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Thanks to the availability of texts on the Web in recent years, increased knowledge and information have been made available to broader audiences. However, the way in which a text is written—its vocabulary, its syntax—can be difficult to read and understand for many people, especially those with poor literacy, cognitive or linguistic impairment, or those with limited knowledge of the language of the text. Texts containing uncommon words or long and complicated sentences can be difficult to read and understand by people as well as difficult to analyze by machines. Automatic text simplification is the process of transforming a text into another text which, ideally conveying the same message, will be easier to read and understand by a broader audience. The process usually involves the replacement of difficult or unknown phrases with simpler equivalents and the transformation of long and syntactically complex sentences into shorter and less complex ones. Automatic text simplification, a research topic which started 20 years ago, now has taken on a central role in natural language processing research not only because of the interesting challenges it posesses but also because of its social implications. This book presents past and current research in text simplification, exploring key issues including automatic readability assessment, lexical simplification, and syntactic simplification. It also provides a detailed account of machine learning techniques currently used in simplification, describes full systems designed for specific languages and target audiences, and offers available resources for research and development together with text simplification evaluation techniques.

Thanks to the availability of texts on the Web in recent years, increased knowledge and information have been made available to broader audiences. However, the way in which a text is written—its vocabulary, its syntax—can be difficult to read and understand for many people, especially those with poor literacy, cognitive or linguistic impairment, or those with limited knowledge of the language of the text. Texts containing uncommon words or long and complicated sentences can be difficult to read and understand by people as well as difficult to analyze by machines. Automatic text simplification is the process of transforming a text into another text which, ideally conveying the same message, will be easier to read and understand by a broader audience. The process usually involves the replacement of difficult or unknown phrases with simpler equivalents and the transformation of long and syntactically complex sentences into shorter and less complex ones. Automatic text simplification, a research topic which started 20 years ago, now has taken on a central role in natural language processing research not only because of the interesting challenges it posesses but also because of its social implications. This book presents past and current research in text simplification, exploring key issues including automatic readability assessment, lexical simplification, and syntactic simplification. It also provides a detailed account of machine learning techniques currently used in simplification, describes full systems designed for specific languages and target audiences, and offers available resources for research and development together with text simplification evaluation techniques.

Speech Recognition has a long history of being one of the difficult problems in Artificial Intelligence and Computer Science. As one goes from problem solving tasks such as puzzles and chess to perceptual tasks such as speech and vision, the problem characteristics change dramatically: knowledge poor to knowledge rich; low data rates to high data rates; slow response time (minutes to hours) to instantaneous response time. These characteristics taken together increase the computational complexity of the problem by several orders of magnitude. Further, speech provides a challenging task domain which embodies many of the requirements of intelligent behavior: operate in real time; exploit vast amounts of knowledge, tolerate errorful, unexpected unknown input; use symbols and abstractions; communicate in natural language and learn from the environment. Voice input to computers offers a number of advantages. It provides a natural, fast, hands free, eyes free, location free input medium. However, there are many as yet unsolved problems that prevent routine use of speech as an input device by non-experts. These include cost, real time response, speaker independence, robustness to variations such as noise, microphone, speech rate and loudness, and the ability to handle non-grammatical speech. Satisfactory solutions to each of these problems can be expected within the next decade. Recognition of unrestricted spontaneous continuous speech appears unsolvable at present. However, by the addition of simple constraints, such as clarification dialog to resolve ambiguity, we believe it will be possible to develop systems capable of accepting very large vocabulary continuous speechdictation.

This book contains the original, peer-reviewed research papers from the International Symposium on Automatic Control and Emerging Technologies, held in Kenitra, Morrocco, on July 11-13, 2023. The topics covered include but are not limited to: System Identification, Linear/Nonlinear Control Systems, Data-driven Modelling and Control, Process Modelling and Process Control, Fault Diagnosis and Reliable Control, Intelligent Systems, and Machine Learning and Artificial Intelligence.The papers showcased here share the latest findings on topics with potential for academic research and industrial applications, making the book a valuable resource for researchers, engineers, and university students alike.

This book proposes secure schemes to address security challenges in secure automatic dependent surveillance-broadcast systems (ADS-B) from five different angles. First, the authors examine encryption schemes applied to the ADS-B environment for protecting messages confidentiality. Second, they propose an ADS-B broadcast authentication scheme with batch verification by employing an identity-based signature. Third, they present ADS-B broadcast authentication scheme based on a digital signature with message recovery, which provides a feature that the message is recoverable from the signature. Fourth, they propose a new cryptographic solution to ADS-B security. Finally, they propose an accurate and efficient cognitive aircraft location verification scheme preserving aircraft location privacy by utilizing a grid-based k-nearest neighbor algorithm. In summary, the authors show how ADS-B data links can greatly enhance flight safety by these proposed schemes without sacrificing data security.Proposes several secure schemes to address security challenges in secure automatic dependent surveillance-broadcast systems (ADS-B);Provides extensive experiments and evaluates the proposed schemes using real-world data;Shows how ADS-B data links can greatly enhance safety without sacrificing data security

AUTOMATIC SPEECH RECOGNITION and TRANSLATION for LOW-RESOURCE LANGUAGES This book is a comprehensive exploration into the cutting-edge research, methodologies, and advancements in addressing the unique challenges associated with ASR and translation for low-resource languages. Automatic Speech Recognition and Translation for Low Resource Languages contains groundbreaking research from experts and researchers sharing innovative solutions that address language challenges in low-resource environments. The book begins by delving into the fundamental concepts of ASR and translation, providing readers with a solid foundation for understanding the subsequent chapters. It then explores the intricacies of low-resource languages, analyzing the factors that contribute to their challenges and the significance of developing tailored solutions to overcome them. The chapters encompass a wide range of topics, ranging from both the theoretical and practical aspects of ASR and translation for low-resource languages. The book discusses data augmentation techniques, transfer learning, and multilingual training approaches that leverage the power of existing linguistic resources to improve accuracy and performance. Additionally, it investigates the possibilities offered by unsupervised and semi-supervised learning, as well as the benefits of active learning and crowdsourcing in enriching the training data. Throughout the book, emphasis is placed on the importance of considering the cultural and linguistic context of low-resource languages, recognizing the unique nuances and intricacies that influence accurate ASR and translation. Furthermore, the book explores the potential impact of these technologies in various domains, such as healthcare, education, and commerce, empowering individuals and communities by breaking down language barriers. Audience The book targets researchers and professionals in the fields of natural language processing, computational linguistics, and speech technology. It will also be of interest to engineers, linguists, and individuals in industries and organizations working on cross-lingual communication, accessibility, and global connectivity.

This book presents a wide and comprehensive range of issues and problems in various fields of science and engineering, from both theoretical and applied perspectives. The desire to develop more effective and efficient tools and techniques for dealing with complex processes and systems has been a natural inspiration for the emergence of numerous fields of science and technology, in particular control and automation and, more recently, robotics. The contributions gathered here concern the development of methods and algorithms to determine best practices regarding broadly perceived decisions or controls. From an engineering standpoint, many of them focus on how to automate a specific process or complex system. From a tools-based perspective, several contributions address the development of analytic and algorithmic methods and techniques, devices and systems that make it possible to develop and subsequently implement the automation and robotization of crucial areas of human activity. All topics discussed are illustrated with sample applications.

This book presents a contrastive linguistics study of Arabic and English for the dual purposes of improved language teaching and speech processing of Arabic via spectral analysis and neural networks. Contrastive linguistics is a field of linguistics which aims to compare the linguistic systems of two or more languages in order to ease the tasks of teaching, learning, and translation. The main focus of the present study is to treat the Arabic minimal syllable automatically to facilitate automatic speech processing in Arabic. It represents important reading for language learners and for linguists with an interest in Arabic and computational approaches.

This book provides readers with a brief account of the history of Language Identification (LI) research and a survey of the features and methods most used in LI literature. LI is the problem of determining the language in which a document is written and is a crucial part of many text processing pipelines. The authors use a unified notation to clarify the relationships between common LI methods. The book introduces LI performance evaluation methods and takes a detailed look at LI-related shared tasks. The authors identify open issues and discuss the applications of LI and related tasks and proposes future directions for research in LI.

This book constitutes the revised and extended papers of the First Automatic Assessment of Parkinsonian Speech Workshop, AAPS 2019, held in Cambridge, Massachusetts, USA, in September 2019. The 6 full papers were thoroughly reviewed and selected from 15 submissions. They present recent research on the automatic assessment of parkinsonian speech from the point of view of such disciplines as machine learning, speech technology, phonetics, neurology, and speech therapy

On the basis of instrument electrical and automatic control system, the 5th International Conference on Electrical Engineering and Automatic Control (CEEAC) was established at the crossroads of information technology and control technology, and seeks to effectively apply information technology to a sweeping trend that views control as the core of intelligent manufacturing and life. This book takes a look forward into advanced manufacturing development, an area shaped by intelligent manufacturing. It highlights the application and promotion of process control represented by traditional industries, such as the steel industry and petrochemical industry; the technical equipment and system cooperative control represented by robot technology and multi-axis CNC; and the control and support of emerging process technologies represented by laser melting and stacking, as well as the emerging industry represented by sustainable and intelligent life. The book places particular emphasis on themicro-segments field, such as intelligent micro-grids, new energy vehicles, and the Internet of Things.

In the fields of data mining and control, the huge amount of unstructured data and the presence of uncertainty in system descriptions have always been critical issues. The book Randomized Algorithms in Automatic Control and Data Mining introduces the readers to the fundamentals of randomized algorithm applications in data mining (especially clustering) and in automatic control synthesis. The methods proposed in this book guarantee that the computational complexity of classical algorithms and the conservativeness of standard robust control techniques will be reduced. It is shown that when a problem requires'brute force'in selecting among options, algorithms based on random selection of alternatives offer good results with certain probability for a restricted time and significantly reduce the volume of operations.

This book describes effective methods for automatically analyzing a sentence, based on the syntactic and semantic characteristics of the elements that form it. To tackle ambiguities, the authors use selectional preferences (SP), which measure how well two words fit together semantically in a sentence. Today, many disciplines require automatic text analysis based on the syntactic and semantic characteristics of language and as such several techniques for parsing sentences have been proposed. Which is better? In this book the authors begin with simple heuristics before moving on to more complex methods that identify nouns and verbs and then aggregate modifiers, and lastly discuss methods that can handle complex subordinate and relative clauses. During this process, several ambiguities arise. SP are commonly determined on the basis of the association between a pair of words. However, in many cases, SP depend on more words. For example, something (such as grass) may be edible, depending on who is eating it (a cow?). Moreover, things such as popcorn are usually eaten at the movies, and not in a restaurant. The authors deal with these phenomena from different points of view.

This book explores break-through approaches to tackling and mitigating the well-known problems of compiler optimization using design space exploration and machine learning techniques. It demonstrates that not all the optimization passes are suitable for use within an optimization sequence and that, in fact, many of the available passes tend to counteract one another. After providing a comprehensive survey of currently available methodologies, including many experimental comparisons with state-of-the-art compiler frameworks, the book describes new approaches to solving the problem of selecting the best compiler optimizations and the phase-ordering problem, allowing readers to overcome the enormous complexity of choosing the right order of optimizations for each code segment in an application. As such, the book offers a valuable resource for a broad readership, including researchers interested in Computer Architecture, Electronic Design Automation and Machine Learning, as well as computer architects and compiler developers.

This book, and the research it describes, resulted from a simple observation we made sometime in 1986. Put simply, we noticed that many VLSI design tools looked'alike'. That is, at least at the overall software architecture level, the algorithms and data structures required to solve problem X looked much like those required to solve problem X'. Unfortunately, this resemblance is often of little help in actually writing the software for problem X'given the software for problem X. In the VLSI CAD world, technology changes rapidly enough that design software must continually strive to keep up. And of course, VLSI design software, and engineering design software in general, is often exquisitely sensitive to some aspects of the domain (technology) in which it operates. Modest changes in functionality have an unfortunate tendency to require substantial (and time-consuming) internal software modifications. Now, observing that large engineering software systems are technology­ dependent is not particularly clever. However, we believe that our approach to xiv Preface dealing with this problem took an interesting new direction. We chose to investigate the extent to which automatic programming ideas cold be used to synthesize such software systems from high-level specifications. This book is one of the results of that effort.

This book constitutes the refereed proceedings of the 10th International Conference, NooJ 2016, held České Budějovice, Czech Republic, in June 2016.The 21 revised full papers presented in this volume were carefully reviewed and selected from 45 submissions. NooJ is a linguistic development environment that provides tools for linguists to construct linguistic resources that formalise a large gamut of linguistic phenomena: typography, orthography, lexicons for simple words, multiword units and discontinuous expressions, inflectional and derivational morphology, local, structural and transformational syntax, and semantics.

This book constitutes the refereed proceedings of the 9th International Conference, NooJ 2015, held in Minsk, Belarus, in June 2015.NooJ 2015 received 51 submissions. The 20 revised full papers presented in this volume were carefully reviewed and selected from the 35 papers that were presented at the conference. The papers are organized in topical sections on corpora, vocabulary and morphology; syntax and semantics; application.

The attempt to spot deception through its correlates in human behavior has a long history. Until recently, these efforts have concentrated on identifying individual'cues'that might occur with deception. However, with the advent of computational means to analyze language and other human behavior, we now have the ability to determine whether there are consistent clusters of differences in behavior that might be associated with a false statement as opposed to a true one. While its focus is on verbal behavior, this book describes a range of behaviors—physiological, gestural as well as verbal—that have been proposed as indicators of deception. An overview of the primary psychological and cognitive theories that have been offered as explanations of deceptive behaviors gives context for the description of specific behaviors. The book also addresses the differences between data collected in a laboratory and'real-world'data with respect to the emotional and cognitive state of the liar. It discusses sources of real-world data and problematic issues in its collection and identifies the primary areas in which applied studies based on real-world data are critical, including police, security, border crossing, customs, and asylum interviews; congressional hearings; financial reporting; legal depositions; human resource evaluation; predatory communications that include Internet scams, identity theft, and fraud; and false product reviews. Having established the background, this book concentrates on computational analyses of deceptive verbal behavior that have enabled the field of deception studies to move from individual cues to overall differences in behavior. The computational work is organized around the features used for classification from ����-gram through syntax to predicate-argument and rhetorical structure. The book concludes with a set of open questions that the computational work has generated.

This book reviews the state-of-the-art in combinatorial testing, with particular emphasis on the automatic generation of test data. It describes the most commonly used approaches in this area - including algebraic construction, greedy methods, evolutionary computation, constraint solving and optimization - and explains major algorithms with examples. In addition, the book lists a number of test generation tools, as well as benchmarks and applications. Addressing a multidisciplinary topic, it will be of particular interest to researchers and professionals in the areas of software testing, combinatorics, constraint solving and evolutionary computation.

This book deals with the problems related to planning motion laws and t- jectories for the actuation system of automatic machines, in particular for those based on electric drives, and robots. The problem of planning suitable trajectories is relevant not only for the proper use of these machines, in order to avoid undesired e?ects such as vibrations or even damages on the mech- ical structure, but also in some phases of their design and in the choice and sizing of the actuators. This is particularly true now that the concept of “el- tronic cams” has replaced, in the design of automatic machines, the classical approach based on “mechanical cams”. The choice of a particular trajectory has direct and relevant implications on several aspects of the design and use of an automatic machine, like the dimensioning of the actuators and of the reduction gears, the vibrations and e?orts generated on the machine and on the load, the tracking errors during the motion execution. For these reasons, in order to understand and appreciate the peculiarities of the di?erent techniques available for trajectory planning, besides the ma- ematical aspects of their implementation also a detailed analysis in the time and frequency domains, a comparison of their main properties under di?erent points of view, and general considerations related to their practical use are reported.

Since the early days of computers, machine learning and automatic programming have attracted researchers in computer science and related fields, particularly pattern recognition and automatic control theory. Most of the learning concepts in machine perception have been inspired by pattern recognition approaches that rely on statistical techniques. These statistical techniques have applicability in limited recognition tasks. Automatic programming in perception systems has generally been limited to interfaces that allow easy specification of the task using natural language. Clearly, machine learning and automatic programming can make percep­ tion systems powerful and easy to use. Vogt's book addresses both these tasks in the context of machine vision. He uses morphological operations to implement his approach which was developed for solving the figure-ground problem in images. His system selects the correct se­ quence of operators to accept or reject pixels for fmding objects in an image. The sequence of operators is selected after a user specifies what the correct objects are. On the surface it may appear that the problem solved by the system is not very interesting, however, the contribution ofVogt's work should not be judged by the images that the system can segment. Its real contribution is in demonstrat­ ing, possibly for'the frrst time, that automatic programming is possible in computer vision systems. The selection of morphological operators demonstrates that to implement an automatic programming-based approach, operators whose behavior is clearly defined in the image space are required.

Automatic learning is a complex, multidisciplinary field of research and development, involving theoretical and applied methods from statistics, computer science, artificial intelligence, biology and psychology. Its applications to engineering problems, such as those encountered in electrical power systems, are therefore challenging, while extremely promising. More and more data have become available, collected from the field by systematic archiving, or generated through computer-based simulation. To handle this explosion of data, automatic learning can be used to provide systematic approaches, without which the increasing data amounts and computer power would be of little use. Automatic Learning Techniques in Power Systems is dedicated to the practical application of automatic learning to power systems. Power systems to which automatic learning can be applied are screened and the complementary aspects of automatic learning, with respect to analytical methods and numerical simulation, are investigated. This book presents a representative subset of automatic learning methods - basic and more sophisticated ones - available from statistics (both classical and modern), and from artificial intelligence (both hard and soft computing). The text also discusses appropriate methodologies for combining these methods to make the best use of available data in the context of real-life problems. Automatic Learning Techniques in Power Systems is a useful reference source for professionals and researchers developing automatic learning systems in the electrical power field.

Explorations in Automatic Thesaurus Discovery presents an automated method for creating a first-draft thesaurus from raw text. It describes natural processing steps of tokenization, surface syntactic analysis, and syntactic attribute extraction. From these attributes, word and term similarity is calculated and a thesaurus is created showing important common terms and their relation to each other, common verb--noun pairings, common expressions, and word family members. The techniques are tested on twenty different corpora ranging from baseball newsgroups, assassination archives, medical X-ray reports, abstracts on AIDS, to encyclopedia articles on animals, even on the text of the book itself. The corpora range from 40,000 to 6 million characters of text, and results are presented for each in the Appendix. The methods described in the book have undergone extensive evaluation. Their time and space complexity are shown to be modest. The results are shown to converge to a stable state as the corpus grows. The similarities calculated are compared to those produced by psychological testing. A method of evaluation using Artificial Synonyms is tested. Gold Standards evaluation show that techniques significantly outperform non-linguistic-based techniques for the most important words in corpora. Explorations in Automatic Thesaurus Discovery includes applications to the fields of information retrieval using established testbeds, existing thesaural enrichment, semantic analysis. Also included are applications showing how to create, implement, and test a first-draft thesaurus.

In the last decade the remarkable advances in computing and networking have sparked an enormous interest in deploying automatic speech recognition in devices and networks, and the trend is accelerating. This book brings together leading academic researchers and industrial practitioners to address the issues in this emerging realm. It covers networked, distributed and embedded speech recognition systems, which are expected to co-exist in the future. The book is divided into four parts: networked speech recognition, distributed speech recognition, embedded speech recognition, and systems and applications. A profound and unified introduction about this area and its latest development is provided, as well as working knowledge needed for research and practical application deployment. This book covers the most up-to-date standards and a number of systems. This all-inclusive reference is an essential read for graduate students, scientists and engineers working or researching in the field of speech recognition and processing.

Once realized, the potential of large-scale quantum computers promises to radically transform computer science. Despite large-scale international efforts, however, essential questions about the potential of quantum algorithms are still unanswered. Automatic Quantum Computer Programming is an introduction both to quantum computing for non-physicists and to genetic programming for non-computer-scientists. The book explores several ways in which genetic programming can support automatic quantum computer programming and presents detailed descriptions of specific techniques, along with several examples of their human-competitive performance on specific problems.

Proceedings of the NATO Advanced Study Institute on New Systems and Architecture for Automatic Speech Recognition and Synthesis, held at Bonas, Gers, France, 2-14 July 1984

The evaluation of a logical formula can be viewed as a game played by two opponents, one trying to show that the formula is true and the other trying to prove it is false. This correspondence has been known for a very long time and has inspired numerous research directions. In this book, the author extends this connection between logic and games to the class of automatic structures, where relations are recognized by synchronous finite automata.In model-checking games for automatic structures, two coalitions play against each other with a particular kind of hierarchical imperfect information. The investigation of such games leads to the introduction of a game quantifier on automatic structures, which connects alternating automata with the classical model-theoretic notion of a game quantifier. This study is then extended, determining the memory needed for strategies in infinitary games on the one hand, and characterizing regularity-preserving Lindström quantifiers on the other. Counting quantifiers are investigated in depth: it is shown that all countable omega-automatic structures are in fact finite-word automatic and that the infinity and uncountability set quantifiers are definable in MSO over countable linear orders and over labeled binary trees.This book is based on the PhD thesis of Lukasz Kaiser, which was awarded with the E.W. Beth award for outstanding dissertations in the fields of logic, language, and information in 2009. The work constitutes an innovative study in the area of algorithmic model theory, demonstrating the deep interplay between logic and computability in automatic structures. It displays very high technical and presentational quality and originality, advances significantly the field of algorithmic model theory and raises interesting new questions, thus emerging as a fruitful and inspiring source for future research.

Automatic Quantum Computer Programming provides an introduction to quantum computing for non-physicists, as well as an introduction to genetic programming for non-computer-scientists. The book explores several ways in which genetic programming can support automatic quantum computer programming and presents detailed descriptions of specific techniques, along with several examples of their human-competitive performance on specific problems. Source code for the author's QGAME quantum computer simulator is included as an appendix, and pointers to additional online resources furnish the reader with an array of tools for automatic quantum computer programming.

Speech recognition technology is being increasingly employed in human-machine interfaces. A remaining problem however is the robustness of this technology to non-native accents, which still cause considerable difficulties for current systems.In this book, methods to overcome this problem are described. A speaker adaptation algorithm that is capable of adapting to the current speaker with just a few words of speaker-specific data based on the MLLR principle is developed and combined with confidence measures that focus on phone durations as well as on acoustic features. Furthermore, a specific pronunciation modelling technique that allows the automatic derivation of non-native pronunciations without using non-native data is described and combined with the previous techniques to produce a robust adaptation to non-native accents in an automatic speech recognition system.

The significance of natural language texts as the prime information structure for the management and dissemination of knowledge is - as the rise of the web shows - still increasing. Making relevant texts available in different contexts is of primary importance for efficient task completion in academic and industrial settings. Meeting this demand requires automatic form and content based processing of texts, which enables to reconstruct or even to explore the dynamic relationship of language system, text event and context type. The rise of new application areas, disciplines and methods (e.g. text and web mining) testify to the importance of this task. Moreover, the growing area of new media demands the further development of methods of text analysis with respect to their computational linguistic, information theoretical, and mathematical underpinning. This book contributes to this task. It collects contributions of authors from a multidisciplinary area who focus on the topic of automatic text analysis from several (i.e. linguistic, mathematical, and information theoretical) perspectives. It describes methodological as well as methodical foundations and collects approaches in the field of text and corpus linguistics. In this sense, it contributes to the computational linguistic and information theoretical grounding of automatic text analysis.

Automatic Indexing and Abstracting of Document Texts summarizes the latest techniques of automatic indexing and abstracting, and the results of their application. It also places the techniques in the context of the study of text, manual indexing and abstracting, and the use of the indexing descriptions and abstracts in systems that select documents or information from large collections. Important sections of the book consider the development of new techniques for indexing and abstracting. The techniques involve the following: using text grammars, learning of the themes of the texts including the identification of representative sentences or paragraphs by means of adequate cluster algorithms, and learning of classification patterns of texts. In addition, the book is an attempt to illuminate new avenues for future research. Automatic Indexing and Abstracting of Document Texts is an excellent reference for researchers and professionals working in the field of content management and information retrieval.

We are both fans of watching animated stories. Every evening, before or after d- ner, we always sit in front of the television and watch the animation program, which is originally produced and shown for children. We find ourselves becoming younger while immerged in the interesting plot of the animation: how the princess is first killed and then rescued, how the little rat defeats the big cat, etc. But what we have found in those animation programs are not only interesting plots, but also a big chance for the application of computer science and artificial intelligence techniques. As is well known, the cost of producing animated movies is very high, even with the use of computer graphics techniques. Turning a story in text form into an animated movie is a long and complicated procedure. We came to the c- clusion that many parts of this process could be automated by using artificial - telligence techniques. It is actually a challenge and test for machine intelligence. So we decided to explore the possibility of a full life cycle automation of c- puter animation generation. By full life cycle we mean the generation process of computer animation from a children s story in natural language text form to the final animated movie. It is of course a task of immense difficulty. However, we decided to try our best and to see how far we could go.

Automatic Re-engineering of Software Using Genetic Programming describes the application of Genetic Programming to a real world application area - software re-engineering in general and automatic parallelization specifically. Unlike most uses of Genetic Programming, this book evolves sequences of provable transformations rather than actual programs. It demonstrates that the benefits of this approach are twofold: first, the time required for evaluating a population is drastically reduced, and second, the transformations can subsequently be used to prove that the new program is functionally equivalent to the original. Automatic Re-engineering of Software Using Genetic Programming shows that there are applications where it is more practical to use GP to assist with software engineering rather than to entirely replace it. It also demonstrates how the author isolated aspects of a problem that were particularly suited to GP, and used traditional software engineering techniques in those areas for which they were adequate. Automatic Re-engineering of Software Using Genetic Programming is an excellent resource for researchers in this exciting new field.

This book provides comprehensive coverage on a new direction in computational mathematics research: automatic search for formulas. Formulas must be sought in all areas of science and life: these are the laws of the universe, the macro and micro world, fundamental physics, engineering, weather and natural disasters forecasting; the search for new laws in economics, politics, sociology. Accumulating many years of experience in the development and application of numerical methods of symbolic regression to solving control problems, the authors offer new possibilities not only in the field of control automation, but also in the design of completely different optimal structures in many fields. For specialists in the field of control, Machine Learning Control by Symbolic Regression opens up a new promising direction of research and acquaints scientists with the methods of automatic construction of control systems.For specialists in the fieldof machine learning, the book opens up a new, much broader direction than neural networks: methods of symbolic regression. This book makes it easy to master this new area in machine learning and apply this approach everywhere neural networks are used. For mathematicians, the book opens up a new approach to the construction of numerical methods for obtaining analytical solutions to unsolvable problems; for example, numerical analytical solutions of algebraic equations, differential equations, non-trivial integrals, etc. For specialists in the field of artificial intelligence, the book offers a machine way to solve problems, framed in the form of analytical relationships.

The book provides general knowledge of automatic control engineering and its applications.Providing an overview of control theory and systems, the chapters introduce transfer functions, modeling of control systems, automatic control systems, block diagrams, and signal flow graphs. While control system analysis and design are accompanied by root-locus methods and frequency response analyses, distributed control systems, nonlinarity in control systems including Z-transformation are also presented.With straightforward demonstrations, examples, and multiple-choice questions, this book can be used as a reference textbook for electrical and electronics engineering, computer control engineering, automation engineering, mechatronics engineering, mechanics, robotics, AI control systems, hydraulics, process engineering, safety control engineering, aeronautical and aerospace engineering, auto-pilot system, decision-making system, and stock exchange, and will be suitable for majors, non-majors, and experts in the field of science and technology.

This book offers a timely and comprehensive snapshot of research and developments in the fields of dynamic systems and control engineering. Covering a wide range of theoretical and practical issues, the contributions describes a number of different control approaches, such as PID control, adaptive control, nonlinear systems and control, intelligent monitoring and control based on fuzzy and neural systems, robust control systems, and real time control, among others. Sensors and actuators, measurement systems, renewable energy systems, aeronautic and aerospace systems as well as industrial control and automation, are also comprehensively covered. Based on the proceedings of the 15th APCA International Conference on Automatic Control and Soft Computing, held on July 6-8, 2022, in Caparica, Portugal, the book offers a timely and thoroughly survey of the latest research in the fields of dynamic systems and automatic control engineering, and a source of inspiration for researchers and professionals worldwide.

This thoroughly revised and updated second edition of the bestselling Springer Handbook of Automation provides the most advanced, comprehensive, and balanced coverage of the technical and engineering aspects of automation.Starting with a holistic discussion on the history and societal impacts of automation, the book provides the tools to understand, design and implement automation solutions. This includes:the scientific foundations, from traditional control theory to the latest developments in artificial intelligence and machine learning;the technical aspects of automation design, from hardware such as mechatronics and sensors to cyber-physical systems and human-machine interaction, to collaborative automation;the methods of automation integration in products, processes and services; and finally,the technical, economic and ethical management of automation.Readers will find the most complete and state-of-the-art overview on the implementation, effects and examples of automation in industrial contexts, as well as infrastructure, service, medical and healthcare, home, office and enterprise automation. The book concludes with up-to-date case studies from industrial forerunners. Edited by an internationally renowned and experienced expert and supported by a distinguished advisory board, this Springer Handbook offers a wealth of information for industry practitioners, aspiring engineers and automation experts alike.

The book is concerned with contemporary methodologies used for automatic text summarization. It proposes interesting approaches to solve well-known problems on text summarization using computational intelligence (CI) techniques including cognitive approaches. A better understanding of the cognitive basis of the summarization task is still an open research issue; an extent of its use in text summarization is highlighted for further exploration. With the ever-growing text, people in research have little time to spare for extensive reading, where summarized information helps for a better understanding of the context at a shorter time.This book helps students and researchers to automatically summarize the text documents in an efficient and effective way. The computational approaches and the research techniques presented guides to achieve text summarization at ease. The summarized text generated supports readers to learn the context or the domain at a quicker pace. The book is presented with reasonable amount of illustrations and examples convenient for the readers to understand and implement for their use. It is not to make readers understand what text summarization is, but for people to perform text summarization using various approaches. This also describes measures that can help to evaluate, determine, and explore the best possibilities for text summarization to analyse and use for any specific purpose. The illustration is based on social media and healthcare domain, which shows the possibilities to work with any domain for summarization. The new approach for text summarization based on cognitive intelligence is presented for further exploration in the field.

The two-volume proceedings set LNAI 14338 and 14339 constitutes the refereed proceedings of the 25th International Conference on Speech and Computer, SPECOM 2023, held in Dharwad, India, during November 29–December 2, 2023.The 94 papers included in these proceedings were carefully reviewed and selected from 174 submissions. They focus on all aspects of speech science and technology: ​automatic speech recognition; computational paralinguistics; digital signal processing; speech prosody; natural language processing; child speech processing; speech processing for medicine; industrial speech and language technology; speech technology for under-resourced languages; speech analysis and synthesis; speaker and language identification, verification and diarization.

The two-volume proceedings set LNAI 14338 and 14339 constitutes the refereed proceedings of the 25th International Conference on Speech and Computer, SPECOM 2023, held in Dharwad, India, during November 29–December 2, 2023.The 94 papers included in these proceedings were carefully reviewed and selected from 174 submissions. They focus on all aspects of speech science and technology: ​automatic speech recognition; computational paralinguistics; digital signal processing; speech prosody; natural language processing; child speech processing; speech processing for medicine; industrial speech and language technology; speech technology for under-resourced languages; speech analysis and synthesis; speaker and language identification, verification and diarization.

This book provides a clear insight about IoD and its requirements, protocols, performance improvement, evaluation methods and challenging aspects, to the readers at one place. The recent enhancement of integrating drone with the Internet of things (IoT) technology promises tremendous global development. The top applications of the Internet of Drones (IoD) are expected to be infrastructure & building monitoring, fire service systems, insurance investigations, retail fulfilment, agriculture and forensic evidence collections. Conventional drone technology is enhanced with the Internet and other emerging technologies such as cloud computing, big data, artificial intelligence and communication networks which open up for enormous opportunities like ahead for on-demand service-oriented and user-friendly IoD applications. This book presents extensive knowledge about the role of IoT and emerging technology in drone networks. It focuses on major research areas of the Internet of Drones and its related applications. It provides a strong knowledge platform towards the Internet of Drones for graduates, researchers, data scientists, educators and drone hobbyists.

This book offers a timely and comprehensive snapshot of research and developments in the field of control engineering. Covering a wide range of theoretical and practical issues, the contributions describes a number of different control approaches, such adaptive control, fuzzy and neuro-fuzzy control, remote and robust control systems, real time an fault tolerant control, among others. Sensors and actuators, measurement systems, renewable energy systems, aerospace systems as well as industrial control and automation, are also comprehensively covered. Based on the proceedings of the 14th APCA International Conference on Automatic Control and Soft Computing, held on July 1-3, 2020, in Bragança, Portugal, the book offers a timely and thoroughly survey of the latest research in the field of control, and a source of inspiration for researchers and professionals worldwide.

This book provides a thorough overview of recent progress in video object tracking, allowing researchers and industrial practitioners to gain a better understanding of the most important problems and developed technologies in the area. Video tracking is a key research area in computer vision and aims to track unique objects in a given video, which are useful for various applications such as video conference, video editing, surveillance, and autonomous driving. This book begins with an introduction to the task of video object tracking, including the most common problem settings. Given the revolution of deep learning in computer vision problems, numerous new tasks, datasets, and methods have been recently proposed in the domain of video tracking. The book includes these recent results as well as benchmarks in large-scale human-centric video analysis in complex events.

This two-volume set of LNAI 14739-14740 constitute the proceedings of the 12th International Joint Conference on Automated Reasoning, IJCAR 2024, held in Nancy, France, during July 3-6, 2024. The 39 full research papers and 6 short papers presented in this book were carefully reviewed and selected from 115 submissions. The papers focus on the following topics: theorem proving and tools; SAT, SMT and Quantifier Elimination; Intuitionistic Logics and Modal Logics; Calculi, Proof Theory and Decision Procedures; and Unification, Rewriting and Computational Models. This book is open access.

This book focuses in detail on data science and data analysis and emphasizes the importance of data engineering and data management in the design of big data applications. The author uses patterns discovered in a collection of big data applications to provide design principles for hypothesis generation, integrating big data processing and management, machine learning and data mining techniques. The book proposes and explains innovative principles for interpreting hypotheses by integrating micro-explanations (those based on the explanation of analytical models and individual decisions within them) with macro-explanations (those based on applied processes and model generation). Practical case studies are used to demonstrate how hypothesis-generation and -interpretation technologies work. These are based on “social infrastructure” applications like in-bound tourism, disaster management, lunar and planetary exploration, and treatment of infectious diseases. The novel methods and technologies proposed in Hypothesis Generation and Interpretation are supported by the incorporation of historical perspectives on science and an emphasis on the origin and development of the ideas behind their design principles and patterns. Academic investigators and practitioners working on the further development and application of hypothesis generation and interpretation in big data computing, with backgrounds in data science and engineering, or the study of problem solving and scientific methods or who employ those ideas in fields like machine learning will find this book of considerable interest.

This book provides a comprehensive presentation of a recently introduced framework, named'probabilistic indexing'(PrIx), for searching text in large collections of document images and other related applications. It fosters the development of new search engines for effective information retrieval from manuscripts which, however, lack the electronic text (transcripts) that would typically be required for such search and retrieval tasks. The book is structured into 11 chapters and three appendices. The first two chapters briefly outline the necessary fundamentals and state of the art in pattern recognition, statistical decision theory, and handwritten text recognition. Chapter 3 presents approaches for indexing (as opposed to “spotting”) each region of a handwritten text image which is likely to contain a word. Next, Chapter 4 describes models adopted for handwritten text in images, namely hidden Markov models, convolutional and recurrent neural networks and language models, and provides full details of weighted finite-state transducer (WFST) concepts and methods, needed in further chapters of the book. Chapter 5 explains the set of techniques and algorithms developed to generate image probabilistic indexes which allow for fast search and retrieval of textual information in the indexed images. Chapter 6 then presents experimental evaluations of the proposed framework and algorithms on different traditional benchmark datasets and compares them with other approaches, while Chapter 7 reviews the most popular keyword-spotting approaches. Chapter 8 explains how PrIx can support classical free-text search tools, while Chapter 9 presents new methods that use PrIx not only for searching, but also to deal with text analytics and other related natural language processing and information extraction tasks. Chapter 10 shows how the proposed solutions can be used to effectively index very large collections of handwritten document images, before Chapter 11 eventually summarizes the book and suggests promising lines of future research. The appendices detail the necessary mathematical foundations for the work and presents details of the text image collections and datasets used in the experiments throughout the book. This book is written for researchers and (post-)graduate students in pattern recognition and information retrieval. It will also be of interest to people in areas like history, criminology, or psychology who need technical support to evaluate, understand or decode historical or contemporary handwritten text.

This book presents the latest achievements in the theory and practice of SEMS Group interaction by scientists from the Russian Academy of Sciences. It also discusses the development of methods for the design and simulation of SEMS Group interaction based on the principles of safety, flexibility and adaptability in behavior and intelligence and parallelism in information processing, computation and control. Recently, the task has been to ensure the functioning of robots within the framework of collective collaboration, so that they function efficiently, reliably and safely in real time. The topics covered include, but are not limited to, the following: - the planning behavior of the SEMS group;- methods and principles of designing of automatic control systems;- mathematical and computer modeling group interaction;- safety, flexibility and adaptability of the SEMS Group;- information-measuring soft- and hardware. This book is intended for students, scientists and engineers specializing in the field of smart electromechanical systems and robotics.

This book reports on innovative research and developments in automation. Spanning a wide range of disciplines, including communication engineering, power engineering, control engineering, instrumentation, signal processing and cybersecurity, it focuses on methods and findings aimed at improving the control and monitoring of industrial and manufacturing processes as well as safety. Based on the International Russian Automation Conference, held on September 4–10, 2022, in Sochi, Russia, the book provides academics and professionals with a timely overview of and extensive information on the state of the art in the field of automation and control systems and fosters new ideas and collaborations between groups in different countries.

This open access book constitutes the proceedings of the 29th International Conference on Automated Deduction, CADE 29, which took place in Rome, Italy, during July 2023. The 28 full papers and 5 short papers presented were carefully reviewed and selected from 77 submissions. CADE is the major forum for the presentation of research in all aspects of automated deduction, including foundations, applications, implementations, and practical experience. The papers are organized in the following topics: Logical foundations; theory and principles; implementation and application; ATP and AI; and system descriptions.

This book presents the concept of Control Barrier Function (CBF), which captures the evolution of safety requirements during the execution of a system and can be used to enforce safety. Safety is formalized using an emerging state-of-the-art approach based on CBFs, and many illustrative examples from autonomous driving, traffic control, and robot control are provided. Safety is central to autonomous systems since they are intended to operate with minimal or no human supervision, and a single failure could result in catastrophic results. The authors discuss how safety can be guaranteed via both theoretical and application perspectives. This presented method is computationally efficient and can be easily implemented in real-time systems that require high-frequency reactive control. In addition, the CBF approach can easily deal with nonlinear models and complex constraints used in a wide spectrum of applications, including autonomous driving, robotics, and traffic control. Withthe proliferation of autonomous systems, such as self-driving cars, mobile robots, and unmanned air vehicles, safety plays a crucial role in ensuring their widespread adoption. This book considers the integration of safety guarantees into the operation of such systems including typical safety requirements that involve collision avoidance, technological system limitations, and bounds on real-time executions. Adaptive approaches for safety are also proposed for time-varying execution bounds and noisy dynamics.