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Management of deep carious lesions
Describes the challenges that deep carious lesions pose for dental practitioners, including the risk of endodontic complications and the difficulty of restorative treatment, and identifies options for overcoming these challenges on the basis of the best available evidence. The opening chapter sets the scene by discussing pathophysiology, histopathology, clinical symptomatology, and treatment thresholds. The various treatment options are then systematically presented and reviewed, covering non-selective, stepwise, and selective carious tissue removal and restoration, sealing of lesions using resin sealants or crowns, and non-restorative management approaches. In each case the current evidence with respect to the treatment is carefully evaluated. Advantages and disadvantages are explained and recommendations made on when to use the treatment in question. Illustrative clinical cases and treatment pathways for clinicians are included. This book will be of value for all practitioners who treat dental caries and carious lesions, whether in the permanent or the primary dentition. It will also be of interest to under- and postgraduate students in cariology and restorative, operative, preventive, and pediatric dentistry.
Management by Measurement : Designing Key Indicators and Performance Measurement Systems
The selection of good performance indicators is not an easy process. This monograph focuses on the designing of a Performance Measurement System (PMS), knowing that "magic rules" to identify them do not exist. Some indicators seem right and easy to measure, but have subtle, counter-productive consequences. Other indicators are more difficult to measure, but focus the enterprise on those decisions and actions that are critical to success. This book suggests how to identify indicators that achieve a balance in these effects and enhance long-term profitability.
Making Fisheries Management Work : Implementation of Policies for Sustainable Fishing
This book seeks to widen the perspective taken on implementation in fisheries management. The cases presented in this volume addresses legal, administrative, and political challenges regarding implementation of resource conservation policies. The book addresses problems relating to goal achievement, but also causes of deliberate change of political goals during implementation. Fisheries management systems are embedded in inert social structures and natural conditions that vary among different states. Consequently, the book takes a historical and comparative approach, describing the historical developments of national implementation systems and the conditions that shaped their development. It thus seeks to explain why national fisheries management systems have evolved differently, focusing on Norwegian, Faeroese, and EU/Danish management systems. The descriptive and explanatory outlines are accompanied by qualitative assessments of the systems effectiveness as tools for collective action.
Magnetohydrodynamics : Historical Evolution and Trends
Magnetohydrodynamics (MHD) studies the interaction between the flow of an electrically conducting fluid and magnetic fields. It involves such diverse topics as the evolution and dynamics of astrophysical objects, thermonuclear fusion, metallurgy and semiconductor crystal growth, etc. Although the first ideas in magnetohydrodynamics appeared at the beginning of the last century, the "explosion" in theoretical and experimental studies occurred in the 1950s-60s. This state-of-the-art book aims at revising the evolution of ideas in various branches of magnetohydrodynamics (astrophysics, earth and solar dynamos, plasmas, MHD turbulence and liquid metals) and reviews current trends and challenges.
Magnetic Functions Beyond the Spin-Hamiltonian
Using the spin-Hamiltonian formalism the magnetic parameters are introduced through the components of the Lambda-tensor involving only the matrix elements of the angular momentum operator. The energy levels for a variety of spins are generated and the modeling of the magnetization, the magnetic susceptibility and the heat capacity is done. Theoretical formulae necessary in performing the energy level calculations for a multi-term system are prepared with the help of the irreducible tensor operator approach. The goal of the programming lies in the fact that the entire relevant matrix elements (electron repulsion, crystal field, spin-orbit interaction, orbital-Zeeman, and spin-Zeeman operators) are evaluated in the basis set of free-atom terms. The modeling of the zero-field splitting is done at three levels of sophistication. The spin-Hamiltonian formalism offers simple formulae for the magnetic parameters by evaluating the matrix elements of the angular momentum operator in the basis set of the crystal-field terms. The magnetic functions for dn complexes are modeled for a wide range of the crystal-field strengths.
Magnesium
Until recently the physiological role of magnesium was essentially ignored. However, with the development of new technologies to measure the intracellular free concentration of magnesium ([Mg2+]i), the biologically important fraction, there has been an explosion of interest in the molecular, biochemical, physiological and pharmacological functions of magnesium. In addition improved methods for assessing magnesium status in the clinic have contributed to the further understanding of magnesium regulation in health and disease...
Machine Learning Techniques for Multimedia : Case Studies on Organization and Retrieval
This book provides a comprehensive coverage of the most important machine learning techniques used and their application in this domain. Arising from the EU MUSCLE network, a program that drew together multidisciplinary teams with expertise in machine learning, pattern recognition, artificial intelligence, and image, video, text and crossmedia processing, the book first introduces the machine learning principles and techniques that are applied in multimedia data processing and analysis. The second part focuses on multimedia data processing applications, with chapters examining specific machine learning issues in domains .
Machine Learning in Computer Vision
The goal of this book is to address the use of several important machine learning techniques into computer vision applications. An innovative combination of computer vision and machine learning techniques has the promise of advancing the field of computer vision, which contributes to better understanding of complex real-world applications. The effective usage of machine learning technology in real-world computer vision problems requires understanding the domain of application, abstraction of a learning problem from a given computer vision task, and the selection of appropriate representations for the learnable (input) and learned (internal) entities of the system. In this book, we address all these important aspects from a new perspective: that the key element in the current computer revolution is the use of machine learning to capture the variations in visual appearance, rather than having the designer of the model accomplish this. As a bonus, models learned from large datasets are likely to be more robust and more realistic than the brittle all-design models.
Machine learning for neurodegenerative disorders : advancements and applications
Explores the application of machine learning to the understanding, early diagnosis, and management of neurodegenerative disorders. With a specific focus on its role in ongoing clinical trials, the book covers essential topics such as data collection, pre-processing, feature extraction, model development, and validation techniques. It delves into the applications of neuroimaging techniques like magnetic resonance imaging (MRI), computed tomography (CT), and positron emission tomography (PET) in the diagnosis and understanding of neurodegenerative disorders. Additionally, the book examines various machine-learning algorithms employed for biomarker discovery in neurodegenerative disorders. It highlights the role of neuroinformatics and big data analysis in advancing the understanding and management of neurodegenerative disorders. Furthermore, the book reviews future prospects and presents the ethical considerations and regulatory challenges associated with implementing machine learning approaches in the diagnosis, treatment, and prevention of neurodegenerative disorders.
Machine Learning for Multimodal Interaction ; Vol.4299 ; 3rd International Workshop, MLMI 2006, Bethesda, MD, USA, May 1-4, 2006, Revised Selected Papers
This book contains a selection of refereed papers presented at the 3rd Workshop on Machine Learning for Multimodal Interaction (MLMI 2006), held in Bethesda MD, USA during May 1–4, 2006.
Machine Learning for Multimodal Interaction ; Vol.3869 ; 2nd International Workshop, MLMI 2005, Edinburgh, UK, July 11-13, 2005, Revised Selected Papers
The papers are organized in topical sections on multimodal processing, HCI and applications, discourse and dialogue, emotion, visual processing, speech and audio processing, and NIST meeting recognition evaluation
Machine Learning for Multimodal Interaction ; Vol.3361 : 1st International Workshop, MLMI 2004, Martigny, Switzerland, June 21-23, 2004, Revised Selected Papers
his book contains a selection of refereed papers presented at the 1st Wo- shop on Machine Learning for Multimodal Interaction (MLMI 2004), held at the “Centre du Parc,” Martigny, Switzerland, during June 21–23, 2004. The workshop was organized and sponsored jointly by three European projects, – AMI, Augmented Multiparty Interaction, http://www.amiproject.org – PASCAL, Pattern Analysis, Statistical Modeling and Computational Learning, http://www.pascal-network.org – M4, Multi-modal Meeting Manager, http://www.m4project.org as well as the Swiss National Centre of Competence in Research (NCCR): – IM2: Interactive Multimodal Information Management, http://www.im2.ch MLMI 2004 was thus sponsored by the European Commission and the Swiss National Science Foundation.
Machine Learning for Multimodal Interaction ; 5th International Workshop, MLMI 2008, Utrecht, The Netherlands, September 8-10, 2008. Proceedings
The 12 revised full papers and 15 revised poster papers presented together with 5 papers of a special session on user requirements and evaluation of multimodal meeting browsers/assistants were carefully reviewed and selected from 47 submissions. The papers cover a wide range of topics related to human-human communication modeling and processing, as well as to human-computer interaction, using several communication modalities. Special focus is given to the analysis of non-verbal communication cues and social signal processing, the analysis of communicative content, audio-visual scene analysis, speech processing, interactive systems and applications.
Machine Learning for Multimodal Interaction ; 4th International Workshop, MLMI 2007, Brno, Czech Republic, June 28-30, 2007, Revised Selected Papers
This book contains a selection of revised papers from the 4th Workshop on Machine Learning for Multimodal Interaction (MLMI 2007), which took place in Brno, Czech Republic, during June 28 30, 2007. As in the previous editions of the MLMI series, the 26 chapters of this book cover a large area of topics, from multimodal processing and human computer interaction to video, audio, speech and language processing. The application of machine learning techniques to problems arising in these felds and the design and analysis of software
Machine Learning and Knowledge Extraction ; 5th IFIP TC 5, TC 12, WG 8.4, WG 8.9, WG 12.9 International Cross-Domain Conference, CD-MAKE 2021, Virtual Event, August 17–20, 2021, Proceedings
Constitutes the refereed proceedings of the 5th IFIP TC 5, TC 12, WG 8.4, WG 8.9, WG 12.9 International Cross-Domain Conference, CD-MAKE 2021, held in virtually in August 2021. The 20 full papers and 2 short papers presented were carefully reviewed and selected from 48 submissions. The cross-domain integration and appraisal of different fields provides an atmosphere to foster different perspectives and opinions; it will offer a platform for novel ideas and a fresh look on the methodologies to put these ideas into business for the benefit of humanity.
Machine learning and data mining for sports analytics ; 7th international workshop, MLSA 2020, Co-located with ECML/PKDD 2020, Ghent, Belgium, September 14–18, 2020, Proceedings
Constitutes the refereed post-conference proceedings of the 7th International Workshop on Machine Learning and Data Mining for Sports Analytics, MLSA 2020, colocated with ECML/PKDD 2020, in Ghent, Belgium, in September 2020. The 11 papers presented were carefully reviewed and selected from 22 submissions. The papers present a variety of topics within the area of sports analytics, including tactical analysis, outcome predictions, data acquisition, performance optimization, and player evaluation.
Lymphocyte Signal Transduction
Signal transduction through leukocyte receptors involves a variety of signaling molecules including kinases, phosphatases, adaptor proteins, small GTPases GTP exchange factors, membrane phospholipids as well as others. These signal transducers, regulated by inter- and intra-molecular interactions, as well as by various post-translational modifications, lead to the activation of transcription factors that mediate cellular differentiation and growth, effector cell functions, and apoptotic cell death. Several investigators from various parts of the world convened at the 3rd Lymphocyte Signal Transduction Workshop in Crete, Greece from May 27 to June 1, 2005 to discuss their most recent findings in leukocyte signaling. This volume represents a collection of topics discussed during the conference.
Low-cost methods for molecular characterization of mutant plants : Tissue desiccation, DNA extraction and mutation discovery : Protocols
Offers low-cost and rapid molecular assays for the characterization of mutant plant germplasm. Detailed protocols are provided for the desiccation of plant tissues; the extraction of high-quality DNA for downstream applications; the extraction of single-strand-specific nucleases for single nucleotide polymorphism; and small insertion/deletion discovery using standard agarose gel electrophoresis. The methods described can be applied in any laboratory equipped for basic molecular biology and do away with the need for expensive freezers and toxic organic compounds.
Low Power Uwb Cmos Radar Sensors
Low Power UWB CMOS Radar Sensors deals with the problem of designing low cost CMOS radar sensors. The radar sensor uses UWB signals in order to obtain a reasonable target separation capability, while maintaining a maximum signal frequency below 2 GHz. This maximum frequency value is well within the reach of current CMOS technologies. The use of UWB signals means that most of the methodologies used in the design of circuits and systems that process narrow band signals, can no longer be applied. Low Power UWB CMOS Radar Sensors provides an analysis between the interaction of UWB signals, the antennas and the processing circuits.
Logical aspects of computational linguistics ; 4th International Conference, LACL 2001, Le Croisic, France, June 27-29, 2001, Proceedings
Structural Equations in Language Learning.- On the Distinction between Model-Theoretic and Generative-Enumerative Syntactic Frameworks.- Contributed Papers.- A Formal Definition of Bottom-Up Embedded Push-Down Automata and Their Tabulation Technique.- An Algebraic Approach to French Sentence Structure.- Deductive Parsing of Visual Languages.- Lambek Grammars Based on Pregroups.- An Algebraic Analysis of Clitic Pronouns in Italian.- Consistent Identification in the Limit of Any of the Classes k-Valued Is NP-hard.- Polarized Non-projective Dependency Grammars.- On Mixing Deduction and Substitution in Lambek Categorial Grammars.- A Framework for the Hyperintensional Semantics of Natural Language with Two Implementations.- A Characterization of Minimalist Languages.- of Speech Tagging from a Logical Point of View.- Transforming Linear Context-Free Rewriting Systems into Minimalist Grammars.- Recognizing Head Movement.- Combinators for Paraconsistent Attitudes.- Combining Syntax and Pragmatic Knowledge for the Understanding of Spontaneous Spoken Sentences.- Atomicity of Some Categorially Polyvalent Modifiers.
