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1. |
Record Nr. |
UNINA9910484694803321 |
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Autore |
Taghia Javad |
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Titolo |
Applied guidance methodologies for off-road vehicles / / Javad Taghia, Jayantha Katupitiya |
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Pubbl/distr/stampa |
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Cham : , : Springer International Publishing : , : Imprint : Springer, , 2020 |
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ISBN |
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Edizione |
[1st edition 2020.] |
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Descrizione fisica |
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1 online resource (xiv, 137 pages) |
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Collana |
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Springer Tracts in Advanced Robotics, , 1610-7438 ; ; 138 |
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Disciplina |
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Soggetti |
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Robotics |
Artificial intelligence |
Automated vehicles - Control |
Off-road vehicles |
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Lingua di pubblicazione |
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Formato |
Materiale a stampa |
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Livello bibliografico |
Monografia |
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Note generali |
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Nota di contenuto |
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Introduction -- Modelling Vehicle Systems -- Offset Models of Vehicles -- Design of Controllers -- Implementation of Controllers -- Conclusion. |
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Sommario/riassunto |
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This book provides methodologies for designing and implementing guidance algorithms for autonomous vehicles. These algorithms make important decision regarding how to steer and drive a ground vehicle in order to safely stay on an intended path, thereby making the vehicle driverless. The design tools provided in this book enable the reader to develop highly practical and real-world implementable guidance algorithms that will deliver high-accuracy driving for field vehicles. (They are equally applicable for on-road vehicles.) The book covers a variety of vehicle types, including wheeled vehicles, tracked vehicles, wheeled and tracked vehicles towing trailers, and four-wheel-steer and four-wheel-drive vehicles. It also covers active trailers that are driven and steered. Vehicles used in agriculture, mining and road construction are subjected to unpredictable and significant disturbances. The robust control methodologies presented can successfully compensate for these disturbances, as confirmed by the experimental results presented. Though the majority of the methodologies presented are based on sliding-mode controllers, other robust control methodologies |
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are also discussed. To help the reader decide which controller is best suited for his/her choice of vehicle, experimental results are presented in a comparative format. . |
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2. |
Record Nr. |
UNISA996217063403316 |
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Titolo |
Advanced computer-assisted techniques in drug discovery [[electronic resource] /] / edited by Han van de Waterbeemd |
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Pubbl/distr/stampa |
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Weinheim ; ; New York, : VCH, c1995 |
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ISBN |
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1-281-84288-5 |
9786611842888 |
3-527-61567-9 |
3-527-61566-0 |
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Descrizione fisica |
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1 online resource (367 p.) |
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Collana |
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Methods and principles in medicinal chemistry ; ; v. 3 |
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Altri autori (Persone) |
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Disciplina |
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Soggetti |
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Pharmaceutical chemistry - Data processing |
Drugs - Design - Data processing |
Drugs - Research - Data processing |
QSAR (Biochemistry) |
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Lingua di pubblicazione |
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Formato |
Materiale a stampa |
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Livello bibliografico |
Monografia |
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Note generali |
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Description based upon print version of record. |
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Nota di bibliografia |
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Includes bibliographical references and index. |
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Nota di contenuto |
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Advanced Computer- Assisted Techniques in Drug Discovery; Preface; A Personal Foreword; Contents; 1 Introduction; 1.1 3D QSAR; 1.2 Databases; 1.3 Progress in Multivariate Data Analysis; 1.4 Scope of this Book; References; 2 3D QSAR: The Integration of QSAR with Molecular Modeling; 2.1 Chemometrics and Molecular Modeling; 2.1.1 Introduction; 2.1.2 QSAR Methodology using Molecular Modeling and Chemometrics; 2.1.2.1 Search for the Geometric Pharmacophore; 2.1.2.2 Quantitative Correlation between Molecular Properties and Activity; 2.1.2.3 Computer Programs; 2.1.3 Illustrative Examples |
2.1.3.1 Amnesia-Reversal Compounds2.1.3.2 Non-Peptide Angiotensin II Receptor Antagonists; 2.1.3.3 HMG-CoA Reductase Inhibitors; 2.1.3.4 |
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Antagonists at the 5-HT3 Receptor; 2.1.3.5 Polychlorinated Dibenzo-p-dioxins; 2.1.4 Conclusions; References; 2.2 3D QSAR Methods; 2.2.1 Introduction; 2.2.2 3D QSAR of a Series of Calcium Channel Agonists; 2.2.2.1 Molecular Alignment; 2.2.2.2 Charges; 2.2.2.3 Generating 3D Fields; 2.2.2.4 Compilation of GRID Maps; 2.2.2.5 Inclusion of Macroscopic Descriptors with 3D Field Data; 2.2.3 Statistical Analysis; 2.2.3.1 Results of the Analysis |
2.2.3.2 Testing the Model2.2.4 Conclusions; References; 2.3 GOLPE Philosophy and Applications in 3D QSAR; 2.3.1 Introduction; 2.3.1.1 3D Molecular Descriptors and Chemometric Tools; 2.3.1.2 Unfolding Three-way Matrices; 2.3.2 The GOLPE Philosophy; 2.3.2.1 Variable Selection; 2.3.3 Applications; 2.3.3.1 PCA on the Target Matrix; 2.3.3.2 PCA on the Probe Matrix; 2.3.3.3 PLS Analysis on the Target Matrix; 2.3.3.4 PLS on Target Matrix as a Strategy to Ascertain the Active Conformation; 2.3.3.5 GOLPE with Different 3D Descriptors; 2.3.4 Conclusions and Perspectives; References |
3 Rational Use of Chemical and Sequence Databases3.1 Molecular Similarity Analysis: Applications in Drug Discovery; 3.1.1 Introduction; 3.1.2 Similarity-Based Compound Selection; 3.1.2.1 Similarity Measures and Neighborhoods; 3.1.2.2 Application of 2D and 3D Similarity Measures; 3.1.2.3 Application of Dissimilarity-Based Compound Selection for Broad Screening; 3.1.3 Structure-Activity Maps (SAMs); 3.1.3.1 A Visual Analogy; 3.1.3.2 Representing Inter-Structure Distances; 3.1.3.3 Structure Maps; 3.1.3.4 Coloring a Structure Map; 3.1.4 Field-Based Similarity Methods |
3.1.4.1 Field-Based Similarity Measures3.1.4.2 Field-Based Molecular Superpositions; 3.1.4.3 An Example of Field-Based Fitting: Morphine and Clonidine; 3.1.5 Conclusions; References; 3.2 Clustering of Chemical Structure Databases for Compound Selection; 3.2.1 Introduction; 3.2.2 Review of Clustering Methods; 3.2.2.1 Hierarchical Clustering Methods; 3.2.2.2 Non-Hierarchical Clustering Methods; 3.2.3 Choice of Clustering Method; 3.2.3.1 Computational Requirements; 3.2.3.2 Cluster Shapes; 3.2.3.3 Comparative Studies |
3.2.4 Examples of the Selection of Compounds from Databases by Clustering Techniques |
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Sommario/riassunto |
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The use of powerful computers has revolutionized molecular design and drug discovery. Thoroughly researched and well-structured, this comprehensive handbook covers highly effective and efficient techniques in 3D-QSAR and advanced statistical analysis. The emphasis is on showing users how to apply these methods and avoid costly and time-consuming methodical errors.Topics covered include* combination of statistical methods and molecular modeling tools* rational use of databases* advanced statistical techniques* neural networks and expert systems in molecular design<br |
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