Finance Employment Report - MIT Sloan
This year we achieved a 98% reporting rate for full-time data, and a 100% reporting rate for internship data. MIT Sloan Master of Finance graduates found opportunities for impact in …
A. General Information - Boston College
H - Six-year graduation rate for 2011 cohort (G divided by C) 90% 93% 92% 92% For Two-Year Institutions 2015 Cohort B12 B13 B14 0 Please provide data for the 2015 cohort if available. If …
We’ve finalized our Early Decision selection process and …
December 15, 2023 Dear Colleagues, We’ve finalized our Early Decision selection process and notified applicants of their decisions.
Master of Science Degree Data Science Program Guide …
Rowan University undergraduates majoring in the Bachelor of Science in Computer Science program may apply to the ... Master of Science in Data Science degrees in five years instead …
