Search Results - (((((((ant OR antti) OR semantic) OR arts) OR cantor) OR anne) OR maarten) OR mantis) algorithms.

DEEP LEARNING FOR HEALTHCARE DECISION MAKING.

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Machine learning for dummies by Mueller, John, 1958-, Massaron, Luca

Table of Contents: “…Discovering the fad uses of AI and machine learning -- Considering the true uses of AI and machine learning -- Being useful -- being mundane -- Considering the Relationship between AI and Machine Learning -- Considering AI and Machine Learning Specifications -- Defining the Divide between Art and Engineering -- Chapter 2 Learning in the Age of Big Data -- Defining Big Data -- Considering the Sources of Big Data -- Building a new data source -- Using existing data sources -- Locating test data sources -- Specifying the Role of Statistics in Machine Learning -- Understanding the Role of Algorithms.…”
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Optimisation in Economic Analysis. by Mills, Gordon

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Figuring it out : entertaining encounters with everyday math by Crato, Nuno

Table of Contents: “…. -- The dinner table algorithm -- Cutting the Christmas cake -- Oranges and computers -- When two and two don't make four -- Getting more intelligent every day -- The other lane always goes faster -- Shoelaces and neckties -- Number puzzles -- Tossing a coin -- The switch -- Eubulides, the heap and the Euro -- The Earth is Round. -- How GPS works -- Gear wheels -- February 29 -- The Nonius scale -- Pedro Nunes' map -- Lighthouse geometry -- Asteroids and least squares -- The useful man and the genius -- Secret Affairs. -- Alice and Bob -- Inviolate cybersecrets -- Quantum cryptography -- The FBI wavelet -- The enigma machine -- Art and Geometry. -- The Vitruvian man -- The golden number -- The geometry of A4 paper sizes -- The strange worlds of Escher -- Escher and the Möbius strip -- Picasso, Einstein and the fourth dimension -- Pollock's fractals -- Voronoi diagrams -- The Platonic solids -- Pythagorean mosquitoes -- The most beautiful of all -- Mathematical Objects. -- The power of math -- Doubts in the realm of certainty -- When chance enhances reliability -- The difficulty of chance -- Conjectures and proofs -- Mr. …”
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Large-scale computing techniques for complex system simulations by Dubitzky, Werner

Table of Contents: “…Front Matter -- State-of-the-Art Technologies for Large-Scale Computing / Florian Feldhaus, Stefan Freitag, Chaker El Amrani -- The e-Infrastructure Ecosystem: Providing Local Support to Global Science / Erwin Laure, Aʻke Edlund -- Accelerated Many-Core GPU Computing for Physics and Astrophysics on Three Continents / Rainer Spurzem, Peter Berczik, Ingo Berentzen, Wei Ge, Xiaowei Wang, Hsi-yu Schive, Keigo Nitadori, Tsuyoshi Hamada, Još Fiestas -- An Overview of the SimWorld Agent-Based Grid Experimentation System / Matthias Scheutz, Jack J Harris -- Repast HPC: A Platform for Large-Scale Agent-Based Modeling / Nicholson Collier, Michael North -- Building and Running Collaborative Distributed Multiscale Applications / Katarzyna Rycerz, Marian Bubak -- Large-Scale Data-Intensive Computing / Mark Parsons -- A Topology-Aware Evolutionary Algorithm for Reverse-Engineering Gene Regulatory Networks / Martin Swain, Camille Coti, Johannes Mandel, Werner Dubitzky -- QosCosGrid e-Science Infrastructure for Large-Scale Complex System Simulations / Krzysztof Kurowski, Bartosz Bosak, Piotr Grabowski, Mariusz Mamonski, Tomasz Piontek, George Kampis, L̀szl̤ Gulỳs, Camille Coti, Thomas Herault, Franck Cappello -- Glossary -- Index -- Wiley Series on Parallel and Distributed Computing.…”
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Regression Analysis with Python. by Massaron, Luca, Boschetti, Alberto

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Quite right : the story of mathematics, measurement, and money by Biggs, Norman

Table of Contents: “…4. The Age of AlgorithmsHow to do arithmetic; Advances in arithmetic; The uses of arithmetic; The north-west frontier; The art of al-jabr; The origins of symbolic algebra; 5. …”
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Mathematical programming solver based on local search

Table of Contents: “…LocalSolver programming language; 2.4. The core algorithmic ideas; 2.4.1. Effective local search moves; 2.4.2. …”
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Wireless Sensor and Ad Hoc Networks Under Diversified Network Scenarios. by Sarkar, Subir Kumar

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Deep Learning with TensorFlow : Explore neural networks and build intelligent systems with Python, 2nd Edition. by Zaccone, Giancarlo

Table of Contents: “…; Artificial neural networks; The biological neurons; The artificial neuron; How does an ANN learn?; ANNs and the backpropagation algorithm; Weight optimization; Stochastic gradient descent; Neural network architectures; Deep Neural Networks (DNNs); Multilayer perceptron; Deep Belief Networks (DBNs).…”
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Advances in face image analysis : theory and applications. by Fadi Dornaika

Table of Contents: “…3D FACE ALIGNMENTFACE RECOGNITION; CONCLUDING REMARKS; CONFLICT OF INTEREST; ACKNOWLEDGEMENTS; REFERENCES; Model-Less 3D Face Pose Estimation ; INTRODUCTION; STATE OF THE ART; THE MACHINE LEARNING METHODOLOGY; Locality Preserving Projections; LPP Algorithm; Supervised Locality Preserving Projections; LABEL-SENSITIVE LOCALITY PRESERVING PROJECTION; Presetting:; Algorithm:; PROPOSED APPROACH: SPARSE GRAPH BASED LSLPP; EXPERIMENTAL RESULTS; CONCLUSION; NOTES; CONFLICT OF INTEREST; ACKNOWLEDGEMENTS; REFERENCES; Efficient Deformable 3D Face Model Fitting to Monocular Images ; INTRODUCTION.…”
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Daylighting in Architecture : a European Reference Book. by Baker, Nick V.

Table of Contents: “…Cover; Title Page; Copyright Page; Acknowledgments; Preface; Table of Contents; Introduction; Chapter 1 Daylighting Evolution And Analysis; The Pre-industrial Period; The Industrial Revolution; Daylighting in Art Galleries; Daylighting in UK Schools; The Analytical Approach; Design Tools; The Post-fluorescent Era; European Research and Development; Chapter 2 Light and Human Requirements; Design Constraints ; Design Response ; Visual Comfort Requirements ; Chapter 3 Daylight Data ; Review of Sky Models ; Luminous Efficacy of Daylight ; Results of Measurements ; Sky Type Probabilities.…”
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Smoothing of multivariate data : density estimation and visualization by Klemelä, Jussi, 1965-

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Establishing Sufficient Temporal Independence Efficiently : a Monitoring Approach. by Neukirchner, Moritz

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In pursuit of the traveling salesman : mathematics at the limits of computation by Cook, William, 1957-

Table of Contents: “…General-purpose model -- The simplex algorithm -- Two for the price of one: LP duality -- The degree LP relaxation of the TSP -- Eliminating subtours -- A perfect relaxation -- Integer programming -- Operations research -- Cutting planes. …”
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Spam : a Shadow History of the Internet by Brunton, Finn, 1980-

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Complexity : a guided tour by Mitchell, Melanie (Computer scientist)

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Dermatologic principles and practice in oncology : conditions of the skin, hair, and nails in cancer patients

Table of Contents: “…Borovicka, Jennifer R.S. Gordon, Ann Cameron Haley, Nicole E. Larson and Dennis P. …”
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Computational ecology : artificial neural networks and their applications by Zhang, Wenjun

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Design reuse in product development modeling, analysis and optimization by Ong, S. K., 1969-

Table of Contents: “…Cover -- Contents -- Preface -- 1 Introduction -- 1.1 Design Reuse What and Why -- 1.1.1 Types of design reuse -- 1.1.2 The importance of design reuse -- 1.2 Product Conceptual Design -- 1.2.1 Product family design -- 1.3 Major Issues in Design Reuse -- 1.3.1 Design reuse process -- 1.3.2 Product information modeling -- 1.3.3 Product information analysis -- 1.3.4 Design synthesis -- 1.3.5 Solution evaluation -- 1.4 Engineering Design Reuse Applications -- 1.4.1 Design reuse in software engineering -- 1.4.2 Design reuse in mechanical and electro-mechanical engineering -- 1.4.3 Design reuse in manufacturing -- 1.5 Barriers to Design Reuse -- 1.6 Summary -- 2 Design Reuse Systems and Enabling Tools -- 2.1 Engineering Design Reuse Approaches -- 2.1.1 Case-based reasoning -- 2.1.2 Catalog-based design -- 2.1.3 Modular design -- 2.1.4 Adaptable design -- 2.1.5 Expert systems -- 2.1.6 Innovative design using TRIZ -- 2.2 Reasoning in Design Reuse -- 2.2.1 Machine learning -- 2.2.2 Data mining -- 2.2.3 Design structure matrix -- 2.2.4 Artificial neural networks -- 2.2.5 Genetic algorithms -- 2.2.6 Agent-based method -- 2.3 Summary -- 3 Product Information Modeling -- 3.1 Data, Information and Knowledge -- 3.2 Information Modeling State-Of-The-Art Review -- 3.2.1 Content of information model -- 3.2.2 Modeling languages -- 3.2.3 Taxonomies -- 3.2.4 Database system and web-based environment -- 3.3 Function-Based Product Information Model -- 3.3.1 A multiple facet product information model -- 3.3.2 Representation of function using key element vector -- 3.3.3 Function taxonomies -- 3.3.4 An illustrative example -- 3.4 Summary -- 4 Design of Product Platform -- 4.1 Role of Product Platform -- 4.2 Product Platform and Product Family Design -- 4.2.1 A top-down perspective -- 4.2.2 A bottom-up perspective -- 4.3 Computational Tools for Product Architecture Building -- 4.3.1 QFD-based approach -- 4.3.2 DSM-based approach -- 4.3.3 Heuristic and quantitative approaches -- 4.4 Product Architecture Building Using Self-Organizing Map -- 4.4.1 Introduction of SOM -- 4.4.2 Function clustering based on SOM -- 4.4.3 A case study -- 4.4.4 Evaluation of the SOM method -- 4.5 Other Relevant Issues in Product Platform Design -- 4.5.1 Extraction of KCs as performance criteria -- 4.5.2 Formation of component catalog -- 4.5.3 Establishment of mapping route using correlation matrices -- 4.6 Summary -- 5 Optimization in Product Design -- 5.1 Introduction -- 5.1.1 Weighted sum method -- 5.1.2 Goal programming -- 5.1.3 Multi-level programming/rank ordering -- 5.1.4 Genetic algorithms -- 5.2 Automated Design Synthesis -- 5.2.1 Configuration design -- 5.2.2 Design synthesis techniques -- 5.3 Multi-objective Struggle Genetic Algorithm Design Synthesis -- 5.3.1 Problem formulation -- 5.3.2 The MOSGA algorithm -- 5.3.3 Implementation of MOSGA in product configuration design -- 5.3.4 Precautions and limitations -- 5.4 Post-optimal Solution Selection -- 5.5 A Case Study -- 5.5.1 Experience-based design -- 5.5.2 Product design using the design reuse approach -- 5.5.3 Comparison of the two methods -- 5.6 Summary -- 6 Cost Estimation in Product Development -- 6.1 Introduction -- 6.2 Product Development Cost -- 6.2.1 Cost stru.…”
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