Advances in engineering research. Volume 13 / Victoria M. Petrova, editor.

Format:

Book

Contributor:

Petrova, Victoria M., editor.

Series:

Advances in Engineering Research (NOT ON COVER)

Advances in Engineering Research, 2159-1989

Language:

English

Subjects (All):

Engineering--Research.

Engineering.

Physical Description:

1 online resource (215 p.)

Place of Publication:

New York : Nova Publishers, 2016.

Summary:

This book focuses on the latest developments in the field of engineering. The first chapter presents trajectory planning for robots with rigid bodies. Chapter Two explores image tracking of a humanoid robot based on visual serving. Chapter Three describes a project in the area of Ambient Assisted Living (AAL), in particular for the continuous care of the elderly. Chapter Four reviews how widely combat robots will be used in the future. Chapter Five tackles the problem of diagnosing complex systems composed of units capable of executing tests on each other (so-called, mutual testing). Chapter Six demonstrates how data from learning processes can be extracted, semantically prepared, and transformed into mining executable formats to enable prediction of individual learning patterns and outcomes through further semantic analysis of the discovered models. Chapter Seven explores ways to make TSHD more dredging efficiency. Chapter Eight discusses personalized thermal comfort.

Contents:

ADVANCES IN ENGINEERING RESEARCH: VOLUME 13; ADVANCES IN: ENGINEERING RESEARCH: VOLUME 13; Library of Congress Cataloging-in-Publication Data; CONTENTS; PREFACE; Chapter 1: TRAJECTORY PLANNING; Abstract; 1. Background of Trajectory Planning Problem; 1.1. Problem; 1.2. Motion Equation and State of Robot; 2. Solvers; 2.1. Full Search Algorithm; 2.2. Randomized Kynodynamic Planning; 2.3. RASMO; 2.4. LPUSS; Conclusion; References; Chapter 2: IMAGE TRACKING OF A HUMANOID ROBOT BASED ON VISUAL SERVING; ABSTRACT; INTRODUCTION; 1. HUMANOID ROBOT SYSTEM ARCHITECTURE

2. STEREO VISION SYSTEM OF THE HUMANOID ROBOT3. KINEMATICS ANALYSIS OF HUMANOID ROBOT ARM; 4. THE TARGET OBJECT TRACKING AND POSITION; 5. THE REALIZATION OF THE VISION TRACKING; 6. POSITION AND TRACKING EXPERIMENTS; CONCLUSION; ACKNOWLEDGMENT; REFERENCES; Chapter 3: DEVELOPMENT OF A MECHATRONIC SYSTEM FOR BEDRIDDEN PEOPLE SUPPORT; ABSTRACT; 1. INTRODUCTION; 1.1. Context; 1.2. Motivation; 1.3. Aim; 2. STATE OF ART; 2.1. Target Population; 2.2. Scenario of the Caregiver; 2.3. Ambient Assisted Living (AAL); 2.4. Assistive Technology; 2.5. Existing Equipment; 2.5.1. Safety-Related Equipment

2.5.2. Comfort-Related Equipment2.5.3. Mobility-Related Equipment; 2.5.4. Hygiene-Related Equipment; 2.5.5. Value Analysis of Existing Equipment; 2.5.6. The Hold of the Analysis; 3. METHODOLOGY OF PROJECT; 4. FINAL REMARKS; REFERENCES; Chapter 4: COMBAT AUTONOMOUS ARTIFICIAL INTELLIGENCE AND THE FUTURE OF CIVILISATION; ABSTRACT; INTRODUCTION; THE ABILITY OF DEVELOPED COUNTRIES TO WITHSTAND EXTERNAL AGGRESSION IN THE 21ST CENTURY; THE CREATION OF FIGHTING ROBOT ARMIES - A NECESSARY CONDITION FOR THE SURVIVAL OF THE DEVELOPED COUNTRIES IN THE 21ST CENTURY; CONCLUSION; REFERENCES

Chapter 5: APPLYING PETRI NETS TO MODELING OF COMPLEX SYSTEMS DIAGNOSISABSTRACT; INTRODUCTION; UTILIZATION OF MUTUAL TESTING IN COMPLEX SYSTEMS; APPROACHES TO MODELING OF MUTUAL TESTING; BASICS OF PETRI NETS; APPLYING PETRI NETS TO MODELING OF MUTUAL TESTING; SIMULATION RESULTS; CONCLUSION; REFERENCES; Chapter 6: SEMANTIC PROCESS MINING TOWARDS THE DISCOVERY AND ENHANCEMENT OF LEARNING MODELS ANALYSIS; ABSTRACT; 1. INTRODUCTION; 2. SYSTEM OVERVIEW; 2.1. Learning Process Example; 3. LEARNING PROCESS MINING IN ACTION; 3.1. Learning Process Mapping; 4. SEMANTIC LEARNING PROCESS MINING

4.1. Semantic Annotation of Learning Workflow Library4.2. Semantic Modellig: Ontological Representation of Learning Workflow Sequence with BPMN and Learning Activity Concepts; 4.3. Using Semantic Rules and Description Logic Queries to Discover and Enhance Patterns within the Learning Model; 4.4. Querying of Learning Process Parameters/Real World Question Answering Using Description Logic (DL) Queries; 5. SLPM - AUTOMATED LEARNING ALGORITHM; 6. RELATED WORKS; CONCLUSION; REFERENCES; Chapter 7: TO EXPLORE WAYS TO MAKE TSHD MORE DREDGING EFFICIENCY; ABSTRACT; 1. INTRODUCTION

2. BASIC CONCEPT AND CHARACTERISTICS OF COMBINED DREDGING SYSTEM

Notes:

Description based upon print version of record.

Includes bibliographical references at the end of each chapters and index.

Description based on online resource; title from PDF title page (ebrary, viewed October 5, 2016).

ISBN:

1-63485-427-6