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Auditory signal processing : Physiology, psychoacoustics, and models
The volume includes a total of 62 invited papers, organized into 12 broad thematic areas: cochlear signal processing; brainstem signal processing; pitch; frequency modulation; streaming; amplitude modulation; responses to complex sounds; speech; comodulation masking release; binaural hearing; temporal coding; and plasticity
Artificial intelligence in drug design
Looks at applications of artificial intelligence (AI), machine learning (ML), and deep learning (DL) in drug design. The chapters in this book describe how AI/ML/DL approaches can be applied to accelerate and revolutionize traditional drug design approaches such as: structure- and ligand-based, augmented and multi-objective de novo drug design, SAR and big data analysis, prediction of binding/activity, ADMET, pharmacokinetics and drug-target residence time, precision medicine and selection of favorable chemical synthetic routes. How broadly are these approaches applied and where do they maximally impact productivity today and potentially in the near future.
Application of microbes in environmental and microbial biotechnology
Discusses the innovative approaches and investigation strategies, as well as provides a broad spectrum of the cutting-edge research on the processing, properties and technological developments of microbial products and their applications. Microbes finds very important applications in our lives including industries and food processing. They are widely used in the fermentation of beverages, processing of dairy products, production of pharmaceuticals, chemicals, enzymes, proteins and biomaterials / conversion of biomass into fuel, fuel cell technology, health and environmental sectors. Some of these products are produced commercially, while others are potentially valuable in biotechnology. Microorganisms are considered invaluable in research as model organisms. This is a useful compilation for students and researchers in microbiology, biotechnology and chemical industries.
An introduction to generative drug discovery
Describes the state‑of‑the‑art methods and applications for de novo design of drug candidates using generative chemistry models as well as the ethical aspects of this technology. It will provide a foundation for those new to the field as well as those that may already have some experience of its utility. With contributions from scientists in both academia and industry ‘Introduction to Generative Drug Discovery’ may represent one of the earliest if not the first book to focus on this topic.
AI in disease detection : Advancements and applications
Discusses the integration of artificial intelligence to revolutionize disease detection approaches, with case studies of AI in disease detection as well as insight into the opportunities and challenges of AI in healthcare as a whole. The book explores a wide range of individual AI components such as computer vision, natural language processing, and machine learning as well as the development and implementation of AI systems for efficient practices in data collection, model training, and clinical validation.
Advances in cognitive neurodynamics ICCN 2007; Proceedings of the International conference on cognitive neurodynamics - 2007
Contains the Proceedings of the 1st International Conference on Cognitive Neurodynamics held in Shanghai, November 17-21, 2007. The participants were treated to an exciting and stimulating conference that left everyone with an enthusiastic vision for the future of the field. The latest important progress was covered by 13 mini-symposia including: Models of Mental Disorders; Cognitive Machines; Dynamics in learning and memory; Central nervous system synchronization; Neuroinformatics; Cognitive Computational Modeling of Human Language Processing; Cognitive Neurodynamics of Attention; Bottom-Up and Top-Down; Brain Networks; From Anatomy to Dynamics; Translational Cognitive Neuroimaging; K-sets; Theory and Applications; Advanced Signal Processing Techniques for Brain Data Analysis; Visual cortex: information processing and dynamics; Dynamics of Firing Patterns and Synchronization in Neuronal Systems.
Abeta Peptide and Alzheimers Disease : Celebrating a Century of Research
Abeta Peptide and Alzheimer’s Disease summarizes current knowledge of beta-amyloid peptide (Aß) and its role as the major culprit in Alzheimer’s Disease (AD), shown by recent advances in genetics and brain biochemistry.the book covers fundamental biochemical studies on the Aß peptide, the genetic impact on Aß expression and processing, and various AD therapeutic strategies that target Aß. Although specifically focusing on Aß and AD, there is also some discussion on the similarity and differences of this peptide and AD with other amyloidogenic diseases.
A Changing World : Challenges for Landscape Research
Written primarily for researchers and advanced students in environmental and social sciences, this latest book in Springer’s Landscape Series looks at some of the emerging fields and new challenges in landscape research. These include: the role of value systems in perceiving, appreciating, and managing landscapes the ‘space’ and ‘place’ concept in landscape research GIS and remote sensing techniques for gathering and processing spatially and temporally explicit land cover, vegetation, and land use data methods of landscape history landscape genetics and genetic methods to test landscape connectivity and dispersal of plant and animal species
Mathematical Linguistics
Mathematical Linguistics introduces the mathematical foundations of linguistics to computer scientists, engineers, and mathematicians interested in natural language processing. The book presents linguistics as a cumulative body of knowledge from the ground up, with no prior knowledge of linguistics being assumed, covering more than the average two-semester introductory course in linguistics.This comprehensive, reader-friendly volume offers readers a high-level orientation, discussing the foundations of the field and presenting both the classical work and the most recent results. It covers an extremely rich array of topics including not only syntax and semantics but also phonology and morphology, probabilistic approaches, complexity, learnability, and the analysis of speech and handwriting.
Markov Models for Pattern Recognition : From Theory to Applications
Describes the underlying theoretical concepts - covering Hidden Markov models and Markov chain models - and presents the techniques and algorithmic solutions essential to creating real world applications. The actual use of Markov models in their three main application areas - namely speech recognition, handwriting recognition, and biological sequence analysis - is presented with examples of successful systems.
Machine-learning-assisted intelligent processing and optimization of complex systems
Focuses on the most recent developments in intelligent optimization methods and their applications in various test cases. The reprint covers various topics, including distributed multiagent modeling, metaheuristic algorithms, multisource data fusion, mobile computing and mobile sensing, machine learning-based intelligent processing for modeling complex manufacturing systems, and data-driven intelligent modeling
Machine Learning Refined : Foundations, Algorithms, and Applications
Provides students with the fundamental knowledge and practical tools needed to conduct research and build data-driven products. The authors prioritize geometric intuition and algorithmic thinking, and include detail on all the essential mathematical prerequisites, to offer a fresh and accessible way to learn. Practical applications are emphasized, with examples from disciplines including computer vision, natural language processing, economics, neuroscience, recommender systems, physics, and biology.
Machine learning for cyber-physical systems: selected papers from the international conference ML4CPS 2023
Contains selected papers from the international conference ML4CPS – Machine Learning for Cyber-Physical Systems, which was held in Hamburg (Germany), from 29 to 31 March 2023. Cyber-physical systems are adaptive and learning: they analyze their environment and, based on observations, learn patterns, associations and predictive models. Typical applications are condition monitoring, predictive maintenance, image processing and diagnostics. Machine learning is the key technology for these developments.
Machine learning for biomedical application
Biomedicine is a multidisciplinary branch of medical science that consists of many scientific disciplines, e.g., biology, biotechnology, bioinformatics, and genetics; moreover, it covers various medical specialties. In recent years, this field of science has developed rapidly. This means that a large amount of data has been generated, due to (among other reasons) the processing, analysis, and recognition of a wide range of biomedical signals and images obtained through increasingly advanced medical imaging devices. The analysis of these data requires the use of advanced IT methods, which include those related to the use of artificial intelligence, and in particular machine learning. It is a summary of the Special Issue “Machine Learning for Biomedical Application”, briefly outlining selected applications of machine learning in the processing, analysis, and recognition of biomedical data, mostly regarding biosignals and medical images.
Machine Learning for Audio, Image and Video Analysis : Theory and Applications
The book is organized in four parts: The first focuses on technical aspects, basic mathematical notions and elementary machine learning techniques. The second provides an extensive survey of most relevant machine learning techniques for media processing, while the third part focuses on applications and shows how techniques are applied in actual problems. The fourth part contains detailed appendices that provide notions about the main mathematical instruments used throughout the text
Machine learning approach for cloud data analytics in IoT
Covers the multidimensional perspective of machine learning through the perspective of cloud computing and Internet of Things ranging from fundamentals to advanced applications. Elucidates some of the best practices and their respective outcomes in cloud and fog computing environments. It focuses on all the various research issues related to big data storage and analysis, large-scale data processing, knowledge discovery and knowledge management, computational intelligence, data security and privacy, data representation and visualization, and data analytics. The featured technologies presented in the book optimizes various industry processes using business intelligence in engineering and technology. Light is also shed on cloud-based embedded software development practices to integrate complex machines so as to increase productivity and reduce operational costs. The various practices of data science and analytics which are used in all sectors to understand big data and analyze massive data patterns are also detailed in the book.
Machine Learning and Robot Perception
Presents some of the most recent research results in the area of machine learning and robot perception. The chapters represent new ways of solving real-world problems. This book will appeal to researchers, senior undergraduate/postgraduate students, application engineers and scientists.
Machine Learning and Cognitive Computing for Mobile Communications and Wireless Networks
Communication and network technology has witnessed recent rapid development and numerous information services and applications have been developed globally. These technologies have high impact on society and the way people are leading their lives. The advancement in technology has undoubtedly improved the quality of service and user experience yet a lot needs to be still done. Some areas that still need improvement include seamless wide-area coverage, high-capacity hot-spots, low-power massive-connections, low-latency and high-reliability and so on. Thus, it is highly desirable to develop smart technologies for communication to improve the overall services and management of wireless communication. Machine learning and cognitive computing have converged to give some groundbreaking solutions for smart machines. With these two technologies coming together, the machines can acquire the ability to reason similar to the human brain. The research area of machine learning and cognitive computing cover many fields like psychology, biology, signal processing, physics, information theory, mathematics, and statistics that can be used effectively for topology management. Therefore, the utilization of machine learning techniques like data analytics and cognitive power will lead to better performance of communication and wireless systems.
Machine Learning Algorithms Using Python Programming
Presents the key concepts of Machine Learning which includes Python concepts and Interpreter, Foundation of Machine Learning, Data Pre-processing, Supervised Machine Learning, Unsupervised Machine Learning, Reinforcement Learning, Kernel Machine, Design and analysis of Machine Learning experiment and Data visualization. The theoretical concepts along with coding implementation are covered. This book aims to pursue a middle ground between a theoretical textbook and one that focuses on applications. The book concentrates on the important ideas in machine learning.
Machine Learning : The Basics
Approaches ML as the computational implementation of the scientific principle. This principle consists of continuously adapting a model of a given data-generating phenomenon by minimizing some form of loss incurred by its predictions. Trains readers to break down various ML applications and methods in terms of data, model, and loss, thus helping them to choose from the vast range of ready-made ML methods.
