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Computational Imaging for Scene Understanding: Transient, Spectral, and Polarimetric Analysis
By Takuya Funatomi, Takahiro Okabe. 2024
Most cameras are inherently designed to mimic what is seen by the human eye: they have three channels of RGB…
and can achieve up to around 30 frames per second (FPS). However, some cameras are designed to capture other modalities: some may have the ability to capture spectra from near UV to near IR rather than RGB, polarimetry, different times of light travel, etc. Such modalities are as yet unknown, but they can also collect robust data of the scene they are capturing. This book will focus on the emerging computer vision techniques known as computational imaging. These include capturing, processing and analyzing such modalities for various applications of scene understanding.Software Engineering for Data Scientists
By Catherine Nelson. 2024
Data science happens in code. The ability to write reproducible, robust, scaleable code is key to a data science project's…
success—and is absolutely essential for those working with production code. This practical book bridges the gap between data science and software engineering,and clearly explains how to apply the best practices from software engineering to data science.Examples are provided in Python, drawn from popular packages such as NumPy and pandas. If you want to write better data science code, this guide covers the essential topics that are often missing from introductory data science or coding classes, including how to:Understand data structures and object-oriented programmingClearly and skillfully document your codePackage and share your codeIntegrate data science code with a larger code baseLearn how to write APIsCreate secure codeApply best practices to common tasks such as testing, error handling, and loggingWork more effectively with software engineersWrite more efficient, maintainable, and robust code in PythonPut your data science projects into productionAnd moreThe Engineering Leader
By Cate Huston. 2024
Great engineers don't necessarily make great leaders—at least, not without a lot of work. Finding your path to becoming a…
strong leader is often fraught with challenges. It's not easy to figure out how to be strategic, successful, and considerate while also being firm. Whether you're on the management or individual contributor track, you need to develop strong leadership skills.This practical book shows you how to become a well-rounded and resilient engineering leader.Understand what it means to be the driving force behind your careerLearn how to self-manage and avoid the pitfalls that many newer managers faceEstablish evolving practices and structures to best scale your teamDefine the impact of your team and its core mission and valuesUser Error: Resisting Computer Culture
By Ellen Rose. 2003
User Error explodes the myth of computer technology as juggernaut. Multimedia educator Ellen Rose shows that there is no bandwagon,…
no out-of-control dynamo, no titanic conspiracy to overwhelm us. Instead, there is our own desire to join the fraternity of users, a fraternity that confers legitimacy and power on those who enter the brave new world. Rose exposes how we surrender decision-making power in personal and workplace computing situations. As users we willingly grant authority to the creators of software, support materials, and the seductive infrastructure of technocracy. “Smart” users are rewarded; reluctant users are pathologized. User identity is deliberately constructed at the crossroads of industry, consumer demand, and complicity. User Error sounds a timely alarm, calling on all of us who use the new technologies to recognize how we are being co-opted. With awareness we can reassert our own responsibility and power in this increasingly important interaction. Savvy, accessible, and up-to-date, User Error offers insight, inspiration, and strategies of resistance to general readers, technology professionals, students, and scholars alike.Machine Learning for Business Analytics: Concepts, Techniques, and Applications with Analytic Solver Data Mining
By Galit Shmueli, Peter C. Bruce, Kuber R. Deokar, Nitin R. Patel. 2023
MACHINE LEARNING FOR BUSINESS ANALYTICS Machine learning—also known as data mining or predictive analytics—is a fundamental part of data science.…
It is used by organizations in a wide variety of arenas to turn raw data into actionable information. Machine Learning for Business Analytics: Concepts, Techniques, and Applications with Analytic Solver® Data Mining provides a comprehensive introduction and an overview of this methodology. The fourth edition of this best-selling textbook covers both statistical and machine learning algorithms for prediction, classification, visualization, dimension reduction, rule mining, recommendations, clustering, text mining, experimentation, time series forecasting and network analytics. Along with hands-on exercises and real-life case studies, it also discusses managerial and ethical issues for responsible use of machine learning techniques. This fourth edition of Machine Learning for Business Analytics also includes: An expanded chapter on deep learning A new chapter on experimental feedback techniques, including A/B testing, uplift modeling, and reinforcement learning A new chapter on responsible data science Updates and new material based on feedback from instructors teaching MBA, Masters in Business Analytics and related programs, undergraduate, diploma and executive courses, and from their students A full chapter devoted to relevant case studies with more than a dozen cases demonstrating applications for the machine learning techniques End-of-chapter exercises that help readers gauge and expand their comprehension and competency of the material presented A companion website with more than two dozen data sets, and instructor materials including exercise solutions, slides, and case solutions This textbook is an ideal resource for upper-level undergraduate and graduate level courses in data science, predictive analytics, and business analytics. It is also an excellent reference for analysts, researchers, and data science practitioners working with quantitative data in management, finance, marketing, operations management, information systems, computer science, and information technology.Machine Learning Q and AI: 30 Essential Questions and Answers on Machine Learning and AI
By Sebastian Raschka. 2024
Learn the answers to 30 cutting-edge questions in machine learning and AI and level up your expertise in the field.If…
you&’re ready to venture beyond introductory concepts and dig deeper into machine learning, deep learning, and AI, the question-and-answer format of Machine Learning Q and AI will make things fast and easy for you, without a lot of mucking about.Born out of questions often fielded by author Sebastian Raschka, the direct, no-nonsense approach of this book makes advanced topics more accessible and genuinely engaging. Each brief, self-contained chapter journeys through a fundamental question in AI, unraveling it with clear explanations, diagrams, and hands-on exercises.WHAT'S INSIDE:FOCUSED CHAPTERS: Key questions in AI are answered concisely, and complex ideas are broken down into easily digestible parts.WIDE RANGE OF TOPICS: Raschka covers topics ranging from neural network architectures and model evaluation to computer vision and natural language processing.PRACTICAL APPLICATIONS: Learn techniques for enhancing model performance, fine-tuning large models, and more.You&’ll also explore how to:• Manage the various sources of randomness in neural network training• Differentiate between encoder and decoder architectures in large language models• Reduce overfitting through data and model modifications• Construct confidence intervals for classifiers and optimize models with limited labeled data• Choose between different multi-GPU training paradigms and different types of generative AI models• Understand performance metrics for natural language processing• Make sense of the inductive biases in vision transformersIf you&’ve been on the hunt for the perfect resource to elevate your understanding of machine learning, Machine Learning Q and AI will make it easy for you to painlessly advance your knowledge beyond the basics.Tor: From the Dark Web to the Future of Privacy
By Ben Collier. 2024
A biography of Tor—a cultural and technological history of power, privacy, and global politics at the internet's core.Tor, one of…
the most important and misunderstood technologies of the digital age, is best known as the infrastructure underpinning the so-called Dark Web. But the real &“dark web,&” when it comes to Tor, is the hidden history brought to light in this book: where this complex and contested infrastructure came from, why it exists, and how it connects with global power in intricate and intimate ways. In Tor: From the Dark Web to the Future of Privacy, Ben Collier has written, in essence, a biography of Tor—a cultural and technological history of power, privacy, politics, and empire in the deepest reaches of the internet.The story of Tor begins in the 1990s with its creation by the US Navy&’s Naval Research Lab, from a convergence of different cultural worlds. Drawing on in-depth interviews with designers, developers, activists, and users, along with twenty years of mailing lists, design documents, reporting, and legal papers, Collier traces Tor&’s evolution from those early days to its current operation on the frontlines of global digital power—including the strange collaboration between US military scientists and a group of freewheeling hackers called the Cypherpunks. As Collier charts the rise and fall of three different cultures in Tor&’s diverse community—the engineers, the maintainers, and the activists, each with a distinct understanding of and vision for Tor—he reckons with Tor&’s complicated, changing relationship with contemporary US empire. Ultimately, the book reveals how different groups of users have repurposed Tor and built new technologies and worlds of their own around it, with profound implications for the future of the Internet.The Importance of Being Educable: A New Theory of Human Uniqueness
By Leslie Valiant. 2024
In the age of AI, why our future depends on better understanding what makes us humanWe are at a crossroads…
in history. If we hope to share our planet successfully with one another and the AI systems we are creating, we must reflect on who we are, how we got here, and where we are heading. The Importance of Being Educable puts forward a provocative new exploration of the extraordinary facility of humans to absorb and apply knowledge. The remarkable &“educability&” of the human brain can be understood as an information processing ability. It sets our species apart, enables the civilization we have, and gives us the power and potential to set our planet on a steady course. Yet it comes hand in hand with an insidious weakness. While we can readily absorb entire systems of thought about worlds of experience beyond our own, we struggle to judge correctly what information we should trust.In this visionary book, Leslie Valiant argues that understanding the nature of our own educability is crucial to safeguarding our future. After breaking down how we process information to learn and apply knowledge, and drawing comparisons with other animals and AI systems, he explains why education should be humankind&’s central preoccupation.Will the unique capability that has been so foundational to our achievements and civilization continue to drive our progress, or will we fall victim to our vulnerabilities? If we want to play to our species&’ great strength and protect our collective future, we must better understand and prioritize the vital importance of being educable. This book provides a road map.Soft Computing and Signal Processing: Proceedings of 6th ICSCSP 2023, Volume 1 (Lecture Notes in Networks and Systems #864)
By Vustikayala Sivakumar Reddy, Jiacun Wang, K. T. V. Reddy. 2024
This book presents selected research papers on current developments in the fields of soft computing and signal processing from the…
Sixth International Conference on Soft Computing and Signal Processing (ICSCSP 2023). The book covers topics such as soft sets, rough sets, fuzzy logic, neural networks, genetic algorithms and machine learning and discusses various aspects of these topics, e.g., technological considerations, product implementation and application issues.This two-volume set constitutes selected papers presented during the First International Conference on Advanced Computing, Machine Learning, Robotics and Internet Technologies,…
AMRIT 2023, held in Silchar, India, in March 2023.The 20 full papers and 27 short papers presented were thoroughly reviewed and selected from 110 submissions. They cover the following topics: artificial intelligence, machine learning, natural language processing, image processing, data science, soft computing techniques, computer networks and security, computer architecture and algorithms.Advanced Computing, Machine Learning, Robotics and Internet Technologies: First International Conference, AMRIT 2023, Silchar, India, March 10–11, 2023, Revised Selected Papers, Part II (Communications in Computer and Information Science #1954)
By Prodipto Das, Shahin Ara Begum, Rajkumar Buyya. 2024
This two-volume set constitutes selected papers presented during the First International Conference on Advanced Computing, Machine Learning, Robotics and Internet Technologies,…
AMRIT 2023, held in Silchar, India, in March 2023.The 20 full papers and 27 short papers presented were thoroughly reviewed and selected from 110 submissions. They cover the following topics: artificial intelligence, machine learning, natural language processing, image processing, data science, soft computing techniques, computer networks and security, computer architecture and algorithms.Euro-Par 2023: Euro-Par 2023 International Workshops, Limassol, Cyprus, August 28 – September 1, 2023, Revised Selected Papers, Part I (Lecture Notes in Computer Science #14351)
By Demetris Zeinalipour, Dora Blanco Heras, George Pallis, Herodotos Herodotou, Demetris Trihinas, Daniel Balouek, Patrick Diehl, Terry Cojean, Karl Fürlinger, Maja Hanne Kirkeby, Matteo Nardelli, Pierangelo Di Sanzo. 2024
This book constitutes revised selected papers from the workshops held at the 29th International Conference on Parallel and Distributed Computing,…
Euro-Par 2023, which took place in Limassol, Cyprus, during August 28–September 1, 2023. The 42 full papers presented in this book together with 11 symposium papers and 14 demo/poster papers were carefully reviewed and selected from 55 submissions. The papers cover covering all aspects of parallel and distributed processing, ranging from theory to practice, from small to the largest parallel and distributed systems and infrastructures, from fundamental computational problems to applications, from architecture, compiler, language and interface design and implementation, to tools, support infrastructures, and application performance aspects.LNCS 14351:First International Workshop on Scalable Compute Continuum (WSCC 2023). First International Workshop on Tools for Data Locality, Power and Performance (TDLPP 2023). First International Workshop on Urgent Analytics for Distributed Computing (QuickPar 2023). 21st International Workshop on Algorithms, Models and Tools for Parallel Computing on Heterogeneous Platforms (HETEROPAR 2023). LNCS 14352: Second International Workshop on Resource AWareness of Systems and Society (RAW 2023). Third International Workshop on Asynchronous Many-Task systems for Exascale (AMTE 2023). Third International Workshop on Performance and Energy-efficiency in Concurrent and Distributed Systems (PECS 2023) First Minisymposium on Applications and Benefits of UPMEM commercial Massively Parallel Processing-In-Memory Platform (ABUMPIMP 2023). First Minsymposium on Adaptive High Performance Input / Output Systems (ADAPIO 2023).This book mainly focuses on the design methodologies of various quantum circuits, DNA circuits, DNA-quantum circuits, and quantum-DNA circuits. In…
this text, the author has compiled various design aspects of multiple-valued logic DNA-quantum and quantum-DNA sequential circuits, memory devices, programmable logic devices, and nanoprocessors. Multiple-Valued Computing in Quantum Molecular Biology: Sequential Circuits, Memory Devices, Programmable Logic Devices, and Nanoprocessors is Volume 2 of a two-volume set, and consists of four parts. This book presents various design aspects of multiple-valued logic DNA-quantum and quantum-DNA sequential circuits, memory devices, programmable logic devices, and nanoprocessors. Part I discusses multiple-valued quantum and DNA sequential circuits such as D flip-flop, SR latch, SR flip-flop, JK flip-flop, T flip-flop, shift register, ripple counter, and synchronous counter, which are described, respectively, with the applications and working procedures. After that, multiple-valued quantum-DNA and DNA-quantum sequential circuits such as D flip-flop, SR flip-flop, JK flip-flop, T flip-flop, shift register, ripple counter and synchronous counter circuits are explained with working procedures and architecture. Part II discusses the architecture and design procedure of memory devices such as random access memory (RAM), read-only memory (ROM), programmable read-only memory (PROM), and cache memory, which are sequentially described in multiple-valued quantum, DNA, quantum-DNA, and DNA-quantum computing. In Part III, the author examines the architectures and working principles of programmable logic devices such as programmable logic array (PLA), programmable array logic (PAL), field programmable gate array (FPGA), and complex programmable logic device (CPLD) in multiple-valued quantum, DNA, quantum-DNA, and DNA-quantum computing. Multiple-valued quantum, DNA, quantum-DNA, and DNA-quantum nanoprocessors are designed with algorithms in Part IV. Furthermore, the basic components of ternary nanoprocessors such as T-RAM, ternary instruction register, ternary incrementor circuit, ternary decoder, ternary multiplexer, ternary accumulator in quantum, DNA, quantum-DNA, and DNA-quantum computing are also explained in detail. This book will be of great help to researchers and students in quantum computing, DNA computing, quantum-DNA computing, and DNA-quantum computing.Handbook of Mixture Analysis (ISSN)
By Sylvia Frühwirth-Schnatter, Gilles Celeux and Christian P. Robert. 2019
Mixture models have been around for over 150 years, and they are found in many branches of statistical modelling, as…
a versatile and multifaceted tool. They can be applied to a wide range of data: univariate or multivariate, continuous or categorical, cross-sectional, time series, networks, and much more. Mixture analysis is a very active research topic in statistics and machine learning, with new developments in methodology and applications taking place all the time. The Handbook of Mixture Analysis is a very timely publication, presenting a broad overview of the methods and applications of this important field of research. It covers a wide array of topics, including the EM algorithm, Bayesian mixture models, model-based clustering, high-dimensional data, hidden Markov models, and applications in finance, genomics, and astronomy.Features: Provides a comprehensive overview of the methods and applications of mixture modelling and analysis Divided into three parts: Foundations and Methods; Mixture Modelling and Extensions; and Selected Applications Contains many worked examples using real data, together with computational implementation, to illustrate the methods described Includes contributions from the leading researchers in the field The Handbook of Mixture Analysis is targeted at graduate students and young researchers new to the field. It will also be an important reference for anyone working in this field, whether they are developing new methodology, or applying the models to real scientific problems.Numerical Analysis and Scientific Computation (Textbooks in Mathematics)
By Jeffery J. Leader. 2022
This is an introductory single-term numerical analysis text with a modern scientific computing flavor. It offers an immediate immersion in…
numerical methods featuring an up-to-date approach to computational matrix algebra and an emphasis on methods used in actual software packages, always highlighting how hardware concerns can impact the choice of algorithm. It fills the need for a text that is mathematical enough for a numerical analysis course yet applied enough for students of science and engineering taking it with practical need in mind.The standard methods of numerical analysis are rigorously derived with results stated carefully and many proven. But while this is the focus, topics such as parallel implementations, the Basic Linear Algebra Subroutines, halfto quadruple-precision computing, and other practical matters are frequently discussed as well.Prior computing experience is not assumed. Optional MATLAB subsections for each section provide a comprehensive self-taught tutorial and also allow students to engage in numerical experiments with the methods they have just read about. The text may also be used with other computing environments.This new edition offers a complete and thorough update. Parallel approaches, emerging hardware capabilities, computational modeling, and data science are given greater weight.Data Science and Big Data Analytics in Smart Environments
By Marta Chinnici; Florin Pop; Cătălin Negru. 2022
Most applications generate large datasets, like social networking and social influence programs, smart cities applications, smart house environments, Cloud applications,…
public web sites, scientific experiments and simulations, data warehouse, monitoring platforms, and e-government services. Data grows rapidly, since applications produce continuously increasing volumes of both unstructured and structured data. Large-scale interconnected systems aim to aggregate and efficiently exploit the power of widely distributed resources. In this context, major solutions for scalability, mobility, reliability, fault tolerance and security are required to achieve high performance and to create a smart environment. The impact on data processing, transfer and storage is the need to re-evaluate the approaches and solutions to better answer the user needs. A variety of solutions for specific applications and platforms exist so a thorough and systematic analysis of existing solutions for data science, data analytics, methods and algorithms used in Big Data processing and storage environments is significant in designing and implementing a smart environment.Fundamental issues pertaining to smart environments (smart cities, ambient assisted leaving, smart houses, green houses, cyber physical systems, etc.) are reviewed. Most of the current efforts still do not adequately address the heterogeneity of different distributed systems, the interoperability between them, and the systems resilience. This book will primarily encompass practical approaches that promote research in all aspects of data processing, data analytics, data processing in different type of systems: Cluster Computing, Grid Computing, Peer-to-Peer, Cloud/Edge/Fog Computing, all involving elements of heterogeneity, having a large variety of tools and software to manage them. The main role of resource management techniques in this domain is to create the suitable frameworks for development of applications and deployment in smart environments, with respect to high performance. The book focuses on topics covering algorithms, architectures, management models, high performance computing techniques and large-scale distributed systems.Artificial Intelligence in Accounting: Practical Applications (ISSN)
By Cory Ng, John Alarcon. 2021
Artificial Intelligence in Accounting: Practical Applications was written with a simple goal: to provide accountants with a foundational understanding of…
AI and its many business and accounting applications. It is meant to serve as a guide for identifying opportunities to implement AI initiatives to increase productivity and profitability. This book will help you answer questions about what AI is and how it is used in the accounting profession today. Offering practical guidance that you can leverage for your organization, this book provides an overview of essential AI concepts and technologies that accountants should know, such as machine learning, deep learning, and natural language processing. It also describes accounting-specific applications of robotic process automation and text mining. Illustrated with case studies and interviews with representatives from global professional services firms, this concise volume makes a significant contribution to examining the intersection of AI and the accounting profession. This innovative book also explores the challenges and ethical considerations of AI. It will be of great interest to accounting practitioners, researchers, educators, and students.Is art created with computers really art? This book answers ‘yes.’ Computers can generate visual art with unique aesthetic effects…
based on innovations in computer technology and a Postmodern naturalization of technology wherein technology becomes something we live in as well as use. The present study establishes these claims by looking at digital art’s historical emergence from the 1960s to the start of the present century. Paul Crowther, using a philosophical approach to art history, considers the first steps towards digital graphics, their development in terms of three-dimensional abstraction and figuration, and then the complexities of their interactive formats.The Lean IT Field Guide: A Roadmap for Your Transformation
By Michael A. Orzen, Thomas A. Paider. 2016
How many IT books have you read that are long on theory and short on practical application? They are interesting,…
but not very impactful. They provide a framework from which to think and understand, but lack a process from which to act. Addressing this urgent need for the IT community, The Lean IT Field Guide explains how to initiate, execute, and sustain a lean IT transformation.Illuminating a clear path to lean IT, the authors integrate more than two decades of combined experience to provide you with a proven method for creating and sustaining a true lean IT workplace. This field guide not only highlights the organizational techniques of more agile and lean processes, but also the leadership work required to help management adopt these new approaches.Based on proven methods from different industries, including banking, manufacturing, insurance, food and beverage, and logistics, the book details a clear model that covers all the components you need to achieve and sustain a favorable work environment and culture in support of lean IT.Filled with anecdotes and case studies from actual businesses, the book includes pictures, templates, and examples that illustrate the application of the lean methods discussed.Virtual reality (VR) techniques are becoming increasingly popular. The use of computer modeling and visualization is no longer uncommon in…
the area of ergonomics and occupational health and safety. This book explains how studies conducted in a simulated virtual world are making it possible to test new solutions for designed workstations, offering a high degree of ease for introducing modifications and eliminating risk and work-related accidents. Virtual reality techniques offer a wide range of possibilities including increasing the cognitive abilities of the elderly, adapting workstations for people with disabilities and special needs, and remote control of machines using collaborative robots.Detailed discussions include: Testing protective devices, safety systems, and the numerical reconstruction of work accidents Using computer simulation in generic virtual environments On the one hand, it is a self-study book made so by well-crafted and numerous examples. On the other hand, through a detailed analysis of the virtual reality from a point of view of work safety and ergonomics and health improvement. Ewa Grabska, Jagiellonian University, Kraków, PolandNoteworthy is the broad scope and diversity of the addressed problems, ranging from training employees using VR environments with different degrees of perceived reality; training and rehabilitation of the elderly; to designing, testing, modifying, and adapting workplaces to various needs including those of disabled workers; to simulation and investigation of the cause of accidents at a workplace.Andrzej Krawiecki, Warsaw University of Technology, Warsaw, Poland