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Engineering design processes, which inherently involve multiple, often conflicting criteria, can be broadly classified into synthesis and analysis processes. Multiple Criteria Decision Making addresses synthesis and analysis processes through multiple objective optimisation to generate sets of efficient design solutions (i.e. on Pareto surfaces) and multiple attribute decision making to analyse and select the most preferred design solution(s). MCDM, therefore, has been widely used in all fields of engineering design; for example it has been applied to such diverse areas as naval battle ships criteria analysis/selection and product appearance design. Given a list of design alternatives with multiple conflicting criteria, preferences often determine the final selection of a particular set of design alternative(s). Preferences may also be used to drive the design/design optimisation processes. Various methods have been proposed to model preference structure, for example simple weights, multiple attribute utility theory, pairwise comparison, etc. Preference structure is often non-linear, discontinuous and complex. An Artificial Neural Network (ANN) learning-based preference elicitation method is presented in this paper. ANNs efficiently model the non-linearity, complexity and discontinuity nature of any given preference structure. A case study is presented to illustrate the learning-based approach to preference structure elicitation.

"Civil engineering is a profession that has a distinct focus on the design of infrastructure systems. There are major differences between the characteristics of the infrastructure design problems that civil engineers solve and the problems examined by other engineering disciplines, which tend to emphasize the design of smaller items produced for short term use. Beginning students in civil engineering should be made aware of these distinctions and the types of systems civil engineers design so that they can begin to think about the problems associated with them. This is the starting point for evolving into professional civil engineers whose area of expertise is design of the civil works infrastructure that supports modern societies."--

Expedience of probabilistic durability concepts and approaches in advanced engineering design of building materials, structural members and systems is considered. Target margin values of structural safety and serviceability indices are analyzed and their draft values are presented. Analytical methods of the cumulative coefficient of correlation and the limit transient action effect for calculation of reliability indices are given. Analysis can be used for probabilistic durability assessment of carrying and enclosure metal, reinforced concrete, wood, plastic, masonry both homogeneous and sandwich or composite structures and some kinds of equipments. Analysis models can be applied in other engineering fields.

Intro -- PROTEIN ENGINEERING -- LIBRARY OF CONGRESS CATALOGING-IN-PUBLICATION DATA -- CONTENTS -- PREFACE -- Chapter 1 SYNTHESIZING MAMMALIAN CELL ADHESIVE SURFACES USING SELF-ASSEMBLING FIBRONECTIN DOMAINS -- ABSTRACT -- INTRODUCTION -- THE DESIGN CONCEPT -- Directed Mutation of the 9th-10th Type III Fibronectin Domain Pair -- Design of Self-Assembling Integrin α5β1 Ligands -- CHARACTERISATION OF OLIGOMERIC PROTEINS -- ENGINEERING OF CELL ADHESIVE SURFACES -- MEDICAL APPLICATIONS OF CELL ADHESIVE LIGANDS AND SURFACES -- Bone Regeneration -- Wound Healing -- Cancer -- CONCLUSION -- REFERENCES -- Chapter 2 ENGINEERING THERMOBIFIDA FUSCA CELLULASES: CATALYTIC MECHANISMS AND IMPROVED ACTIVITY -- ABSTRACT -- INTRODUCTION -- Elucidation of Catalytic Mechanisms -- Roles of Cellulose-Binding Modules -- Improvement of Crystalline Cellulose Hydrolysis -- Improvement in Processivity -- Converting Free Cellulases into Cellulosome Components -- Other Cellulase Properties for Biomass Conversion -- CONCLUSION -- ACKNOWLEDGMENTS -- REFERENCES -- Chapter 3 AN EMPIRICAL STUDY FOR FINDING A ROBUST ENSEMBLE OF CLASSIFIERS FOR PROTEIN CLASSIFICATION -- ABSTRACT -- 1. INTRODUCTION -- 2. RELATED WORKS -- 2.1. Submitochondria Protein Location -- 2.2. Protein-Protein Interactions -- 3. FEATURE EXTRACTION -- 3.1. Physicochemical 2-Grams (P2G) -- 3.2. Quasi Residue Couple (RC) -- 3.3. Autocovariance Approach (AC) -- 3.4. Genetic Pseudo Amino Acids Features (GP) -- 4. EXPERIMENTS -- 5.1. Datasets and Testing Protocol -- 5.2. Experimental Results -- CONCLUSION -- REFERENCES -- Chapter 4 REVOLUTIONARY PROTEIN ENGINEERING USING MOLECULAR DISPLAY -- ABSTRACT -- CONTRIBUTION TO INNOVATION IN PROTEIN ENGINEERING -- CONTRIBUTION TO THE CREATION OF NOVEL AND FUNCTIONAL PROTEINS -- REFERENCES -- Chapter 5 CHEMOSELECTIVE MODIFICATION USING ALDEHYDE/KETONE TAGS -- ABSTRACT.

Cover -- Half Title -- Title Page -- Copyright Page -- Contents -- Foreword -- Preface -- Acknowledgments -- Authors -- Chapter 1 Remediation Engineering: State of the Practice -- 1.1 Introduction -- 1.1.1 Growth of an Industry -- 1.1.2 Technical Discipline to Practice -- 1.1.3 Advances in Complementary Disciplines -- 1.1.3.1 Advances in Remediation Hydrogeology -- 1.1.3.2 Advances in Environmental Microbiology -- 1.1.3.3 Environmental Geochemistry -- 1.1.3.4 Geophysical Methods -- 1.1.4 Role of Remediation Engineer -- 1.2 Evolution and Maturation of Technologies