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Research Interests:
Research Interests:
Artificial networks can be used to identify hydrogen nuclear magnetic resonance (1H-NMR) spectra of complex oligosaccharides. Feed-forward neural networks with back-propagation of errors can distinguish between spectra of oligosaccharides... more
Artificial networks can be used to identify hydrogen nuclear magnetic resonance (1H-NMR) spectra of complex oligosaccharides. Feed-forward neural networks with back-propagation of errors can distinguish between spectra of oligosaccharides that differ by only one glycosyl residue in twenty. The artificial neural networks use features of the strongly overlapping region of the spectra (hump region) as well as features of the resolved regions of the spectra (structural reporter groups) to recognize spectra and efficiently recognized 1H-NMR spectra even when the spectra were perturbed by minor variations in their chemical shifts. Identification of spectra by neural network-based pattern recognition techniques required less than 0.1 second. It is anticipated that artificial neural networks can be used to identify the structures of any complex carbohydrate that has been previously characterized and for which a 1H-NMR spectrum is available.
Research Interests: Artificial Intelligence, Hydrogen, Pattern Recognition, Back Propagation, Science, and 12 moreNuclear Magnetic Resonance, Polysaccharides, Magnetic Resonance Spectroscopy, Neural Network, Multidisciplinary, Glucans, Spectrum, Xylans, Chemical Shift, Artificial Neural Network, Oligosaccharides, and Feed Forward Neural Network
Abstract The sceptical inheritance nets introduced in Horty et al.[Proceedings of AAAI-87 (1987): 358-363] are translated into a version of Nute's defeasible logic. Moreover this translation is modular in the sense of Thomason and... more
Abstract The sceptical inheritance nets introduced in Horty et al.[Proceedings of AAAI-87 (1987): 358-363] are translated into a version of Nute's defeasible logic. Moreover this translation is modular in the sense of Thomason and Horty [Non-Monotonic Reasoning. ...
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Research Interests: Decision Making, Agent Based, Ecosystem management, Multidisciplinary, Knowledge Based System, and 11 moreDecision support system, Software modelling and simulation, Graphic User Interface Design, Visual System, Forest ecosystem, Model Management, Blackboard Architecture, Support System, Simulation Model, Rule Based, and Vegetative Growth
We propose development of an argument-based decision support system utilizing defeasible or nonmonotonic reasoning. Defeasible logic graphs (d-graphs) represent the knowledge contained in a defeasible theory. A method for propagating... more
We propose development of an argument-based decision support system utilizing defeasible or nonmonotonic reasoning. Defeasible logic graphs (d-graphs) represent the knowledge contained in a defeasible theory. A method for propagating labels through a d-graph is developed as a means for reasoning about the theory from which the d-graph is generated. This method is proven to be sound with respect to
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Decision making for forest ecosystem management can include the use of a wide variety of modeling tools. These tools include vegetation growth models, wildlife models, silvicultural models, GIS, and visualization tools. NED-2 is a robust,... more
Decision making for forest ecosystem management can include the use of a wide variety of modeling tools. These tools include vegetation growth models, wildlife models, silvicultural models, GIS, and visualization tools. NED-2 is a robust, intelligent, goal-driven decision support system that integrates tools in each of these categories. NED-2 uses a blackboard architecture and a set of semi-autonomous agents to manage these tools for the user. The blackboard integrates a Microsoft Access database and Prolog clauses, and the agents are implemented in Prolog. A graphical user interface written in Visual C++ provides powerful inventory analysis tools; dialogs for selecting timber, water, ecological, wildlife, and visual goals; and dialogs for defining treatments and building prescriptive management plans. Users can simulate management plans and perform goal analysis on different views of the management unit, where a view is determined by a management plan and a point in time. Prolog ag...
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Research Interests:
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80 Methodological research at the ecoregional level-Review workshop Methodologies for Integrating Data Across Geographic Scales in a Data ... To date, census data and ad hoc household surveys have been primary mechanisms for inventorying... more
80 Methodological research at the ecoregional level-Review workshop Methodologies for Integrating Data Across Geographic Scales in a Data ... To date, census data and ad hoc household surveys have been primary mechanisms for inventorying a landscape resource base. ...
Mathematical models for predicting the fate of pollutants in the environment require reactivity parameter values —that is, the physical and chemical constants that govern reactivity. Although empirical structure-activity relationships... more
Mathematical models for predicting the fate of pollutants in the environment require reactivity parameter values —that is, the physical and chemical constants that govern reactivity. Although empirical structure-activity relationships have been developed that allow estimation of some constants, such relationships generally hold only within limited families of chemicals. Computer programs are under development that predict chemical reactivity strictly from molecular structure for a broad range of molecular structures. A prototype computer system called SPARC (SPARC Performs Automated Reasoning in Chemistry) uses computational algorithms based on fundamental chemical structure theory to estimate a variety of reactivity parameters (e.g., equilibrium/rate constants, UV-visible absorption spectra, etc.). This capability crosses chemical family boundaries to cover a broad range of organic compounds. SPARC does not do “first principles” computation, but seeks to analyze chemical structure relative to a specific reactivity query in much the same manner in which an expert chemist would do so. Molecular structures are broken into functional units with known intrinsic reactivity. This intrinsic behavior is modified for a specific molecule in question with mechanistic perturbation models. To date, computational procedures have been developed for UV-visible light absorption spectra, ionization pKa, hydrolysis rate constants, and numerous physical properties. This paper describes the logic of the approach to chemistry prediction and provides an overview of the computational procedures. Additional papers are in preparation describing in detail the chemical models and specific applications.