الصفحة 3
الصفحة 3
New advances in audio signal processing
In the era of digitalization, audio signal processing is gaining peculiar relevance as an automation and remote analysis means, also considering its enhancement by novel artificial intelligence (AI) techniques. This Reprint aims to offer an overview of the current developments in all fields that revolve around audio processing: from advancements in the acoustic domain to deep learning architectures for the audio-based analysis of real-world problems such as pitch detection or pathology identification.
Neurotransmitter Interactions and Cognitive Function
Cognitive function involves the participation of many different neurotransmitter systems in a variety of brain areas. The centerpiece of investigation regarding cognitive function has classically been the cholinergic system, but it has become increasingly clear that other transmitter systems interact with cholinergic systems to provide the neural basis for cognitive function. This book brings together cutting edge research to determine how the transmitter interactions form the mechanistic bases for attention, learning and memory. This research on transmitter interactions not only provides a more accurate, though complex, picture of how the brain works to provide cognitive function, it also provides important new levels of understanding about the mechanisms of cognitive dysfunction and novel avenues for therapeutic treatment. The researchers who contributed to this volume both reviewed the latest findings but also point to the directions of advancement of the field of neurotransmitter interactions and cognitive function.
Neuroscribe = نيوروسكرايب
Neuroscribe is a cutting-edge deep learning framework designed to address the complexities and inefficiencies encountered in existing frameworks like PyTorch and TensorFlow. Aimed at streamlining model development and enhancing performance across diverse hardware environments, NeuroScribe offers a lightweight and flexible solution. The framework features a robust tensor library, an auto-differentiation engine, a comprehensive neural network module, and advanced optimization algorithms. With built-in visualization tools and a user-friendly interface, NeuroScribe simplifies both beginner and advanced workflows. Its cross-platform compatibility, supported by CUDA and Metal Performance Shaders (MPS), ensures optimal performance, and in some scenarios, NeuroScribe demonstrates superior speed compared to leading frameworks. Additionally, NeuroScribe introduces unique libraries and features not found in other frameworks, further enhancing its versatility and appeal. The modular architecture and automatic system detection further enhance its adaptability, making NeuroScribe a versatile and powerful tool for deep learning practitioners.
Neuromuscular Disease : Evidence and Analysis in Clinical Neurology
Through a series of questions and answers concerning specific neuromuscular disorders, each chapter critiques the best available evidence to illustrate strengths and weaknesses of the data and make the reader aware of the quality of clinical research studies in general. Introductory chapters facilitate this learning process by elucidating the epidemiological and biostatistical issues pertinent to diagnosis, treatment, and prognosis. A broad range of disorders of the anterior horn cell, nerve roots, peripheral nerves, neuromuscular junction, and muscle are critically appraised and discussed.
Neural Networks in a Softcomputing Framework
This concise but comprehensive textbook provides a powerful and universal paradigm for information processing. Each chapter provides state-of-the-art descriptions of the important major research results of the respective neural-network methods. A range of relevant computational intelligence topics, such as fuzzy logic and evolutionary algorithms, are introduced. These are powerful tools for neural-network learning. Array signal processing problems are discussed in order to illustrate the applications of each neural-network model.
Neural networks and deep learning
Covers both classical and modern models in deep learning. The primary focus is on the theory and algorithms of deep learning. The theory and algorithms of neural networks are particularly important for understanding important concepts, so that one can understand the important design concepts of neural architectures in different applications. Why do neural networks work? When do they work better than off-the-shelf machine-learning models? When is depth useful? Why is training neural networks so hard? What are the pitfalls? The book is also rich in discussing different applications in order to give the practitioner a flavor of how neural architectures are designed for different types of problems.
Neural Networks : Methodology and Applications
Neural networks represent a powerful data processing technique that has reached maturity and broad application. When clearly understood and appropriately used, they are a mandatory component in the toolbox of any engineer who wants make the best use of the available data, in order to build models, make predictions, mine data, recognize shapes or signals, etc. Ranging from theoretical foundations to real-life applications, this book is intended to provide engineers and researchers with clear methodologies for taking advantage of neural networks in industrial, financial or banking applications, many instances of which are presented in the book. For the benefit of readers wishing to gain deeper knowledge of the topics, the book features appendices that provide theoretical details for greater insight, and algorithmic details for efficient programming and implementation. The chapters have been written by experts ands seemlessly edited to present a coherent and comprehensive, yet not redundant, practically-oriented introduction.
Neural Networks : Computational Models and Applications
Neural Networks: Computational Models and Applications covers a wealth of important theoretical and practical issues in neural networks, including the learning algorithms of feed-forward neural networks, various dynamical properties of recurrent neural networks, winner-take-all networks and their applications in broad manifolds of computational intelligence: pattern recognition, uniform approximation, constrained optimization, NP-hard problems, and image segmentation. By presenting various computational models, this book is developed to provide readers with a quick but insightful understanding of the broad and rapidly growing areas in the neural networks domain. Besides laying down fundamentals on artificial neural networks, this book also studies biologically inspired neural networks. Some typical computational models are discussed, and subsequently applied to objection recognition, scene analysis and associative memory. The studies of bio-inspired models have important implications in computer vision and robotic navigation, as well as new efficient algorithms for image analysis.
Neural Nets ; 16th Italian Workshop on Neural Nets, WIRN 2005, International workshop on natural and artificial immune systems, NAIS 2005, Vietri sul Mare, Italy, June 8-11, 2005, Revised Selected Papers
This book constitutes the thoroughly refereed postproceedings of the 16th Italian Workshop on Neural Nets, WIRN 2005, as well as the satellite International Workshop on Natural and Artificial Immune Systems, NAIS 2005, held in Vietri sul Mare, Italy in June 2005. The 41 revised papers presented together with a lecture by the winner of the Premio Caianiello award were carefully reviewed and improved during two rounds of selection and refereeing.
Neural Information Processing ; 14th International Conference, ICONIP 2007, Kitakyushu, Japan, November 13-16, 2007, Revised Selected Papers, Part II
The 228 revised full papers presented were carefully reviewed and selected from numerous ordinary paper submissions and 15 special organized sessions. The 116 papers of the first volume are organized in topical sections on computational neuroscience, learning and memory, neural network models ,supervised /unsupervised/reinforcement learning, statistical learning algorithms, optimization algorithms, novel algorithms, as well as motor control and vision. The second volume contains 112 contributions related to statistical and pattern recognition algorithms, neuromorphic hardware and implementations, robotics, data mining and knowledge discovery, real world applications, cognitive and hybrid intelligent systems, bioinformatics, neuroinformatics, brain-conputer interfaces, and novel approaches.
Neural Information Processing ; 14th International Conference, ICONIP 2007, Kitakyushu, Japan, November 13-16, 2007, Revised Selected Papers, Part I
The 228 revised full papers presented were carefully reviewed and selected from numerous ordinary paper submissions and 15 special organized sessions. The 116 papers of the first volume are organized in topical sections on computational neuroscience, learning and memory, neural network models, supervised/unsupervised/reinforcement learning, statistical learning algorithms, optimization algorithms, novel algorithms, as well as motor control and vision. The second volume contains 112 contributions related to statistical and pattern recognition algorithms, neuromorphic hardware and implementations, robotics, data mining and knowledge discovery, real world applications, cognitive and hybrid intelligent systems, bioinformatics, neuroinformatics, brain-conputer interfaces, and novel approaches.
Network Security, Firewalls, and VPNs ; 3rd ed.
Provides a unique, in-depth look at the major business challenges and threats that are introduced when an organization’s network is connected to the public Internet. Written by industry experts, this book provides a comprehensive explanation of network security basics, including how hackers access online networks and the use of Firewalls and VPNs to provide security countermeasures. Using examples and exercises, this book incorporates hands-on activities to prepare the reader to disarm threats and prepare for emerging technologies and future attacks.
Network Classification For Traffic Management : Anomaly detection, feature selection, clustering and classification
Investigates network traffic classification solutions by proposing transport-layer methods to achieve better run and operated enterprise-scale networks. With the massive increase of data and traffic on the Internet within the 5G, IoT and smart cities frameworks, current network classification and analysis techniques are falling short. Novel approaches using machine learning algorithms are needed to cope with and manage real-world network traffic, including supervised, semi-supervised, and unsupervised classification techniques. Accurate and effective classification of network traffic will lead to better quality of service and more secure and manageable networks. Investigates network traffic classification solutions by proposing transport-layer methods to achieve better run and operated enterprise-scale networks. The authors explore novel methods for enhancing network statistics at the transport layer, helping to identify optimal feature selection through a global optimization approach and providing automatic labelling for raw traffic through a SemTra framework to maintain provable privacy on information disclosure properties.
Neo-Liberalism, Globalization and Human Capital Learning : Reclaiming Education for Democratic Citizenship
Throughout the world, neoliberalism functions to decouple learning from the most important elements of civic education, transforming education into training and students into consumers. Neoliberalism, Globalization, and Human Capital Learning is an enormously important book that reveals in painstaking detail how neoliberal ideology destroys critical education. But it does much more. It also provides the insights and tools for educators to both overcome the market-based attack on critical education and address schooling as a democratic public sphere and the classroom as a laboratory for the nurturing of critical agency and social responsibility. This dynamic book should stir a public outcry among concerned citizens and educators through out the globe.
Negotiation agent
Negor is an eCommerce AI chatbot that increases sales by engaging with the user much like a salesperson when you walk into a store. This conversational eCommerce approach allows companies to overcome sales obstacles, recommend products for cross- or up-sells, and reduce support tickets all while being available 24/7. E-commerce is a way to make the customers' buying experience more seamless and interactive while helping to offer bargaining features, which are familiar in traditional stores. In addition, the Chatbot is used to negotiate the best price for the customer and the best deal for the seller.
Navigating Numeracies : Home/School Numeracy Practices
The book aims to further understanding of why some pupils have low achievement in numeracy in the school context. The authors aim to achieve this by a relatively original view that focuses on numeracy as a social practice. They report on their investigations into the meanings and uses of numeracy in school and home and community contexts, using ethnographic-style approaches, including formal and informal interviews and observations. The book will be useful for policy, practice and further research into the teaching and learning of mathematics in schools. It will therefore be of interest to policy makers, teachers and practitioners, academics and practitioners in teacher education, education researchers, and parents and community leaders.
Nature Inspired Cooperative Strategies for Optimization (NICSO 2007)
The aim for NICSO 2007 was to provide a forum were the latest ideas and state of the art research related to cooperative strategies for problem solving arising from Nature could be discussed. The contributions collected in this book were strictly peer reviewed by at least three members of the international programme committee, to whom we are indebted for their support and assistance. The topics covered by the contributions include several well established nature inspired techniques like Genetic Algorithms, Ant Colonies, Artificial Immune Systems, Evolutionary Robotics, Evolvable Systems, Membrane Computing, Quantum Computing, Software Self Assembly, Swarm Intelligence, etc.
Natural Language Processing and Text Mining
Natural Language Processing and Text Mining not only discusses applications of certain NLP techniques to certain Text Mining tasks, but also the converse, i.e., use of Text Mining to facilitate NLP. It explores a variety of real-world applications of NLP and text-mining algorithms in comprehensive detail, placing emphasis on the description of end-to-end solutions to real problems, and detailing the associated difficulties that must be resolved before the algorithm can be applied and its full benefits realized.
Natural Language Processing and Information Systems ; Vol. 3513 ; 10th International Conference on Applications of Natural Language to Information Systems, NLDB 2005, Alicante, Spain, June 15-17, Proceedings
The development and convergence of computing, telecommunications and information systems has already led to a revolution in the way that we work, communicate with each other, buy goods and use services, and even in the way that we entertain and educate ourselves.The revolution continues, and one of its results is that large volumes of information will increasingly be held in a form which is more natural for users than the data presentation formats typical of computer systems of the past. Natural language processing (NLP) is crucial in solving these problems, and language technologies will make an indispensable contribution to the success of information systems. We hope that NLDB 2005 was a modest contribution to this goal. NLDB 2005 contributed to advancing the goals and the high international standing of these conferences, largely due to its Program Committee, composed of renowned researchers in the field of natural language processing and inf- mation system engineering. Papers were reviewed by three reviewers from the Program Committee. This clearly contributed to the significant number of - pers submitted (95). Twenty-nine were accepted as regular papers, while 18 were accepted as short papers.
Natural Language Processing and Chinese Computing ; 9th CCF International Conference, NLPCC 2020, Zhengzhou, China, October 14–18, 2020, Proceedings, Part II
This two-volume set of LNAI 12340 and LNAI 12341 constitutes the refereed proceedings of the 9th CCF Conference on Natural Language Processing and Chinese Computing, NLPCC 2020, held in Zhengzhou, China, in October 2020. The 70 full papers, 30 poster papers and 14 workshop papers presented were carefully reviewed and selected from 320 submissions. They are organized in the following areas: Conversational Bot/QA; Fundamentals of NLP; Knowledge Base, Graphs and Semantic Web; Machine Learning for NLP; Machine Translation and Multilinguality; NLP Applications; Social Media and Network; Text Mining; and Trending Topics.
