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Nonlinear Analyses and Algorithms for Speech Processing ; International Conference on Non-Linear Speech Processing, NOLISP 2005, Barcelona, Spain, April 19-22, 2005, Revised Selected Papers
We present in this volume the collection of ?nally accepted papers of NOLISP 2005 conference. It has been the third event in a series of events related to N- linear speech processing, in the framework of the European COST action 277 “Nonlinear speech processing”. Many speci?cs of the speech signal are not well addressed by conv- tional models currently used in the ?eld of speech processing. The purpose of NOLISP is to present and discuss novel ideas, work and results related to alternative techniques for speech processing, which depart from mainstream approaches. With this intention in mind, we provide an open forum for discussion. Alt- nate approaches are appreciated, although the results achieved at present may not clearly surpass results based on state-of-the-art methods. The call for papers was launched at the beginning of 2005, addressing the following domains: 1. Non-Linear Approximation and Estimation 2. Non-Linear Oscillators and Predictors 3. Higher-Order Statistics 4. Independent Component Analysis 5. Nearest Neighbors 6. Neural Networks 7. Decision Trees 8. Non-Parametric Models 9. Dynamics of Non-Linear Systems 10. Fractal Methods 11. Chaos Modeling 12. Non-Linear Di?erential Equations 13. Others All the main ?elds of speech processing are targeted by the workshop, namely: 1. Speech Coding:Thebit rateavailablefor speechsignalsmustbe strictly l- ited in order to accommodate the constraints of the channel resource.
Middleware 2005 ; ACM/IFIP/USENIX 6th International Middleware Conference, Grenoble, France, November 28 - December 2, 2005, Proceedings
Today, middleware is a key part of almost any application. Gone are the days when middleware was only used in the IT industry for high-end applications. Rather than middleware being part of the IT world, today IT applications r- resent only one aspect of middleware. With the increase in distribution, network capacity, and widespread deployment of computing devices (in homes, auto- biles, mobile phones, etc.), middleware has surpassed the importance of operating systems as the platform where application development and deployment take place. This makes middleware very exciting as a research area but also a very challenging one since it encompasses many different concepts and techniques from a wide varietyof ?elds: networking, distributed systems, softwareengine- ing, performance analysis, computer architecture, and data management. Middleware 2005 in Grenoble, France, was the 6th edition of an increasingly successfulconference.The scope of the conference has been slowly widening with every edition to accommodate new ?elds and applications.
Metalearning : Applications to Automated Machine Learning and Data Mining
This book as one of the fastest-growing areas of research in machine learning, metalearning studies principled methods to obtain efficient models and solutions by adapting machine learning and data mining processes. This adaptation usually exploits information from past experience on other tasks and the adaptive processes can involve machine learning approaches. As a related area to metalearning and a hot topic currently, automated machine learning (AutoML) is concerned with automating the machine learning processes. Metalearning and AutoML can help AI learn to control the application of different learning methods and acquire new solutions faster without unnecessary interventions from the user.
Introducing Robotic Process Automation to Your Organization : A Guide for Business Leaders
Enables you, a novice to RPA, to successfully implement an RPA program at your company. RPA is rapidly growing in use, but is only starting to be taught at a university level. Many mid-level managers will be tasked with introducing an RPA program at their organizations as senior management learns of its efficacy, but will be unfamiliar with how to do so. This book provides you with the skills and information you need to make an informed decision. You will learn: Know the benefits of robotic process automation (RPA) / Understand the limitations of RPA / Ask the right questions to determine whether a process is a good candidate for automation / Obtain buy-in from skeptics at the senior and middle manager levels, and from line workers Be familiar with the structure required for success
Implementing machine learning for finance : A systematic approach to predictive risk and performance analysis for investment portfolios
Introduces pattern recognition and future price forecasting that exerts effects on time series analysis models, such as the Autoregressive Integrated Moving Average (ARIMA) model, Seasonal ARIMA (SARIMA) model, and Additive model, and it covers the Least Squares model and the Long Short-Term Memory (LSTM) model. It presents hidden pattern recognition and market regime prediction applying the Gaussian Hidden Markov Model. The book covers the practical application of the K-Means model in stock clustering. It establishes the practical application of the Variance-Covariance method and Simulation method (using Monte Carlo Simulation) for value at risk estimation. It also includes market direction classification using both the Logistic classifier and the Multilayer Perceptron classifier. Finally, the book presents performance and risk analysis for investment portfolios. You will: Understand the fundamentals of the financial market and algorithmic trading, as well as supervised and unsupervised learning models that are appropriate for systematic investment portfolio management / Know the concepts of feature engineering, data visualization, and hyperparameter optimization / Design, build, and test supervised and unsupervised ML and DL models / Discover seasonality, trends, and market regimes, simulating a change in the market and investment strategy problems and predicting market direction and prices / Structure and optimize an investment portfolio with preeminent asset classes and measure the / underlying risk
Image Analysis and Recognition ; Vol. 3656 ; 2ond International Conference, ICIAR 2005, Toronto, Canada, September 28-30, 2005, Proceedings
ICIAR 2005, the International Conference on Image Analysis and Recognition, was the second ICIAR conference, and was held in Toronto, Canada. ICIAR is organized annually, and alternates between Europe and North America. ICIAR 2004 was held in Porto, Portugal. The idea of o?ering these conferences came as a result of discussion between researchers in Portugal and Canada to encourage collaboration and exchange, mainly between these two countries, but also with the open participation of other countries, addressing recent advances in theory, methodology and applications. TheresponsetothecallforpapersforICIAR2005wasencouraging.From295 full papers submitted, 153 were ?nally accepted (80 oral presentations, and 73 posters). The review process was carried out by the Program Committee m- bers and other reviewers ; all are experts in various image analysis and recognition areas. Each paper was reviewed by at least two reviewers, and also checked by the conference co-chairs. The high quality of the papers in these proceedings is attributed ?rst to the authors,and second to the quality of the reviews provided by the experts. We would like to thank the authors for responding to our call, andwewholeheartedlythankthe reviewersfor theirexcellentwork,andfortheir timely response. It is this collective e?ort that resulted in the strong conference program and high-quality proceedings in your hands.
Hyperparameter tuning for machine and deep learning with R : A practical guide
Equips readers with the ability to achieve better results with significantly less time, costs, effort and resources using the methods described here. The case studies presented in this book can be run on a regular desktop or notebook computer. The content focuses on the hyperparameter tuning of ML and DL algorithms, and is divided into two main parts: theory (Part I) and application (Part II). Essential topics covered include: a survey of important model parameters; four parameter tuning studies and one extensive global parameter tuning study; statistical analysis of the performance of ML and DL methods based on severity; and a new, consensus-ranking-based way to aggregate and analyze results from multiple algorithms.
Handbook of multibiometrics
Handbook of Multibiometrics, a professional book, introduces multibiometric systems, and demonstrates the noteworthy advantages of these systems over their unimodal counterparts. In addition, this book describes in detail the various scenarios that are possible when fusing biometric evidence from multiple information sources. This comprehensive volume on multibiometric systems concisely and clearly outlines the different fusion methodologies that have been proposed by researchers to integrate multiple biometric traits.
Formal Methods for Computational Systems Biology ; 8th International School on Formal Methods for the Design of Computer, Communication, and Software Systems, SFM 2008 Bertinoro, Italy, June 2-7, 2008 Advanced Lectures
This volume presents the set of papers accompanying the lectures of the eighth International School on Formal Methods for the Design of Computer, Com- nication, and Software Systems (SFM). This series of schools addresses the use of formal methods in computer science asaprominent approach to theri gorousdesign of computer, communication, and software systems. The main aim of the SFM series is to ofer a good spectrum of current research in foundations as well as applications of formal methods, which can be of help for graduate students and young researchers who intend to approach the feld.
Distributed systems : Concurrency and consistency
Explores the gray area of distributed systems and draws a map of weak consistency criteria, identifying several families and demonstrating how these may be implemented into a programming language. Unlike their sequential counterparts, distributed systems are much more difficult to design, and are therefore prone to problems. On a large scale, usability reminiscent of sequential consistency, which would provide the same global view to all users, is very expensive or impossible to achieve.
Design and analysis of randomized algorithms : Introduction to design paradigms
Randomness is a powerful phenomenon that can be harnessed to solve various problems in all areas of computer science. Randomized algorithms are often more efficient, simpler and, surprisingly, also more reliable than their deterministic counterparts. Computing tasks exist that require billions of years of computer work when solved using the fastest known deterministic algorithms, but they can be solved using randomized algorithms in a few minutes with negligible error probabilities. Introducing the fascinating world of randomness, this book systematically teaches the main algorithm design paradigms – foiling an adversary, abundance of witnesses, fingerprinting, amplification, and random sampling, etc. – while also providing a deep insight into the nature of success in randomization. Taking sufficient time to present motivations and to develop the reader's intuition, while being rigorous throughout, this text is a very effective and efficient introduction to this exciting field.
CyberParks – The Interface Between People, Places and Technology: New Approaches and Perspectives
This book is about public open spaces, about people, and about the relationship between them and the role of technology in this relationship. It is about different approaches, methods, empirical studies, and concerns about a phenomenon that is increasingly being in the centre of sciences and strategies – the penetration of digital technologies in the urban space. As the main outcome of the CyberParks Project, this book aims at fostering the understanding about the current and future interactions of the nexus people, public spaces and technology. It addresses a wide range of challenges and multidisciplinary perspectives on emerging phenomena related to the penetration of technology in people’s lifestyles - affecting therefore the whole society, and with this, the production and use of public spaces. Cyberparks coined the term cyberpark to describe the mediated public space, that emerging type of urban spaces where nature and cybertechnologies blend together to generate hybrid experiences and enhance quality of life.
Concurrency, Graphs and Models : Essays Dedicated to Ugo Montanari on the Occasion of His 65th Birthday
The volume consists of seven sections, six of which are dedicated to the main research areas to which Ugo Montanari has contributed: Graph Transformation; Constraint and Logic Programming; Software Engineering; Concurrency; Models of Computation; and Software Verification.
Axial flux permanent magnet brushless machines
Axial Flux Permanent Magnet (AFPM) brushless machines are modern electrical machines with a lot of advantageous merits over their conventional counterparts. They are increasingly used in power generation, domestic appliances, industrial drives, electric vehicles, and marine propulsion drives and many other applications. This book deals with the analysis, construction, design, optimisation, control and applications of AFPM machines. The authors present their own research results, as well as significant research contributions made by others. This monograph will be of interest to electrical engineers and other engineers involved in the design and application of AFPM brushless machine drives. It will be an important resource for researchers and graduate students in the field of electrical machine and drives.
Avalanche Dynamics : Dynamics of Rapid Flows of Dense Granular Avalanches
Avalanches, debris, mudflows and landslides are common and natural phenomena that occur worldwide, predominantly in mountainous regions. With an emphasis on snow avalanches, this book sets out to provide a survey and discussion about the motion of avalanche-like flows from initiation to run out. An important aspect of this book is the formulation and investigation of a simple but appropriate continuum mechanical model for the realistic prediction of geophysical flows of granular material. This will help the practitioners in the field to better understand the physical input and provide them with a tool for their work. Originating from many lectures the authors have given over the years, this instructive volume brings the reader to the forefront of research - an aim also supported by an extensive bibliogrpahy of almost 500 entries.
Autotuning of PID Controllers : A Relay Feedback Approach
Recognising the benefits of improved control, the second edition of Autotuning of PID Controllers provides simple yet effective methods for improving PID controller performance. The practical issues of controller tuning are examined using numerous worked examples and case studies in association with specially written autotuning MATLAB® programs to bridge the gap between conventional tuning practice and novel autotuning methods. Autotuning of PID Controllers is more than just a monograph, it is an independent learning tool applicable to the work of academic control engineers and of their counterparts in industry looking for more effective process control and automation.
Automated machine learning : Methods, systems, challenges
This book presents the first comprehensive overview of general methods in Automated Machine Learning (AutoML), collects descriptions of existing systems based on these methods, and discusses the first series of international challenges of AutoML systems. The recent success of commercial ML applications and the rapid growth of the field has created a high demand for off-the-shelf ML methods that can be used easily and without expert knowledge. However, many of the recent machine learning successes crucially rely on human experts, who manually select appropriate ML architectures (deep learning architectures or more traditional ML workflows) and their hyperparameters. To overcome this problem, the field of AutoML targets a progressive automation of machine learning, based on principles from optimization and machine learning itself.
Advances in Case-Based Reasoning ; 6th European Conference, ECCBR 2002 Aberdeen, Scotland, UK, September 4-7, 2002 Proceedings
The papers collected in this volume were presented at the 6th European C- ference on Case-Based Reasoning (ECCBR 2002) held at The Robert Gordon University in Aberdeen, UK. This conference followed a series of very succe- ful well-established biennial European workshops held in Trento, Italy (2000), Dublin, Ireland (1998), Lausanne, Switzerland (1996), and Paris, France (1994), after the initial workshop in Kaiserslautern, Germany (1993). These meetings have a history of attracting ?rst-class European and international researchers and practitioners in the years interleaving with the biennial international co- terpart ICCBR; the 4th ICCBR Conference was held in Vancouver, Canada in 2001.
Advanced .NET Remoting
Surpassing any white papers, specialist documents and other documentationthis book features in-depth coverage of the .NET Remoting Framework. The text is organized into three main parts, and this revised, second edition features 150 pages of entirely new material! Part one includes a guide to the 1.1 framework and its capabilities in real-world applications. Part two presents .NET remoting internals, and provides real-world code and development strategies. Finally, part three looks at futuristic remoting tools and their present implementation in Visual Studio .NET 2005. You will come to see how remoting procedures will change within the new IDE and revised framework.
Abstract Computing Machines : A Lambda Calculus Perspective
The book addresses ways and means of organizing computations, highlighting the relationship between algorithms and the basic mechanisms and runtime structures necessary to execute them using machines. It completely abstracts from concrete programming languages and machine architectures, taking instead the lambda calculus as the basic programming and program execution model to design various abstract machines for its correct implementation. The emphasis is on fully normalizing machines based on full-fledged beta-reductions as essential prerequisites for symbolic computations that treat functions and variables truly as first-class objects. Their weakly normalizing counterparts are shown to be functional abstract machines that sacrifice the flavors of full beta-reductions for decidedly simpler runtime structures and improved runtime efficiency. Further downgrading of the lambda calculus leads to classical imperative machines that permit side-effecting operations on the runtime environment.
