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Modern Genome Annotation : The Biosapiens Network
An accurate description of current scientific developments in the field of bioinformatics and computational implementation is presented by research of the BioSapiens Network of Excellence. Bioinformatics is essential for annotating the structure and function of genes, proteins and the analysis of complete genomes and to molecular biology and biochemistry. Included is an overview of bioinformatics, the full spectrum of genome annotation approaches including; genome analysis and gene prediction, gene regulation analysis and expression, genome variation and QTL analysis, large scale protein annotation of function and structure, annotation and prediction of protein interactions, and the organization and annotation of molecular networks and biochemical pathways. Also covered is a technical framework to organize and represent genome data using the DAS technology and work in the annotation of two large genomic sets: HIV/HCV viral genomes and splicing alternatives potentially encoded in 1% of the human genome.
Modern Econometric Analysis : Surveys on Recent Developments
The importance of empirical economics and econometric methods has greatly in creased during the last 20 years due to the availability of better data and the improved performance of computers. In an information-driven society such as ours we need quickly to obtain complete and convincing statistical results. This is only possible if the appropriate econometric methods are applied. Traditional econometric analysis concentrates on classical methods which are far from suitable for handling actual economic problems.
Modern deep learning for tabular data : Novel approaches to common modeling problems
Synthesizes and presents novel deep learning approaches to a seemingly unlikely domain - tabular data. Whether for finance, business, security, medicine, or countless other domain, deep learning can help mine and model complex patterns in tabular data - an incredibly ubiquitous form of structured data. Part I of the book offers a rigorous overview of machine learning principles, algorithms, and implementation skills relevant to holistically modeling and manipulating tabular data. Part II studies five dominant deep learning model designs - Artificial Neural Networks, Convolutional Neural Networks, Recurrent Neural Networks, Attention and Transformers, and Tree-Rooted Networks - through both their 'default' usage and their application to tabular data. Part III compounds the power of the previously covered methods by surveying strategies and techniques to supercharge deep learning systems: autoencoders, deep data generation, meta-optimization, multi-model arrangement, and neural network interpretability.
Modern Computational Intelligence Methods for the Interpretation of Medical Images
A detailed description of up-to-date methods used for computer processing and interpretation of medical images is given. The scope of the book include images acquisition, storing with compression, processing, analysis, recognition and also its automatic understanding In introduction general overview of the computer vision methods designed for medical images is presented. Next sources of medical images are presented with their general characteristics. Both traditional (like X-ray) and very modern (like PET) sources of medical images are presented. The main emphasis is placed on such properties of medical images given by particular medical imaging methods which are important form the point of view of its computer processing, analysis and recognition.
Models, Methods and Tools for Product Service Design : The Manutelligence Project
This book summarizes research being pursued within the Manutelligence project, the goal of which is to help enterprises develop smart, social and flexible products with high value added services. Manutelligence has improved Product and Service Design by developing suitable models and methods, and connecting them through a modular, collaborative and secure ICT Platform. The use of real data collected in real time by Internet of Things (IoT) technologies underpins the design of product-service systems and makes it possible to monitor them throughout their life cycle. Available data allows costs and sustainability issues to be more accurately measured and simulated in the form of Life Cycle Cost (LCC) and Life Cycle Assessment (LCA). Analysing data from IoT systems and sharing LCC and LCA information via the ICT Platform can help to accelerate the design of product-service systems, reduce costs and better understand customer needs. Industrial partners involved in Manutelligence provide a clear overview of the project's outcomes, and demonstrate how its technological solutions can be used to improve the design of product-service systems and the management of product-service life cycles.
Models for Discrete Longitudinal Data
This book provides a comprehensive treatment on modeling approaches for non-Gaussian repeated measures, possibly subject to incompleteness. The authors consider a variety of extensions, such as models for multivariate longitudinal measurements, random-effects models with serial correlation, and mixed models with non-Gaussian random effects. They sketch the general principles for how to deal with the commonly encountered issue of incomplete longitudinal data. The authors critique frequently used methods and propose flexible and broadly valid methods instead, and conclude with key concepts of sensitivity analysis. The book shows how the different approaches can be implemented within the SAS software package. The text is organized so the reader can skip the software-oriented chapters and sections without breaking the logical flow.
Modelling, Computation and Optimization in Information Systems and Management Sciences ; 2nd International Conference MCO 2008, Metz, France - Luxembourg, September 8-10, 2008. Proceedings
This book constitutes the refereed proceedings of the Second International Conference MCO 2008, Metz, France, September 2008.The 65 revised full papers presented were carefully reviewed and selected from 160 submissions. The papers are organized in topical sections on optimization and decision making; data mining theory, systems and applications; computer vision and image processing; computer communications and networks; optimization and search techniques for security, reliability, trust.
Modelling water and nutrient dynamics in soil-crop systems : Applications of different models to common data sets - Proceedings of a workshop held 2004 in Müncheberg, Germany
This book contains articles from a workshop on "Modelling water and nutrient dynamics in crop-soil systems". Data sets from lysimeters and experimental fields of multiyear crop rotations were provided for modellers. A unique data set is provided of a 100 year long term field experiment regarding crop yield and organic carbon development under different management systems. The book includes a detailed description of data sets which can be used by modellers and the papers describe the applications of 18 different modelling approaches describing soil-crop-atmosphere interactions for water, nitrogen and carbon dynamics.
Modelling our Changing World
This book focuses on the concepts, tools and techniques needed to successfully model ever-changing time-series data. It emphasizes the need for general models to account for the complexities of the modern world and how these can be applied to a range of issues facing Earth, from modelling volcanic eruptions, carbon dioxide emissions and global temperatures, to modelling unemployment rates, wage inflation and population growth.
Modelling of Powder Die Compaction
In particular, the book presents a number of case studies that have been developed to test compaction models. Full details of the data required for input to compaction models of these case studies is given, together with a survey of the techniques used to generate the data. Details are also given of methods to produce and assess components for validation of die compaction models. The inclusion of information on case studies then provides a reference for the testing and validation of compaction models.
Modelling Distributed Systems
Process algebras are languages for the description of elementary parallel systems and are used to study the behavioural properties of distributed systems, but they often lack the ability to handle data. This textbook guides students through algebraic specification and verification of distributed systems, and some of the most prominent formal verification techniques.
Modelling and Simulation : Exploring Dynamic System Behaviour
Modelling and Simulation: Exploring Dynamic System Behaviour provides the reader with a balanced and integrated presentation of the modelling and simulation activity for both Discrete Event Dynamic Systems (DEDS) and Continuous Time Dynamic Systems (CTDS). This book presents the fundamentals necessary to understand the many important facets of the modeling and simulation methodology.
Modelling and Reasoning with Vague Concepts
This volume outlines a formal representation framework for modelling and reasoning with vague concepts in Artificial Intelligence. The new calculus has many applications, especially in automated reasoning, learning, data analysis and information fusion. This book gives a rigorous introduction to label semantics theory, illustrated with many examples, and suggests clear operational interpretations of the proposed measures. It also provides a detailed description of how the theory can be applied in data analysis and information fusion based on a range of benchmark problems.
Modelling and Development of Intelligent Systems ; 6th International Conference, MDIS 2019, Sibiu, Romania, October 3–5, 2019, Revised Selected Papers
This volume constitutes the refereed proceedings of the 6th International Conference on Modelling and Development of Intelligent Systems, MDIS 2019, held in Sibiu, Romania, in October 2019. The 13 revised full papers presented in the volume were carefully reviewed and selected from 31 submissions. The papers are organized in topical sections on adaptive systems; conceptual modelling; data mining; intelligent systems for decision support; machine learning.
Modélisation et statistique spatiales = Spatial modeling and statistics
Spatial statistics are undergoing significant development due to their use in many fields: earth sciences, environment and climatology, epidemiology, econometrics, image analysis, etc. This book presents the main spatial models used as well as their statistics for the three types of data: geostatistics (observation on a continuous domain), data on a discrete network, point data. The objective is to present in a concise but mathematically complete way the most classical models (second order and variogram; software model and Gibbs-Markov field; point processes) as well as their simulation by MCMC algorithm. Then comes the presentation of statistical tools useful for their study.
Modeling Solar Radiation at the Earth’s Surface : Recent Advances
Solar radiation data is important for a wide range of applications, e.g. in engineering, agriculture, health sector, and in many fields of the natural sciences. A few examples showing the diversity of applications may include: architecture and building design e.g. air conditioning and cooling systems; solar heating system design and use; solar power generation; weather and climate prediction models; evaporation and irrigation; calculation of water requirements for crops; monitoring plant growth and disease control; skin cancer research.
Modeling Performance Measurement : Applications and Implementation Issues in DEA
MODELING PERFORMANCE MEASUREMENT: Applications and Implementation Issues in DEA presents unified results from authors’ recent DEA research. These new DEA methodology and techniques are developed in application-driven scenarios that go beyond the identification of the best-practice frontier and seek solutions to aid managerial decisions. These new DEA developments are well-grounded in real world applications. Both DEA researchers and practitioners will find this book helpful. Theory is provided for DEA researchers for further development and possible extensions. However, it should also be mentioned that each theory is presented in practical terms with numerical examples, simple real management cases and verbal descriptions. It is felt that these concrete examples will be of value to researchers, students, and practitioners , This book also provides an easy-to-use DEA software — DEAFrontier (www.deafrontier.com). This DEA software is an Add-In for Microsoft Excel and provides a custom menu of DEA approaches The DEAFrontier does not set limit on the number of units, inputs or outputs.
Modeling Longitudinal Data
This book teaches the art and statistical science of modern longitudinal data analysis. The author emphasizes specifying, understanding, and interpreting longitudinal data models. He inspects the longitudinal data graphically, analyzes the time trend and covariates, models the covariance matrix, and then draws conclusions. The book has many figures and tables illustrating longitudinal data and numerous homework problems. The associated web site contains many longitudinal data sets, examples of computer code, and labs to re-enforce the material.
Modeling Income Distributions and Lorenz Curves
The parameterization of income distributions and Lorenz Curves is a useful approach for representing how income is distributed within a given population. It provides a way of describing how the data are generated, why the level of inequality is what it is, and what happens to the poorer sections of the population. This book brings together classic papers in the field, including Camilo Dagum’s most influential contribution, survey papers outlining the state-of-the-art of the field, and cutting-edge research contributions. While providing a thorough overview of the methodology of income distribution modeling, the book emphasizes its relevance on development economics and its importance for policy makers who design and assess poverty alleviation and income redistribution policies.
Modeling Financial Time Series with S-PLUS®
This book represents an integration of theory, methods, and examples using the S-PLUS statistical modeling language and the S+FinMetrics module to facilitate the practice of financial econometrics. This is the first book to show the power of S-PLUS for the analysis of time series data.It covers S+FinMetrics 2.0 and includes new chapters on copulas, nonlinear regime switching models, continuous-time financial models, generalized method of moments, semi-nonparametric conditional density models, and the efficient method of moments.
