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Mathematical and Computer Programming Technique...
88,99 € *
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Mathematical and Computer Programming Techniques for Computer Graphics introduces the mathematics and related computer programming techniques used in Computer Graphics. Starting with the underlying mathematical ideas, it gradually leads the reader to a sufficient understanding of the detail to be able to implement libraries and programs for 2D and 3D graphics. Using lots of code examples, the reader is encouraged to explore and experiment with data and computer programs (in the C programming language) and to master the related mathematical techniques.A simple but effective set of routines are included, organised as a library, covering both 2D and 3D graphics - taking a parallel approach to mathematical theory, and showing the reader how to incorporate it into example programs. This approach both demystifies the mathematics and demonstrates its relevance to 2D and 3D computer graphics.

Anbieter: buecher
Stand: 31.03.2020
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Cultural Transmission and Evolution (MPB-16), V...
68,95 € *
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A number of scholars have found that concepts such as mutation, selection, and random drift, which emerged from the theory of biological evolution, may also explain evolutionary phenomena in other disciplines as well. Drawing on these concepts, Professors Cavalli-Sforza and Feldman classify and systematize the various modes of transmitting "culture" and explore their consequences for cultural evolution. In the process, they develop a mathematical theory of the non-genetic transmission of cultural traits that provides a framework for future investigations in quantitative social and anthropological science.The authors use quantitative models that incorporate the various modes of transmission (for example, parent-child, peer-peer, and teacher-student), and evaluate data from sociology, archaeology, and epidemiology in terms of the models. They show that the various modes of transmission in conjunction with cultural and natural selection produce various rates of cultural evolution and various degrees of diversity within and between groups. The same framework can be used for explaining phenomena as apparently unrelated as linguistics, epidemics, social values and customs, and diffusion of innovations. The authors conclude that cultural transmission is an essential factor in the study of cultural change.

Anbieter: buecher
Stand: 31.03.2020
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Cultural Transmission and Evolution (MPB-16), V...
68,95 € *
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A number of scholars have found that concepts such as mutation, selection, and random drift, which emerged from the theory of biological evolution, may also explain evolutionary phenomena in other disciplines as well. Drawing on these concepts, Professors Cavalli-Sforza and Feldman classify and systematize the various modes of transmitting "culture" and explore their consequences for cultural evolution. In the process, they develop a mathematical theory of the non-genetic transmission of cultural traits that provides a framework for future investigations in quantitative social and anthropological science.The authors use quantitative models that incorporate the various modes of transmission (for example, parent-child, peer-peer, and teacher-student), and evaluate data from sociology, archaeology, and epidemiology in terms of the models. They show that the various modes of transmission in conjunction with cultural and natural selection produce various rates of cultural evolution and various degrees of diversity within and between groups. The same framework can be used for explaining phenomena as apparently unrelated as linguistics, epidemics, social values and customs, and diffusion of innovations. The authors conclude that cultural transmission is an essential factor in the study of cultural change.

Anbieter: buecher
Stand: 31.03.2020
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Machine Learning
45,99 € *
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Dig deep into the data with a hands-on guide to machine learning Machine Learning: Hands-On for Developers and Technical Professionals provides hands-on instruction and fully-coded working examples for the most common machine learning techniques used by developers and technical professionals. The book contains a breakdown of each ML variant, explaining how it works and how it is used within certain industries, allowing readers to incorporate the presented techniques into their own work as they follow along. A core tenant of machine learning is a strong focus on data preparation, and a full exploration of the various types of learning algorithms illustrates how the proper tools can help any developer extract information and insights from existing data. The book includes a full complement of Instructor's Materials to facilitate use in the classroom, making this resource useful for students and as a professional reference. At its core, machine learning is a mathematical, algorithm-based technology that forms the basis of historical data mining and modern big data science. Scientific analysis of big data requires a working knowledge of machine learning, which forms predictions based on known properties learned from training data. Machine Learning is an accessible, comprehensive guide for the non-mathematician, providing clear guidance that allows readers to: * Learn the languages of machine learning including Hadoop, Mahout, and Weka * Understand decision trees, Bayesian networks, and artificial neural networks * Implement Association Rule, Real Time, and Batch learning * Develop a strategic plan for safe, effective, and efficient machine learning By learning to construct a system that can learn from data, readers can increase their utility across industries. Machine learning sits at the core of deep dive data analysis and visualization, which is increasingly in demand as companies discover the goldmine hiding in their existing data. For the tech professional involved in data science, Machine Learning: Hands-On for Developers and Technical Professionals provides the skills and techniques required to dig deeper.

Anbieter: buecher
Stand: 31.03.2020
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Machine Learning
45,99 € *
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Dig deep into the data with a hands-on guide to machine learning Machine Learning: Hands-On for Developers and Technical Professionals provides hands-on instruction and fully-coded working examples for the most common machine learning techniques used by developers and technical professionals. The book contains a breakdown of each ML variant, explaining how it works and how it is used within certain industries, allowing readers to incorporate the presented techniques into their own work as they follow along. A core tenant of machine learning is a strong focus on data preparation, and a full exploration of the various types of learning algorithms illustrates how the proper tools can help any developer extract information and insights from existing data. The book includes a full complement of Instructor's Materials to facilitate use in the classroom, making this resource useful for students and as a professional reference. At its core, machine learning is a mathematical, algorithm-based technology that forms the basis of historical data mining and modern big data science. Scientific analysis of big data requires a working knowledge of machine learning, which forms predictions based on known properties learned from training data. Machine Learning is an accessible, comprehensive guide for the non-mathematician, providing clear guidance that allows readers to: * Learn the languages of machine learning including Hadoop, Mahout, and Weka * Understand decision trees, Bayesian networks, and artificial neural networks * Implement Association Rule, Real Time, and Batch learning * Develop a strategic plan for safe, effective, and efficient machine learning By learning to construct a system that can learn from data, readers can increase their utility across industries. Machine learning sits at the core of deep dive data analysis and visualization, which is increasingly in demand as companies discover the goldmine hiding in their existing data. For the tech professional involved in data science, Machine Learning: Hands-On for Developers and Technical Professionals provides the skills and techniques required to dig deeper.

Anbieter: buecher
Stand: 31.03.2020
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Coordination and Decomposition of Large-Scale P...
48,80 € *
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Modern large-scale industrial production sites consist of many production areas each being subject to a variety of technical constraints. The general objective of planning and scheduling is to ensure the on-time delivery of the end product with the lowest possible consumption of resources. In the metal industry, the melt shop and the hot rolling mill represent about 90% of the entire steel production chain energy consumption. An adequate coordination between these two production areas can allow minimizing capital investment, space requirements and power consumption by keeping the storage of the intermediate products as low as possible. Traditionally, optimal schedules of the both production sections are determined separately using a combination of mathematical programming and heuristics. Therefore an optimal schedule of the whole production chain cannot be guaranteed. On the other hand, solving the complete problem for the combined production areas leads to a combinatorial explosion of the mixed-integer linear programming (MILP) model and makes the problem intractable.A bottom-up coordination heuristics of two large-scale flexible multi-stage batch (flow shop) scheduling problems is developed on the basis of an improved Bender’s Decomposition Algorithm (Bender, 1962). An upper-level coordinator is formulated as an optimization problem based on the technical constraints of the bottleneck stages within the production sections. The obtained optimal solution of the coordinator is used as the coordination variables for the lowerlevel schedulers. The coordinator is iteratively updated using the feedback the lower-level schedulers information by adding integer and logical cuts. The location and number of bottleneck stages in the production sections might not be known a priori. An objective-oriented bottleneck definition for scheduling problems modeled as MILP is proposed. The bottleneck(s) are identified using a sensitivity analysis-based heuristics. The proposed coordination heuristics Shows improved results in terms of solution quality and computational effort when compared to other coordination approaches based on the Lagrangean Decomposition and the derivative-free optimization algorithms.The coordination heuristics is validated using actual production data collected from a steel plant. The obtained results showed a 7% increase of the total productivity, a 23% reduction of the slab yard inventory and a 9% reduction of the reheating furnace natural gas consumption when compared to an uncoordinated schedule, with no additional hardware investment. In summary, the proposed coordination approach is a general decomposition and coordination large-scale scheduling problems method that is able to systematically incorporate process knowledge.

Anbieter: Dodax
Stand: 31.03.2020
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Data- and model-based identification of biochem...
48,80 € *
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In the last decade a paradigm shift has taken place in biochemical research: while traditionally biochemical processes have often been studied on a qualitative level, more and more research now focuses on quantitative time-resolved aspects of biochemical processes. However, on a quantitative dynamic level the complexity of these processes increases significantly and the need of mathematical models arises. Once a model is fitted to experimental data it can be used to simulate and study the dynamic behavior of a given process. Furthermore, a fitted model allows it to test new experiments and hypothesis in silico before time and cost intensive real experiments need to be conducted. The interplay between biochemical experimentation and mathematical modeling - known as systems biology - is an integral part of this thesis.Identifying a predictive model starts with the formulation of an initial model, which combines a priori knowledge with new to be tested hypotheses. The initial model is refined in an iterative process of performing quantitative experiments, estimating unknown model parameters, model validation and hypothesis testing. When constructing a model, it is tempting to incorporate all known interactions between biochemical species, which results in models with a large number of unknown parameters, which subsequently have to be estimated from experimental data. However, parameter estimation can only provide valid results, if the complexity of the model and the amount and quality of data are in balance with one another. If this is the case the model is said to be identifiable for the given data. In Chapter 2 of this thesis we describe a new automatic approach to test the identifiability of model parameters. We compare our new method - the eigenvalue method - to three well established methods for identifiability testing. For three published models of signaling cascades our eigenvalue methods outperforms the other methods in terms of efficiency and effectiveness. Furthermore, we find that even when assuming abundant and noise-free measurement data, the three models are not identifiable.If a model turns out to be unidentifiable, two steps can be taken. Either additional experiments need to be conducted to increase the information content of the data, or the model has to be simplified. In Chapter 3 we follow the latter path and describe an iterative approach that combines multi-start parameter estimation, identifiability testing, sampling-based variance analysis and goodness-of-fit testing into a work flow for model simplification. We demonstrate the effectiveness of this work flow by simplifying a published model of a signaling cascade under the assumption of realistic measurements until a good fitting model with identifiable and barely varying parameters results.Finally, in Chapter 3 we demonstrate the power of a data-driven model-based approach for process identification by discriminating between different hypotheses on the function of SHP2 in the early phase of JAK-STAT signaling. Furthermore, we identify key processes that are essential for the dynamics of early pathway activation. In addition to the techniques presented in Chapters 1 and 2 we apply a brute-force method for optimal experimental design to propose new informative experiments. Using an initial and the optimal designed data, we iteratively refine our model until an identifiable and predictive model of early JAK-STAT signaling results that adequately describes the data.

Anbieter: Dodax
Stand: 31.03.2020
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Understanding Method and Purpose of Econometric...
39,90 € *
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This book provides an elementary but comprehensive introduction to econometrics without resorting to deep mathematical analysis. This book attempts to incorporate some of the developments in the theory and practice of ecnometrics. Further the book explains how econometricians use non-experimental or observational information to attract conclusions about the real world which permits us to apply economic idea to real world information. However, econometrics can evaluate the coverage program using distinctive econometric styles in differences strategies. Further, this book explains economic theories with the availability of sophisticated and user friendly statistical package, E-Views at the end.

Anbieter: Dodax
Stand: 31.03.2020
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Critical Thinking Skills in Mathematics
68,00 € *
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Thinking is the most precious cognitive ability with which man is elevated among all animal.Thinking has several kinds and each kind has several components.This book has given a clear analysis of the different kinds of thinking and focuses on the Impact of Critical Thinking Skills on achievement in Mathematics at secondary school.Critical Thinking Skills in mathematics is the ability and disposition to incorporate prior knowledge,mathematical reasoning and cognitive strategies to generalise,prove or evaluate unfamiliar mathematical situations in a classroom for reflective manner.Students must be stimulated to think critically on their own to resolve dilemmas,take stands on issues,judge propositions about knowledge or ideas at school level.Successful mathematics teaching and learning process involves practice of critical thinking skills through Mathematics.The mathematics teacher should make sincere and consistent effort in acquiring and developing abilities and skills by learners in the classrooms.

Anbieter: Dodax
Stand: 31.03.2020
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