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Impact of advances in computing and communications technologies on chemical science and technology [[electronic resource] ] : report of a workshop / / Chemical Sciences Roundtable, Board on Chemical Sciences and Technology, Commission on Physical Sciences, Mathematics, and Applications, National Research Council
| Impact of advances in computing and communications technologies on chemical science and technology [[electronic resource] ] : report of a workshop / / Chemical Sciences Roundtable, Board on Chemical Sciences and Technology, Commission on Physical Sciences, Mathematics, and Applications, National Research Council |
| Pubbl/distr/stampa | Washington, D.C., : National Academy Press, c1999 |
| Descrizione fisica | 1 online resource (235 p.) |
| Disciplina | 542/.85 |
| Collana | The compass series |
| Soggetto topico |
Chemistry - Data processing
Chemistry, Technical - Data processing Communication in chemistry - Technological innovations |
| Soggetto genere / forma | Electronic books. |
| ISBN |
1-280-21033-8
9786610210336 0-309-59707-2 0-585-13601-7 |
| Formato | Materiale a stampa  |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNINA-9910456133503321 |
| Washington, D.C., : National Academy Press, c1999 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Impact of advances in computing and communications technologies on chemical science and technology [[electronic resource] ] : report of a workshop / / Chemical Sciences Roundtable, Board on Chemical Sciences and Technology, Commission on Physical Sciences, Mathematics, and Applications, National Research Council
| Impact of advances in computing and communications technologies on chemical science and technology [[electronic resource] ] : report of a workshop / / Chemical Sciences Roundtable, Board on Chemical Sciences and Technology, Commission on Physical Sciences, Mathematics, and Applications, National Research Council |
| Pubbl/distr/stampa | Washington, D.C., : National Academy Press, c1999 |
| Descrizione fisica | 1 online resource (235 p.) |
| Disciplina | 542/.85 |
| Collana | The compass series |
| Soggetto topico |
Chemistry - Data processing
Chemistry, Technical - Data processing Communication in chemistry - Technological innovations |
| ISBN |
0-309-18402-9
1-280-21033-8 9786610210336 0-309-59707-2 0-585-13601-7 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNINA-9910778745603321 |
| Washington, D.C., : National Academy Press, c1999 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Impact of advances in computing and communications technologies on chemical science and technology : report of a workshop / / Chemical Sciences Roundtable, Board on Chemical Sciences and Technology, Commission on Physical Sciences, Mathematics, and Applications, National Research Council
| Impact of advances in computing and communications technologies on chemical science and technology : report of a workshop / / Chemical Sciences Roundtable, Board on Chemical Sciences and Technology, Commission on Physical Sciences, Mathematics, and Applications, National Research Council |
| Edizione | [1st ed.] |
| Pubbl/distr/stampa | Washington, D.C., : National Academy Press, c1999 |
| Descrizione fisica | 1 online resource (235 p.) |
| Disciplina | 542/.85 |
| Collana | The compass series |
| Soggetto topico |
Chemistry - Data processing
Chemistry, Technical - Data processing Communication in chemistry - Technological innovations |
| ISBN |
0-309-18402-9
1-280-21033-8 9786610210336 0-309-59707-2 0-585-13601-7 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
Impact of Advances in Computing and Communications Technologies on Chemical Science and Technology -- Copyright -- Preface -- Acknowledgment of Reviewers -- Contents -- Summary -- WHITHER COMPUTING AND COMMUNICATIONS TECHNOLOGIES IN CHEMICAL SCIENCE AND TECHNOLOGY? -- COMPUTATIONAL MODELING AND SIMULATION IN CHEMICAL SCIENCE AND TECHNOLOGY -- REMOTE COLLABORATION AND INSTRUMENTS ONLINE -- CHEMICAL INFORMATION ONLINE -- 1 The Accelerated Strategic Computing Initiative -- ASCI'S NEED FOR ADVANCED SIMULATION CAPABILITY -- The Challenges -- Where Are We Now? -- Accelerating Technology Developments -- Simulation Development Environment -- THE CHALLENGES AHEAD -- Archival Storage Systems and Data Management -- Input/Output -- Networks -- Data Analysis and Visualization -- Scientific Simulation Software -- Computer Systems Software -- THE ASCI ALLIANCES -- ASCI'S CONTRIBUTIONS TO THE GREATER SCIENCE COMMUNITY -- SUMMARY -- DISCUSSION -- 2 Software Development for Computational Chemistry: Does Anything Remain to Be Done? -- DISCUSSION -- 3 Recent Advances in Computational Thermochemistry and Challenges for the Future -- INTRODUCTION -- CURRENT STATE OF THE ART IN COMPUTATIONAL THERMOCHEMISTRY -- GAUSSIAN-N THEORY -- FUTURE OUTLOOK -- SUMMARY -- DISCUSSION -- Session 1 Panel Discussion -- 4 The Role of Computational Biology in the Genomics Revolution -- ABSTRACT -- INTRODUCTION -- PREDICTION OF PROTEIN STRUCTURE FROM SEQUENCE -- Description of Ab Initio Protein Folding Methodology -- Validation on Proteins of Known Structure -- Blind Predictions -- STRUCTURE TO FUNCTION -- Limitations of Sequence-based Methods -- Similarity of Global Tertiary Structure Does Not Always Imply Similarity of Function -- Proteins with Similar Function Conserve the Local Structure Around the Active Site, Even If the Glob.
Development of a Three-dimensional Library of Functional Motifs -- Representative Case: The Glutaredoxin/Thioredoxin Family -- Overview -- Ability of the FFF to Identify the Active Site in Experimentally Determined Structures -- Application of the FFF to Predicted Structures -- Screening of Entire Genomes -- COMPUTATIONAL REQUIREMENTS FOR GENOME SCALE STRUCTURE/FUNCTION PREDICTION -- OUTLOOK FOR THE FUTURE -- SUMMARY -- Literature Cited -- DISCUSSION -- 5 Needs and New Directions in Computing for the Chemical Process Industries -- BACKGROUND AND FACTORS DRIVING THE CHEMICAL INDUSTRY -- PROCESS SIMULATION NEEDS OF THE CPI -- AN OVERVIEW OF CURRENT SIMULATION PROGRAMS -- THE EUROPEAN CAPE OPEN PROJECT -- PROCESS CONTROL IN THE CPI -- CONCLUSIONS -- DISCUSSION -- 6 Vision 2020: Computational Needs of the Chemical Industry -- INTRODUCTION -- PROCESS ENGINEERING IN 2020 -- COMPUTATIONAL CHEMISTRY AND MOLECULAR MODELING -- PROCESS CONTROL AND INSTRUMENTATION -- Process Measurement and Control Workshop -- Chemical Instrumentation -- PROCESS OPERATIONS -- PRESENT STATUS -- CHALLENGES -- Session 2 Panel Discussion -- 7 Collaboratory Life: Challenges of Internet-mediated Science for Chemists -- ABSTRACT -- COLLABORATORY LIFE: CHALLENGES OF INTERNET-MEDIATED SCIENCE FOR CHEMISTS -- WHERE DO WE COME FROM? -- WHAT ARE WE? -- WHERE ARE WE GOING? -- The Collaboratory Concept -- Chemistry on the Internet -- The Value of Collaboratories -- Free Flow of Information -- Participatory Education -- CONCLUSION -- ACKNOWLEDGMENTS -- 8 A Computer Science Perspective on Computing for the Chemical Sciences -- DISCUSSION -- 9 Collaboratories: Building Electronic Scientific Communities -- ABSTRACT -- INTRODUCTION -- OPPORTUNITIES FOR COLLABORATORIES -- EXAMPLES OF COLLABORATORIES -- TOOLS FOR COLLABORATION -- Electronic Laboratory Notebooks -- Real-Time Interactions. IMPACTS OF COLLABORATORIES -- THE PROMISE OF COLLABORATORIES -- CONCLUSION -- ACKNOWLEDGMENTS -- DISCUSSION -- 10 The World Wide Laboratory: Remote and Automated Access to Imaging Instrumentation -- INTRODUCTION -- WWL: CURRENT IMPLEMENTATIONS FOR SERVICE, COLLABORATION, AND EDUCATION -- Remote Access to TEM -- Remote Access to MRI -- Chickscope: A K-12 Education Project Using Remote MRI -- REMOTE INSTRUMENTATION FOR SERVICE, COLLABORATION, AND EDUCATION: LESSONS LEARNED -- User Interface -- Modes of Collaboration -- WWL: Current Implementations for Research -- Automated/Intelligent Control for Scientific Research -- REMOTE INSTRUMENTATION FOR SCIENTIFIC RESEARCH: LESSONS LEARNED -- CONCLUSIONS -- ACKNOWLEDGMENTS -- DISCUSSION -- 11 The Wired Laboratory -- HOW HAVE ADVANCES IN COMPUTING TECHNOLOGY HELPED WITH EFFICIENCY IN THE ANALYTICAL CHEMISTRY LABORATORY? -- EXAMPLES FROM A WIRED LABORATORY -- Quantum-Model of an Integrated Spectroscopy Information System -- Walk-up Spectroscopy Laboratory-Instruments Online -- Electronic Information and Knowledge Management -- WIMS-Web-based Information Management System -- The Electronic Laboratory Notebook -- THE FUTURE -- Information Management -- Data Analysis and Instrumentation -- SUMMARY -- CONTRIBUTORS -- DISCUSSION -- Session 3 Panel Discussion -- 12 Chemical Data in the "Internet Age -- INTRODUCTION -- DATA NEEDS -- TYPES OF DATA RESOURCES -- PROBLEMS IN PROVIDING DATA -- DATA RESOURCES CURRENTLY AVAILABLE -- Beilstein Database -- DIPPR Project -- The NIST Chemistry WebBook -- USER DEMAND FOR DATA -- WHAT IS NEEDED -- DISCUSSION -- 13 The Digital Library: An Integrated System for Scholarly Communication -- CRISIS IN SCHOLARLY COMMUNICATION -- SOLUTIONS AND STRATEGIES -- THE CALIFORNIA DIGITAL LIBRARY -- ALTERNATIVE FORMS OF SCHOLARLY COMMUNICATION -- CONCLUSION -- DISCUSSION. 14 Electronic Journal Publishing at the American Chemical Society -- GROWTH OF SCIENTIFIC LITERATURE -- FINANCIAL CONSIDERATIONS -- CHRONOLOGY OF ACS ELECTRONIC JOURNAL DEVELOPMENT -- WHAT CUSTOMERS WANT IN ELECTRONIC JOURNALS -- THE ADVENT OF ELECTRONIC PUBLISHING -- TRANSFORMATION FROM PRINT TO ELECTRONIC PUBLISHING -- DISCUSSION -- Session 4 Panel Discussion -- Appendixes -- Appendix A List of Workshop Participants -- Staff -- Appendix B Origin of and Information on the Chemical Sciences Roundtable. |
| Record Nr. | UNINA-9910960861103321 |
| Washington, D.C., : National Academy Press, c1999 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Support vector machine in chemistry [[electronic resource] /] / Nianyi Chen ... [et al.]
| Support vector machine in chemistry [[electronic resource] /] / Nianyi Chen ... [et al.] |
| Pubbl/distr/stampa | Singapore ; ; Hackensack, N.J., : World Scientific, c2004 |
| Descrizione fisica | 1 online resource (344p.) |
| Disciplina | 540.285631 |
| Altri autori (Persone) | ChenNianyi |
| Soggetto topico |
Chemistry - Data processing
Chemistry, Technical - Data processing Machine learning |
| Soggetto genere / forma | Electronic books. |
| ISBN |
1-281-93460-7
9786611934606 981-279-471-9 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
1. Introduction. 1.1. Support vector machine: data processing method for problems of small sample size. 1.2. Support vector machine: data processing method for complicated data sets in chemistry. 1.3. Underfitting and overfitting: problems of machine learning. 1.4. Theory of overfitting and underfitting control, ERM and SRM principles of statistical learning theory. 1.5. Concept of large margin - a basic concept of SVM. 1.6. Kernel functions: technique for nonlinear data processing by linear algorithm. 1.7. Support vector regression: regression based on principle of statistical learning theory. 1.8. Other machine learning methods related to statistical learning theory. 1.9. Some comments on the application of SVM in chemistry -- 2. Support Vector Machine. 2.1. Margin and optimal separating plane. 2.2. Interpretation by statistical learning therory. 2.3. Support vector classification. 2.4. Support vector regression. 2.5 V-SVM -- 3. Kernel functions. 3.1. Introduction. 3.2. Mercer kernel. 3.3. Properties of kernel. 3.4. Kernel selection -- 4. Feature selection using support vector machine. 4.1. Significance and difficulty of feature selection in chemical data processing. 4.2. SVM-BFS - application of wrapper method and floating search method. 4.3. SVM-RFE: application of optimal brain damage and recursive feature elimination. 4.4. Multitask learning. 4.5. Computer experiments: feature selection of artificially generated data set -- 5. Principle of atomic or molecular parameter-data processing method. 5.1. Two different strategies for structure-property relationship investigation. 5.2. Number of valence electrons of atoms. 5.3. Ionization potential of atoms. 5.4. Atomic radii and ionic radii. 5.5. Electronegativity. 5.6. Charge-radius ratio. 5.7. Topological parameters of molecules and 3-D molecular descriptors. 5.8. Atomic parameters for ionic systems. 5.9. Atomic parameters for covalent compounds. 5.10. Atomic parameters for metallic systems -- 6. SVM applied to phase diagram assessment and prediction. 6.1. Comprehensive assessment and computerized prediction of phase diagrams. 6.2.Atomic parameter-pattern recognition method for phase diagram prediction. 6.3. Prediction of intermediate compound formation. 6.4. Prediction of formation of extended solid solutions. 6.5. Prediction of melting types of intermediate compounds. 6.6. Modeling of melting points or decomposition temperature of intermediate compounds. 6.7. Prediction of crystal types of intermediate compounds. 6.8. Modeling of liquid-liquid immiscibility of inorganic systems. 6.9. SVM applied to intelligent database of phase diagrams.
7. SVM applied to thermodynamic property prediction. 7.1. Significance of estimation of thermodynamic properties of chemical substances. 7.2. Modeling of enthalpy of formation of compounds. 7.3. Modeling of free energy of mixing of liquid alloy systems. 7.4 Prediction of activity coefficient of concentrated electrolyte solutions. 7.5. Regularity of the solubility of C[symbol] in organic solvents -- 8. SVM applied to molecular and materials design. 8.1. concepts of molecular design and materials design. 8.2. SVM applied to new compound synthesis problems. 8.3. SVM applied to the computerized prediction of properties of materials. 8.4. SVM applied to process design for materials preparation -- 9. SVM applied to structure-activity relationships. 9.1. Concept of Structure-Activity Relationships (SAR). 9.2. Brief Introduction to some of chemometric methods used in SAR. 9.3. Brief introduction to molecular descriptors used in SAR. 9.4 SAR of N-(3-Oxo-3,4-dihydro-2H-benzo[l,4]oxazine-6-carbonyl) guanidines. 9.5. SAR of triazole-derivatives. 9.6. SAR of the 5-hydroxytryptamine receptor antagonists. 9.7. QSAR of N-phenylacetamides as herbicides -- 10. SVM applied to data of trace element analysis. 10.1. Trace element science and chemical data processing. 10.2. SVM applied to trace element analysis of human hair. 10.3. SVM applied to trace elements analysis of cigarettes. 10.4. SVM applied to trace element analysis of tea -- 11. SVM applied to archeological chemistry of ancient ceramics. 11.1. SVM applied to archeological data processing. 11.2. Identification of Jun Wares of Song Dynasty. 11.3. Modeling of official Ru Wares. 11.4. Modeling of composition of Yue Wares. 11.5. Modeling of composition of blue and white porcelain samples. 11.6. Archeological research of ancient porcelain kilns. 11.7. Period discrimination of ancient samples -- 12. SVM applied to cancer research. 12.1. SVM applied to cancer epidemiology. 12.2. Carcinogenic and environmental behaviors of polycyclic aromatic hydrocarbons. 12.3. SVM applied to cancer diagnosis -- 13. SVM applied to some topics of chemical analysis. 13.1. Multivariate calibration in chemical analysis. 13.2. Retention indices estimation in chromatography. 13.3. Detection of hidden explosives -- 14. SVM applied to chemical and metallurgical technology. 14.1. Physico-chemical basis of modeling of chemical processes. 14.2. Characteristics of data processing for industrial process modeling. 14.3. Optimal zone: strategy of large margin search. 14.4. Application of strategy of large margin search. 14.5. Optimal control for target maximization or minimization. 14.6. Optimal control for problem of restricted response. 14.7. Materials properties estimation for production process. 14.8. Comprehensive strategy for industrial optimization. |
| Record Nr. | UNINA-9910454316703321 |
| Singapore ; ; Hackensack, N.J., : World Scientific, c2004 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Support vector machine in chemistry [[electronic resource] /] / Nianyi Chen ... [et al.]
| Support vector machine in chemistry [[electronic resource] /] / Nianyi Chen ... [et al.] |
| Pubbl/distr/stampa | Singapore ; ; Hackensack, N.J., : World Scientific, c2004 |
| Descrizione fisica | 1 online resource (344p.) |
| Disciplina | 540.285631 |
| Altri autori (Persone) | ChenNianyi |
| Soggetto topico |
Chemistry - Data processing
Chemistry, Technical - Data processing Machine learning |
| ISBN |
1-281-93460-7
9786611934606 981-279-471-9 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
1. Introduction. 1.1. Support vector machine: data processing method for problems of small sample size. 1.2. Support vector machine: data processing method for complicated data sets in chemistry. 1.3. Underfitting and overfitting: problems of machine learning. 1.4. Theory of overfitting and underfitting control, ERM and SRM principles of statistical learning theory. 1.5. Concept of large margin - a basic concept of SVM. 1.6. Kernel functions: technique for nonlinear data processing by linear algorithm. 1.7. Support vector regression: regression based on principle of statistical learning theory. 1.8. Other machine learning methods related to statistical learning theory. 1.9. Some comments on the application of SVM in chemistry -- 2. Support Vector Machine. 2.1. Margin and optimal separating plane. 2.2. Interpretation by statistical learning therory. 2.3. Support vector classification. 2.4. Support vector regression. 2.5 V-SVM -- 3. Kernel functions. 3.1. Introduction. 3.2. Mercer kernel. 3.3. Properties of kernel. 3.4. Kernel selection -- 4. Feature selection using support vector machine. 4.1. Significance and difficulty of feature selection in chemical data processing. 4.2. SVM-BFS - application of wrapper method and floating search method. 4.3. SVM-RFE: application of optimal brain damage and recursive feature elimination. 4.4. Multitask learning. 4.5. Computer experiments: feature selection of artificially generated data set -- 5. Principle of atomic or molecular parameter-data processing method. 5.1. Two different strategies for structure-property relationship investigation. 5.2. Number of valence electrons of atoms. 5.3. Ionization potential of atoms. 5.4. Atomic radii and ionic radii. 5.5. Electronegativity. 5.6. Charge-radius ratio. 5.7. Topological parameters of molecules and 3-D molecular descriptors. 5.8. Atomic parameters for ionic systems. 5.9. Atomic parameters for covalent compounds. 5.10. Atomic parameters for metallic systems -- 6. SVM applied to phase diagram assessment and prediction. 6.1. Comprehensive assessment and computerized prediction of phase diagrams. 6.2.Atomic parameter-pattern recognition method for phase diagram prediction. 6.3. Prediction of intermediate compound formation. 6.4. Prediction of formation of extended solid solutions. 6.5. Prediction of melting types of intermediate compounds. 6.6. Modeling of melting points or decomposition temperature of intermediate compounds. 6.7. Prediction of crystal types of intermediate compounds. 6.8. Modeling of liquid-liquid immiscibility of inorganic systems. 6.9. SVM applied to intelligent database of phase diagrams.
7. SVM applied to thermodynamic property prediction. 7.1. Significance of estimation of thermodynamic properties of chemical substances. 7.2. Modeling of enthalpy of formation of compounds. 7.3. Modeling of free energy of mixing of liquid alloy systems. 7.4 Prediction of activity coefficient of concentrated electrolyte solutions. 7.5. Regularity of the solubility of C[symbol] in organic solvents -- 8. SVM applied to molecular and materials design. 8.1. concepts of molecular design and materials design. 8.2. SVM applied to new compound synthesis problems. 8.3. SVM applied to the computerized prediction of properties of materials. 8.4. SVM applied to process design for materials preparation -- 9. SVM applied to structure-activity relationships. 9.1. Concept of Structure-Activity Relationships (SAR). 9.2. Brief Introduction to some of chemometric methods used in SAR. 9.3. Brief introduction to molecular descriptors used in SAR. 9.4 SAR of N-(3-Oxo-3,4-dihydro-2H-benzo[l,4]oxazine-6-carbonyl) guanidines. 9.5. SAR of triazole-derivatives. 9.6. SAR of the 5-hydroxytryptamine receptor antagonists. 9.7. QSAR of N-phenylacetamides as herbicides -- 10. SVM applied to data of trace element analysis. 10.1. Trace element science and chemical data processing. 10.2. SVM applied to trace element analysis of human hair. 10.3. SVM applied to trace elements analysis of cigarettes. 10.4. SVM applied to trace element analysis of tea -- 11. SVM applied to archeological chemistry of ancient ceramics. 11.1. SVM applied to archeological data processing. 11.2. Identification of Jun Wares of Song Dynasty. 11.3. Modeling of official Ru Wares. 11.4. Modeling of composition of Yue Wares. 11.5. Modeling of composition of blue and white porcelain samples. 11.6. Archeological research of ancient porcelain kilns. 11.7. Period discrimination of ancient samples -- 12. SVM applied to cancer research. 12.1. SVM applied to cancer epidemiology. 12.2. Carcinogenic and environmental behaviors of polycyclic aromatic hydrocarbons. 12.3. SVM applied to cancer diagnosis -- 13. SVM applied to some topics of chemical analysis. 13.1. Multivariate calibration in chemical analysis. 13.2. Retention indices estimation in chromatography. 13.3. Detection of hidden explosives -- 14. SVM applied to chemical and metallurgical technology. 14.1. Physico-chemical basis of modeling of chemical processes. 14.2. Characteristics of data processing for industrial process modeling. 14.3. Optimal zone: strategy of large margin search. 14.4. Application of strategy of large margin search. 14.5. Optimal control for target maximization or minimization. 14.6. Optimal control for problem of restricted response. 14.7. Materials properties estimation for production process. 14.8. Comprehensive strategy for industrial optimization. |
| Record Nr. | UNINA-9910782119903321 |
| Singapore ; ; Hackensack, N.J., : World Scientific, c2004 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
