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1. |
Record Nr. |
UNINA9910720699003321 |
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Titolo |
Scientific innovation, philosophy, and public policy / edited by Ellen Frankel Paul, Fred D. Miller, Jr., and Jeffrey Paul |
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Pubbl/distr/stampa |
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Cambridge, : Cambridge University Press, 1996 |
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Descrizione fisica |
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Locazione |
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Collocazione |
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Lingua di pubblicazione |
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Materiale a stampa |
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Livello bibliografico |
Monografia |
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2. |
Record Nr. |
UNINA9910855372203321 |
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Titolo |
Geomorphic Risk Reduction Using Geospatial Methods and Tools / / edited by Raju Sarkar, Sunil Saha, Basanta Raj Adhikari, Rajib Shaw |
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Pubbl/distr/stampa |
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Singapore : , : Springer Nature Singapore : , : Imprint : Springer, , 2024 |
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ISBN |
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Edizione |
[1st ed. 2024.] |
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Descrizione fisica |
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1 online resource (328 pages) |
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Collana |
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Disaster Risk Reduction, Methods, Approaches and Practices, , 2196-4114 |
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Disciplina |
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Soggetti |
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Natural disasters |
Geographic information systems |
Geomorphology |
Machine learning |
Artificial intelligence |
Natural Hazards |
Geographical Information System |
Machine Learning |
Artificial Intelligence |
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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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Nota di contenuto |
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Landslide Susceptibility Assessment Based on Machine Learning Techniques -- Measuring landslide susceptibility in Jakholi region of Garhwal Himalaya applying novel ensembles of statistical and machine learning algorithms -- Landslide Susceptibility Mapping using GIS-based Frequency Ratio, Shannon Entropy, Information Value and Weight-of-Evidence approaches in part of Kullu district, Himachal Pradesh, India -- An advanced hybrid machine learning technique for assessing the susceptibility to landslides in the Meenachil river basin of Kerala, India -- Novel ensemble of M5P and Deep learning neural network for predicting landslide susceptibility: A cross-validation approach -- Artificial neural network ensemble with General linear model for modeling the Landslide Susceptibility in Mirik region of West Bengal, India -- Modeling gully erosion susceptibility using advanced machine learning method in Pathro River Basin, India -- Quantitative Assessment of Interferometric Synthetic Aperture 2 Radar(INSAR) for Landslide Monitoring and Mitigation -- Assessment of Landslide Vulnerability using Statistical and Machine Learning Methods in Bageshwar District of Uttarakhand, India -- Assessing the shifting of the River Ganga along Malda District of West Bengal, India -- An ensemble of J48 Decision Tree with AdaBoost, and Bagging for flood susceptibility mapping in the Sundarban of West Bengal, India -- Assessment of mouza level flood resilience in lower part of Mayurakshi River basin, Eastern India -- Spatial flashflood modeling in Beas River Basin of Himachal Pradesh, India using GIS-based machine learning algorithms -- Geospatial study of river shifting and erosion deposition phenomenon along a selected stretch of River Damodar, West Bengal, India -- An Evaluation of Hydrological Modeling Using CN Method in Ungauged Barsa River Basin of Pasakha, Bhutan -- The Adoption of Random Forest (RF) and Support Vector Machine (SVM) with Cat Swarm Optimization (CSO) to Predict the Soil Liquefaction. |
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Sommario/riassunto |
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This book explores the use of advanced geospatial techniques in geomorphic hazards modelling and risk reduction. It also compares the accuracy of traditional statistical methods and advanced machine learning methods and addresses the different ways to reduce the impact of geomorphic hazards. In recent years with the development of human infrastructures, geomorphic hazards are gradually increasing, which include landslides, flood and soil erosion, among others. They cause huge loss of human property and lives. Especially in mountainous, coastal, arid and semi-arid regions, these natural hazards are the main barriers for economic development. Furthermore, human pressure and specific human actions such as deforestation, inappropriate land use and farming have increased the danger of natural disasters and degraded the natural environment, making it more difficult for environmental planners and policymakers to develop appropriate long-term sustainability plans. The most challenging task is to develop a sophisticated approach for continuous inspection and resolution of environmental problems for researchers and scientists. However, in the past several decades, geospatial technology has undergone dramatic advances, opening up new opportunities for handling environmental challenges in a more comprehensive manner. With the help of geographic information system (GIS) tools, high and moderate resolution remote sensing information, such as visible imaging, synthetic aperture radar, global navigation satellite systems, light detection and ranging, Quickbird, Worldview 3, LiDAR, SPOT 5, |
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Google Earth Engine and others deliver state-of-the-art investigations in the identification of multiple natural hazards. For a thorough examination, advanced computer approaches focusing on cutting-edge data processing, machine learning and deep learning may be employed. To detect and manage various geomorphic hazards and their impact, several models with a specific emphasis on natural resources and the environment may be created. |
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3. |
Record Nr. |
UNINA9910483385003321 |
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Titolo |
Algebraic Methodology and Software Technology : 11th International Conference, AMAST 2006, Kuressaare, Estonia, July 5-8, 2006, Proceedings / / edited by Michael Johnson, Varmo Vene |
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Pubbl/distr/stampa |
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Berlin, Heidelberg : , : Springer Berlin Heidelberg : , : Imprint : Springer, , 2006 |
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ISBN |
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Edizione |
[1st ed. 2006.] |
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Descrizione fisica |
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1 online resource (XII, 392 p.) |
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Collana |
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Programming and Software Engineering, , 2945-9168 ; ; 4019 |
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Altri autori (Persone) |
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Disciplina |
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Soggetti |
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Software engineering |
Computer science |
Machine theory |
Computer programming |
Computer science - Mathematics |
Software Engineering |
Computer Science Logic and Foundations of Programming |
Formal Languages and Automata Theory |
Programming Techniques |
Symbolic and Algebraic Manipulation |
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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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Bibliographic Level Mode of Issuance: Monograph |
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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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Invited Talks -- Incremental Software Construction with Refinement Diagrams -- Recursive Program Schemes: Past, Present, and Future -- |
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Monad-Based Logics for Computational Effects -- Contributed Papers -- State Space Representation for Verification of Open Systems -- Data Movement Optimisation in Point-Free Form -- Measuring the Speed of Information Leakage in Mobile Processes -- Formal Islands -- Some Programming Languages for Logspace and Ptime -- Opaque Predicates Detection by Abstract Interpretation -- DO-Casl: An Observer-Based Casl Extension for Dynamic Specifications -- Model Transformations Incorporating Multiple Views -- Hyperfinite Approximations to Labeled Markov Transition Systems -- State Space Reduction of Rewrite Theories Using Invisible Transitions -- The Essence of Multitasking -- The Substitution Vanishes -- Decomposing Interactions -- Verification of Communication Protocols Using Abstract Interpretation of FIFO Queues -- Assessing the Expressivity of Formal Specification Languages -- Fork Algebras as a Sufficiently Rich Universal Institution -- Realizability Criteria for Compositional MSC -- Quantales and Temporal Logics -- Fractional Semantics -- Reasoning About Data-Parallel Pointer Programs in a Modal Extension of Separation Logic -- Testing Semantics: Connecting Processes and Process Logics -- Tableaux for Lattices -- Accelerated Modal Abstractions of Labelled Transition Systems -- A Compositional Semantics of Plan Revision in Intelligent Agents -- System Descriptions -- ITP/OCL: A Rewriting-Based Validation Tool for UML+OCL Static Class Diagrams -- A Computational Group Theoretic Symmetry Reduction Package for the Spin Model Checker -- Using Category Theory as a Basis for a Heterogeneous Data Source Search Meta-engine: The Prométhée Framework. |
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Sommario/riassunto |
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This is the proceedings of the 11th edition of the Algebraic Methodology and Software Technology (AMAST) conference series. The ?rst conference was held in the USA in 1989, and since then AMAST conferences have been held on (or near) ?ve di?erent continents and have been hosted by many of the most prominent people and organizations in the ?eld. The AMAST initiative has always sought to have practical e?ects by dev- oping the science of software and basing it on a ?rm mathematical foundation. AMAST hasinterpretedsoftwaretechnologybroadly,andhas, for example, held AMAST workshops in areas as diverse as real-time systems and (natural) l- guage processing. Similarly, algebraic methodology is interpreted broadly and includes abstract algebra, category theory, logic, and a range of other ma- ematical subdisciplines. The truly distinguishing feature of AMAST is that it seeks rigorous mathematical developments, but always strives to link them to real technological applications. Our meetings frequently include industry-based participants and are a rare opportunity for mathematicians and mathema- callymindedacademicstointeracttechnicallywithindustry-basedtechnologists. Over the years AMAST has included industrial participants from organizations specializing in safety-critical (including medical) systems, transport (including aerospace), and security-critical systems, amongst others. |
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