
From Bioinspired Systems and Biomedical Applications to Machine Learning
Description
Alles über E-Books | Antworten auf Fragen rund um E-Books, Kopierschutz und Dateiformate finden Sie in unserem Info- & Hilfebereich.
More details
Other editions
Additional editions

Content
- Intro
- Preface
- Organization
- Contents - Part II
- Contents - Part I
- Models
- Towards a General Method for Logical Rule Extraction from Time Series
- 1 Introduction
- 2 Temporal APRIORI
- 3 Temporal Abstraction of Time Series
- 4 Application Example
- 5 Conclusions
- References
- A Principled Two-Step Method for Example-Dependent Cost Binary Classification
- 1 Introduction
- 2 Proposed Method
- 3 Experiments
- 3.1 Figure of Merit
- 3.2 Datasets
- 3.3 Benchmark Methods
- 3.4 Results
- 4 Conclusions
- References
- Symbiotic Autonomous Systems with Consciousness Using Digital Twins
- 1 Introduction
- 2 Symbiotic Autonomous Systems
- 3 Associative Cognitive Digital Twin Network
- 4 Consciousness Associative Layer
- 5 Conscious Associative Cognitive Architecture Framework
- 6 A Conscious Architecture for Critical Safety SAS
- 7 Conclusions
- References
- Deep Support Vector Classification and Regression
- 1 Introduction
- 2 Support Vector Machines
- 3 Deep Support Vector Machines
- 3.1 Deep Learning
- 3.2 Deep SVC and SVR
- 4 Experiments
- 4.1 Classification Experiments
- 4.2 Regression Experiments
- 5 Conclusions and Further Work
- References
- An Experimental Study on the Relationships Among Neural Codes and the Computational Properties of Neural Networks
- 1 Introduction
- 2 Materials and Methods
- 2.1 Methods of First Series of Experiments
- 2.2 Methods of the Second Series of Experiments
- 3 Results
- 3.1 Results of the First Series of Experiments
- 3.2 Results of the Second Series of Experiments
- 4 Discussion
- 5 Conclusions
- References
- Uninformed Methods to Build Optimal Choice-Based Ensembles
- 1 Introduction
- 2 Questions and Hypotheses
- 3 Methods
- 3.1 Dataset
- 3.2 Models
- 3.3 Evaluation
- 3.4 Software
- 4 Results
- 4.1 Best Method to Build Ensembles
- 4.2 Comparison with Single Learners and Random Predictions
- 4.3 Comparison with Ensembles Built with Decision Trees
- 5 Discussion
- References
- Robotics
- Design and Implementation of a Robotics Learning Environment to Teach Physics in Secondary Schools
- 1 Introduction
- 2 IDEE Overview
- 3 IDEE Implementation
- 4 The Inclined Plane in IDEE
- 5 Conclusions and Future Work
- References
- Multi-robot User Interface for Cooperative Transportation Tasks
- 1 Introduction
- 2 System Design
- 2.1 Hardware
- 2.2 Software
- 3 Our Approach and Results
- 3.1 Approach
- 3.2 Results
- 4 Conclusion
- References
- Precise Positioning and Heading for Autonomous Scouting Robots in a Harsh Environment
- 1 Introduction
- 2 State of the Art of the Involved Technologies
- 3 Absolute Localization High Level Description
- 4 Relative Localization Overview
- 5 Test
- 6 Results
- 6.1 Absolute Localization Position and Heading
- 6.2 Relative Localization Position and Heading
- 7 Conclusions
- References
- Applications
- Gesture Control Wearables for Human-Machine Interaction in Industry 4.0
- 1 Introduction
- 2 Gesture Control System Description
- 3 Gesture Control System Implementation
- 3.1 System Architecture
- 3.2 Hardware and Software
- 4 Experimentation
- 4.1 Experimental Setup
- 4.2 Reliability Experiment
- 4.3 Latency Times Experiment
- 5 Conclusions
- References
- Computing the Missing Lexicon in Students Using Bayesian Networks
- 1 Introduction
- 2 Theoretical Frame
- 2.1 Available Lexicon and Lexical Availability
- 2.2 Bayesian Networks
- 3 The Problem
- 3.1 Global Graph Generation
- 3.2 Bayesian Network Generation
- 4 Experiments and Results
- 5 Conclusions
- References
- Control of Transitory Take-Off Regime in the Transportation of a Pendulum by a Quadrotor
- 1 Introduction
- 2 Cable Modeling
- 2.1 Introduction
- 2.2 Our Cable Proposal
- 3 Quadrotor Control Strategy
- 4 Reinforcement Learning Model
- 5 Experiment
- 6 Results
- 7 Conclusions
- References
- Improving Scheduling Performance of a Real-Time System by Incorporation of an Artificial Intelligence Planner
- 1 Introduction
- 2 The Adaptive Hybrid Broadcast Model
- 2.1 Scheduling Information in the AHB Server
- 3 Incorporation of AI Planning: Multi-level Scheduling
- 4 Simulation of the AHB Communication Environment
- 5 Experiments and Results Obtained
- 6 Conclusions and Further Work
- References
- Convolutional Neural Networks for Olive Oil Classification
- 1 Introduction
- 2 Methodology
- 2.1 Olive Oil Samples
- 2.2 Chemical Methods for Data Acquisition
- 2.3 Deep Learning Approach
- 2.4 Software and Experimental Setting
- 3 Results
- 3.1 Architecture of the Model
- 3.2 Training the Model
- 3.3 Classification Performance
- 4 Discussion
- References
- An Indoor Illuminance Prediction Model Based on Neural Networks for Visual Comfort and Energy Efficiency Optimization Purposes
- 1 Introduction
- 2 Scope of the Research: Visual Comfort and CIESOL
- 3 A Neural Network Model for Indoor Illuminance of an Office-Room
- 3.1 ANN Inputs and Size
- 3.2 Data-Sets Construction
- 3.3 Architecture and Structure Selection
- 4 Results and Discussion
- 5 Conclusions and Future Works
- References
- Using Probabilistic Context Awareness in a Deliberative Planner System
- 1 Introduction
- 1.1 Contribution
- 1.2 Paper Organization
- 2 Framework Description
- 2.1 Probabilistic Inference Module
- 2.2 Probabilistic Planning
- 3 Experimentation
- 3.1 Evolution of the Location Probability
- 3.2 Comparison with Baseline
- 4 Conclusions
- References
- Combining Data-Driven and Domain Knowledge Components in an Intelligent Assistant to Build Personalized Menus
- 1 Introduction
- 2 Related Work
- 3 Overview of Diet4You
- 4 Formalization of the Nutritional Plan
- 5 Innovative Components of Diet4You
- 5.1 Hard Nutritional Restrictions Management
- 5.2 User Preferences
- 5.3 Cultural Eating Styles
- 5.4 Personal Menu Planner
- 5.5 Human and Artificial Intelligence Components Interaction
- 6 An Example of Application
- 7 Conclusions
- References
- Robust Heading Estimation in Mobile Phones
- 1 Introduction
- 2 Attitude Estimation
- 2.1 Quaternion Calculation
- 2.2 Magnetometer Calibration
- 2.3 Opportunistic Updates
- 3 Relative Position Estimation
- 4 Heading Estimation
- 5 Experimental Evaluation
- 6 Conclusions
- References
- Bioinspired Systems
- Crowding Differential Evolution for Protein Structure Prediction
- 1 Introduction
- 2 Methods
- 2.1 Main Aspects of PSP with Rosetta
- 2.2 Crowding-Based Differential Evolution
- 2.3 Structural Diversity Measure
- 3 Results
- 4 Conclusions
- References
- Bacterial Resistance Algorithm. An Application to CVRP
- 1 Introduction
- 2 Bacterial Antibiotic Resistance Algorithm
- 3 The Algorithmic Proposal
- 4 BARA Algorithm Applied to the CVRP
- 4.1 Solutions Representation
- 4.2 Solutions Evaluation
- 5 Results
- 6 Conclusions
- References
- Conceptual Description of Nature-Inspired Cognitive Cities: Properties and Challenges
- 1 Introduction
- 2 The Cognitive City
- 3 The City as a Complex System
- 4 Natural Resilient Systems
- 5 Our Nature-Inspired Cognitive City Model
- 5.1 Decentralized Control
- 5.2 Locality and Stigmergy
- 5.3 Networking and Feedback Loops
- 5.4 Specialization and Redundancy
- 5.5 Randomness
- 5.6 Governance
- 6 Example: A Cognitive City Scenario
- 7 Open Challenges
- 7.1 Societal Challenges
- 7.2 Technical Challenges
- 8 Conclusions
- References
- Genetic Algorithm to Evolve Ensembles of Rules for On-Line Scheduling on Single Machine with Variable Capacity
- 1 Introduction
- 1.1 Problem Definition
- 2 Solving Method
- 2.1 Schedule Builder
- 2.2 Priority Rules for the (1,Cap(t)||Ti)
- 2.3 Considering Ensembles of Rules and Some Previous Results
- 3 Evolving Ensembles of Rules with Genetic Algorithms
- 4 Experimental Study
- 4.1 Test Bed and Previous Results
- 4.2 Results from GA
- 5 Conclusions
- References
- Multivariate Approach to Alcohol Detection in Drivers by Sensors and Artificial Vision
- 1 Introduction
- 2 Materials and Methods
- 2.1 Electronic Design
- 2.2 Data Coupling Scheme
- 2.3 Data Analysis
- 3 Results
- 3.1 Prototype Selection
- 3.2 Classification Algorithms
- 3.3 Implementation
- 4 Conclusions and Future Works
- References
- Optimization of Bridges Reinforcements with Tied-Arch Using Moth Search Algorithm
- 1 Introduction
- 2 Problem
- 2.1 Objective Function
- 2.2 Decision Variable
- 2.3 Constraints
- 3 Moth Search
- 3.1 Lévy Flights
- 3.2 Straight Flight
- 4 Integration
- 5 Experimental Results
- 5.1 Comparing Results
- 5.2 Distribution Comparison
- 6 Conclusions
- References
- Repairing Infeasibility in Scheduling via Genetic Algorithms
- 1 Introduction
- 2 Definition of the Problem
- 3 Solution Builder
- 4 Genetic Algorithm
- 5 Experimental Study
- 6 Conclusions
- References
- Application of Koniocortex-Like Networks to Cardiac Arrhythmias Classification
- 1 Introduction
- 2 Application of KLN to Cardiac Arrhythmias Classification
- 3 Materials and Methods
- 3.1 MIT-BIH Dataset
- 3.2 Data Preparation
- 3.3 Koniocortex-Like Network Model
- 4 Results
- 4.1 Network Characteristics
- 4.2 Evaluation Method
- 4.3 Classification Results
- 5 Discussion
- 6 Conclusions
- References
- Machine Learning for Big Data and Visualization
- Content Based Image Retrieval by Convolutional Neural Networks
- 1 Introduction
- 2 State of the Art
- 3 Methodology
- 4 Experimental Results
- 4.1 Methods
- 4.2 Hardware and Software
- 4.3 Images Database
- 4.4 Results
- 5 Conclusion
- References
- Deep Learning Networks with p-norm Loss Layers for Spatial Resolution Enhancement of 3D Medical Images
- 1 Introduction
- 2 The Model
- 3 Experimental Results
- 3.1 Datasets
- 3.2 Methods
- 3.3 Results
- 4 Conclusion
- References
- Analysis of Dogs's Abandonment Problem Using Georeferenced Multi-agent Systems
- 1 Introduction
- 2 Related Work
- 3 Problem Statement
- 4 Simulation Model
- 4.1 Simulation Specifications and Features
- 4.2 Analysis and Definition of the Environment
- 4.3 Simulation Structure and Behavior
- 4.4 Environment and Agents Interactions
- 5 Conclusions
- 6 Future Work
- References
- Background Modeling by Shifted Tilings of Stacked Denoising Autoencoders
- 1 Introduction
- 2 Methodology
- 2.1 Patch Feature Extraction
- 2.2 Patch Classification
- 3 Experimental Results
- 3.1 Methods
- 3.2 Sequences
- 3.3 Parameter Selection
- 3.4 Evaluation
- 4 Conclusions
- References
- Deep Learning-Based Security System Powered by Low Cost Hardware and Panoramic Cameras
- 1 Introduction
- 2 Methodology
- 3 System Architecture
- 3.1 Software Architecture
- 3.2 Hardware Architecture
- 4 Experimental Results
- 5 Conclusions
- References
- Biomedical Applications
- Neuroacoustical Stimulation of Parkinson's Disease Patients: A Case Study
- 1 Introduction
- 2 Fundamentals
- 3 Methods and Materials
- 4 Results and Discussion
- 5 Conclusions
- References
- Evaluating Instability on Phonation in Parkinson's Disease and Aging Speech
- 1 Introduction
- 2 Phonation Fundamentals
- 3 Materials and Methods
- 4 Results and Discussion
- 5 Conclusions
- References
- Differentiation Between Ischemic and Heart Rate Related Events Using the Continuous Wavelet Transform
- 1 Introduction
- 2 Materials and Methods
- 3 Results
- 4 Discussion and Conclusions
- References
- .20em plus .1em minus .1emAutomatic Measurement of ISNT and CDR on Retinal Images by Means of a Fast and Efficient Method Based on Mathematical Morphology and Active Contours
- 1 Introduction
- 2 Method
- 2.1 Image Acquisition and Enhancement
- 2.2 Mathematical Morphology
- 2.3 Parametric Active Contours
- 3 Results
- 3.1 ISNT
- 3.2 Cup to Disc Ratio
- 4 Conclusions
- References
- Bihemispheric Beta Desynchronization During an Upper-Limb Motor Task in Chronic Stroke Survivors
- 1 Introduction
- 2 Materials and Methods
- 2.1 Participant Recruitment
- 2.2 Experimental Setup
- 2.3 Experimental Protocol
- 2.4 EEG Data Acquisition and Analysis
- 3 Results
- 3.1 EEG Topographic Analysis
- 3.2 Time-Frequency Analysis
- 4 Discussion
- 5 Conclusion
- References
- Modeling and Estimation of Non-functional Properties: Leveraging the Power of QoS Metrics
- 1 Introduction
- 2 RoQME Overview
- 3 Testing RoQME in an Intralogistics Robotic Scenario
- 3.1 Modeling QoS Metrics on SAFETY and PERFORMANCE
- 3.2 Execution of the Intralogistics Robotic Application
- 4 Conclusions and Future Work
- References
- Machine-Health Application Based on Machine Learning Techniques for Prediction of Valve Wear in a Manufacturing Plant
- 1 Introduction
- 2 Methodology
- 2.1 Prediction of Ideal Behavior Without Valve Wear
- 2.2 Prediction of Real Behavior with Valve Wear
- 2.3 Prediction of Valve Wear
- 3 Results
- 3.1 Prediction of Ideal Valve Opening with MLP
- 3.2 Prediction of Real Valve Opening with RNN
- 3.3 Prediction of Valve Wear Results
- 4 Conclusions
- References
- Deep Learning
- Artificial Semantic Memory with Autonomous Learning Applied to Social Robots
- 1 Introduction
- 2 Related Works
- 3 Person Identification Memory System Description
- 4 Experimentation
- 4.1 Dataset
- 4.2 Person Identification System Experiments
- 5 Limitations
- 6 Conclusion and Future Works
- References
- A Showcase of the Use of Autoencoders in Feature Learning Applications
- 1 Introduction
- 2 Fundamentals of Autoencoders
- 2.1 Encoded Space Structure
- 2.2 Available Software
- 3 Examples of Use
- 3.1 Visualization of High-Dimensional Data
- 3.2 Image Denoising
- 3.3 Anomaly Detection
- 3.4 Semantic Hashing
- 3.5 Other Applications
- 4 Conclusions
- References
- Automatic Image-Based Waste Classification
- 1 Introduction
- 2 Previous Work
- 3 Deep Architectures for Supervised Waste Classification
- 4 Classification Experiments Using TrashNet
- 4.1 The TrashNet Dataset
- 4.2 Data Pre-processing
- 4.3 Classification Experiments and Results
- 5 Conclusion
- References
- Propositional Rules Generated at the Top Layers of a CNN
- 1 Introduction
- 2 Models
- 2.1 CNN Architecture
- 2.2 The DIMLP Model
- 2.3 The Approximation of the CNN Architecture
- 3 Experiments
- 4 Conclusion
- References
- Deep Ordinal Classification Based on the Proportional Odds Model
- 1 Introduction
- 2 Proportional Odds Model as the Output Layer
- 3 Quadratic Weighted Kappa as the Loss Function
- 4 Experiments
- 4.1 Datasets
- 4.2 Models Compared
- 4.3 Experimental Design
- 5 Results
- 5.1 Statistical Analysis
- 5.2 Comparison with Previous Works
- 6 Conclusions
- References
- Data Preprocessing for Automatic WMH Segmentation with FCNNs
- 1 Introduction
- 2 Materials and Methods
- 2.1 Dataset
- 2.2 Preprocessing
- 2.3 Fully Convolutional Neural Network (adapted U-Net)
- 3 Experimental results
- 4 Discussion
- 5 Conclusions
- References
- FER in Primary School Children for Affective Robot Tutors
- 1 Introduction
- 1.1 Affective Robot Tutors
- 1.2 Facial Emotion Recognition
- 2 ARTIE: An Integrated Environment for the Development of Affective Robot Tutors
- 3 A Facial Emotional Expression Recognition Model for Primary School Students
- 3.1 Data Collection
- 3.2 Data Labelling
- 3.3 Emotional Model Generation
- 4 Results
- 5 Conclusions
- References
- Author Index
System requirements
File format: PDF
Copy protection: Watermark-DRM (Digital Rights Management)
System requirements:
- Computer (Windows; MacOS X; Linux): Use the free software Adobe Reader, Adobe Digital Editions, or any other PDF viewer of your choice (see eBook Help).
- Tablet/Smartphone (Android; iOS): Install the free app Adobe Digital Editions or another reading app for eBooks, e.g., PocketBook (see eBook Help).
- E-reader: Bookeen, Kobo, Pocketbook, Sony, Tolino and many more (only limited: Kindle).
The file format PDF always displays a book page identically on any hardware. This makes PDF suitable for complex layouts such as those used in textbooks and reference books (images, tables, columns, footnotes). Unfortunately, on the small screens of e-readers or smartphones, PDFs are rather annoying, requiring too much scrolling.
This eBook uses Watermark-DRM, a „soft” copy protection. This means that there are no technical restrictions to prevent illegal distribution. However, there is a personalised watermark embedded in the eBook that can be used to identify the purchaser of the eBook in the event of misuse and to provide evidence for legal purposes.
For more information, see our eBook Help page.