Relevant bibliographies by topics / Computationat modelling

Academic literature on the topic 'Computationat modelling'

Author: Grafiati
Published: 10 December 2022
Last updated: 28 January 2023

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Journal articles on the topic "Computationat modelling"

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Kourou, K., and DI Fotiadis. "Computational Modelling in Cancer: Methods and Applications." Biomedical Data Journal 01, no. 1 (January 2015): 15–25. http://dx.doi.org/10.11610/bmdj.01103.

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Lloyd, Austin, Helen Moylan, and Joseph McDouall. "Modelling the Effect of Zero-Field Splitting on the 1H, 13C and 29Si Chemical Shifts of Lanthanide and Actinide Compounds." Magnetochemistry 5, no. 1 (January 11, 2019): 3. http://dx.doi.org/10.3390/magnetochemistry5010003.

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The prediction of paramagnetic NMR (pNMR) chemical shifts in molecules containing heavy atoms presents a significant challenge to computational quantum chemistry. The importance of meeting this challenge lies in the central role that NMR plays in the structural characterisation of chemical systems. Hence there is a need for reliable assignment and prediction of chemical shifts. In a previous study [Trends in Physical Chemistry, 17, 25–57, (2017)] we looked at the computation of pNMR chemical shifts in lanthanide and actinide complexes using a spin Hamiltonian approach. In that study we were principally concerned with molecules with S = 1/2 ground states. In the present work we extend that study by looking at the effect of zero field splitting (ZFS) for six complexes with S = 3/2 ground states. It is shown that the inclusion of ZFS can produce substantial shifts in the predicted chemical shifts. The computations presented are typically sufficient to enable assignment of experimental spectra. However for one case, in which the peaks are closely clustered, the inclusion of ZFS re-orders the chemical shifts making assignment quite difficult. We also observe, and echo, the previously reported importance of including the paramagnetic spin-orbit hyperfine interaction for 13 C and 29 Si atoms, when these are directly bound to a heavy element and thus subject to heavy-atom-light-atom effects. The necessary computations are very demanding, and more work is needed to find theoretical and computational approaches that simplify the evaluation of this term. We discuss the computation of each term required in the spin Hamiltonian. The systems we study in this work are restricted to a single heavy atom ion (one Nd(III) and five U(III) complexes), but typify some of the computational complexity encountered in lanthanide and actinide containing molecules.
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Čiegis, R., A. Dement'ev, and G. Šilko. "PARALLEL NUMERICAL MODELLING OF SHORT LASER PULSE COMPRESSION." Mathematical Modelling and Analysis 9, no. 2 (June 30, 2005): 115–26. http://dx.doi.org/10.3846/13926292.2004.9637246.

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In this paper we investigate parallel numerical algorithms for solution of the transient stimulated scattering processes. A new symmetrical splitting scheme is proposed and a parallel version is given. The efficiency of the parallel algorithm is investigated for two cases. The first one describes a case when the computation region is constant during the whole time of computations. The second one describes the initial phase of the process, when the computational region increases linearly in time. In order to distribute more evenly jobs between processors a dynamical the grid redistribution algorithm is is used. We also give a proof of one result about optimal static grid distribution in the case of linearly increased problem complexity. The results of computations are presented. They were obtained on different parallel computers and clusters of workstations. Nagrinejamas priverstines Brijueno sklaidos fokusuotuose pluoštuose uždavinio lygiagretusis skaitinis sprendimo algoritmas. Sukonstruota simetrinio skaidymo baigtiniu skirtumu schema, kurios tikslumas yra antrosios eiles. Lygiagretusis algoritmas gautas naudojant duomenu lygiagretumo paradigma. Detaliai nagrinejamas dinamiškai didejančio sudetingumo uždavinys, modeliuojantis Brijueno sklaidos procesa, kai neužduodama kraštine salyga Stokso bangai. Irodyta hipoteze apie vieno stacionaraus blokinio duomenu paskirstymo algoritmo op‐timaluma. Eksperimentiškai ištirtas dinaminis duomenu perskirstymo algoritmas, patvirtintas jo efektyvumas net ir fiksuoto dydžio uždaviniams. Darbe pateikti skaitinio eksperimento, atlikto naudojant VGTU 20 procesoriu klasteri, rezultatai. Jie patvirtino gautuosius teorinius rezultatus, išsam us fizikiniai rezultatai bus išspausdinti kituose darbuose.
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Dayan, P. "Computational modelling." Current Opinion in Neurobiology 4, no. 2 (1994): 212–17. http://dx.doi.org/10.1016/0959-4388(94)90075-2.

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Nivelkar, Mukta, and S. G. Bhirud. "Modeling of Supervised Machine Learning using Mechanism of Quantum Computing." Journal of Physics: Conference Series 2161, no. 1 (January 1, 2022): 012023. http://dx.doi.org/10.1088/1742-6596/2161/1/012023.

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Abstract Mechanism of quantum computing helps to propose several task of machine learning in quantum technology. Quantum computing is enriched with quantum mechanics such as superposition and entanglement for making new standard of computation which will be far different than classical computer. Qubit is sole of quantum technology and help to use quantum mechanism for several tasks. Tasks which are non-computable by classical machine can be solved by quantum technology and these tasks are classically hard to compute and categorised as complex computations. Machine learning on classical models is very well set but it has more computational requirements based on complex and high-volume data processing. Supervised machine learning modelling using quantum computing deals with feature selection, parameter encoding and parameterized circuit formation. This paper highlights on integration of quantum computation and machine learning which will make sense on quantum machine learning modeling. Modelling of quantum parameterized circuit, Quantum feature set design and implementation for sample data is discussed. Supervised machine learning using quantum mechanism such as superposition and entanglement are articulated. Quantum machine learning helps to enhance the various classical machine learning methods for better analysis and prediction using complex measurement.
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Jain, Rishabh. "Review on Computational Bioinformatics and Molecular Modelling: Novel Tool for Drug Discovery." International Journal of Trend in Scientific Research and Development Volume-3, Issue-1 (December 31, 2018): 51–56. http://dx.doi.org/10.31142/ijtsrd18914.

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Okeke, Saviour I., Noel M. Harrison, and Mingming Tong. "Computational modelling of dynamic recrystallisation of Ni-based superalloy during linear friction welding." International Journal of Advanced Manufacturing Technology 119, no. 7-8 (January 12, 2022): 4461–84. http://dx.doi.org/10.1007/s00170-021-08559-1.

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AbstractLinear friction welding (LFW) is an advanced joining technology used for manufacturing and repairing complex assemblies like blade integrated disks (blisks) of aeroengines. This paper presents an integrated multiphysics computational modelling for predicting the thermomechanical-microstructural processes of IN718 alloy (at the component-scale) during LFW. Johnson–Mehl–Avrami-Kolmogorov (JMAK) model was implemented for predicting the dynamic recrystallisation of γ grain, which was coupled with thermomechanical modelling of the LFW process. The computational modelling results of this paper agree well with experimental results from the literature in terms of γ grain size and weld temperature. Twenty different LFW process parameter configurations were systematically analysed in the computations by using the integrated model. It was found that friction pressure was the most influential process parameter, which significantly affected the dynamic recrystallisation of γ grains and weld temperature during LFW. The integrated multiphysics computational modelling was employed to find the appropriate process window of IN718 LFW.
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Rautenbach, Christo, Julia C. Mullarney, and Karin R. Bryan. "Parallel computing efficiency of SWAN 40.91." Geoscientific Model Development 14, no. 7 (July 6, 2021): 4241–47. http://dx.doi.org/10.5194/gmd-14-4241-2021.

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Abstract. Effective and accurate ocean and coastal wave predictions are necessary for engineering, safety and recreational purposes. Refining predictive capabilities is increasingly critical to reduce the uncertainties faced with a changing global wave climatology. Simulating WAves in the Nearshore (SWAN) is a widely used spectral wave modelling tool employed by coastal engineers and scientists, including for operational wave forecasting purposes. Fore- and hindcasts can span hours to decades, and a detailed understanding of the computational efficiencies is required to design optimized operational protocols and hindcast scenarios. To date, there exists limited knowledge on the relationship between the size of a SWAN computational domain and the optimal amount of parallel computational threads/cores required to execute a simulation effectively. To test the scalability, a hindcast cluster of 28 computational threads/cores (1 node) was used to determine the computation efficiencies of a SWAN model configuration for southern Africa. The model extent and resolution emulate the current operational wave forecasting configuration developed by the South African Weather Service (SAWS). We implemented and compared both OpenMP and the Message Passing Interface (MPI) distributing memory architectures. Three sequential simulations (corresponding to typical grid cell numbers) were compared to various permutations of parallel computations using the speed-up ratio, time-saving ratio and efficiency tests. Generally, a computational node configuration of six threads/cores produced the most effective computational set-up based on wave hindcasts of 1-week duration. The use of more than 20 threads/cores resulted in a decrease in speed-up ratio for the smallest computation domain, owing to the increased sub-domain communication times for limited domain sizes.
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MUSKULUS, MICHAEL, and ROBERT BRIJDER. "COMPLEXITY OF BIO-COMPUTATION: SYMBOLIC DYNAMICS IN MEMBRANE SYSTEMS." International Journal of Foundations of Computer Science 17, no. 01 (February 2006): 147–65. http://dx.doi.org/10.1142/s0129054106003747.

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We discuss aspects of biological relevance to the modelling of bio-computation in a multiset rewriting system context: turnover, robustness against perturbations, and the dataflow programming paradigm. The systems under consideration are maximally parallel and asynchronous parallel membrane systems, the latter corresponding to computation in which the notion of time is operationally meaningless. A natural geometrical setting which seems promising for the study of computational processes in general multiset rewriting systems is presented. Configuration space corresponds to a subset of the lattice [Formula: see text], d ∈ N, and state transitions correspond to vector addition. The similarities and differences with Vector Addition Systems and Petri nets are discussed. Symbolic dynamics are introduced on special partitions of configuration space and we indicate different notions of complexity for membrane systems based on this and related concepts such as graph complexity and minimal automata. Some examples of synchronized, pipelined dataflow computations are given and decompositions into functional subunits are briefly commented on.
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Düben, Peter D., Jaume Joven, Avinash Lingamneni, Hugh McNamara, Giovanni De Micheli, Krishna V. Palem, and T. N. Palmer. "On the use of inexact, pruned hardware in atmospheric modelling." Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences 372, no. 2018 (June 28, 2014): 20130276. http://dx.doi.org/10.1098/rsta.2013.0276.

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Inexact hardware design, which advocates trading the accuracy of computations in exchange for significant savings in area, power and/or performance of computing hardware, has received increasing prominence in several error-tolerant application domains, particularly those involving perceptual or statistical end-users. In this paper, we evaluate inexact hardware for its applicability in weather and climate modelling. We expand previous studies on inexact techniques, in particular probabilistic pruning , to floating point arithmetic units and derive several simulated set-ups of pruned hardware with reasonable levels of error for applications in atmospheric modelling. The set-up is tested on the Lorenz ‘96 model, a toy model for atmospheric dynamics, using software emulation for the proposed hardware. The results show that large parts of the computation tolerate the use of pruned hardware blocks without major changes in the quality of short- and long-time diagnostics, such as forecast errors and probability density functions. This could open the door to significant savings in computational cost and to higher resolution simulations with weather and climate models.
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Dissertations / Theses on the topic "Computationat modelling"

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Gault, Richard. "Computational modelling of tinnitus." Thesis, Ulster University, 2017. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.730910.

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Tinnitus affects 10-15% of the population and causes a diminished quality of life for 1-3% of people. Without a clear understanding of the mechanisms that generate and sustain tinnitus, treatment plans can only attempt to manage the problem rather than address the underlying causes of tinnitus. As 85% of tinnitus sufferers have hearing loss, tinnitus was originally considered to be a problem of the ear. Moreover the remaining tinnitus sufferers are postulated to have hidden hearing loss. Subsequent research has found that tinnitus is a problem extending beyond the ear. Experimental findings have identified tinnitus related activity throughout the auditory system. It is unclear how this activity is created and how it leads to the perception of a phantom sound. This thesis aims to identify the factors involved in the development of tinnitus related activity and the manifestation of a phantom sound; computational models of the auditory system are developed to address this primary objective. In this thesis, a biologically inspired model of the auditory periphery is created, called the peripheral model, which emulates tinnitus related activity in the auditory brainstem and accurately models hidden hearing loss in line with empirical data. The peripheral model is extended to model correlates of tinnitus associated with the thalamocortical network. Finally a perceptual model of tinnitus is developed using a Linear Mixed Effects (LME) approach to show how tinnitus related activity leads to the perception of a phantom sound. The outcomes from the development of the peripheral model include an accurate model of cochlear synaptopathy to replicate hidden hearing loss as well as the finding that hidden hearing loss can instigate adaptive changes that result in tinni­tus related activity. Extending the peripheral model to include the thalamocortical network led to the discovery that tinnitus requires changes to both the bottom-up and top-down signals in the auditory system. The result provides a significant step forward towards understanding the mechanisms underpinning tinnitus related activity. The peripheral model and the result from the investigation of the thalamocortical network provide the underpinning basis upon which to develop the perceptual model of tinnitus using a LME approach. The LME model provides a state of the art perceptual model of tinnitus that accurately models characteristics of tinnitus such as pitch and loudness. The results provide a significant advance­ment in the understanding of tinnitus generation and the evidence to motivate and direct further studies, which could lead to improved treatment methods for this condition.
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Engelhardt, Markus Jochen. "Computational modelling of shakedown." Thesis, University of Leicester, 1999. http://hdl.handle.net/2381/30173.

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The work presented is concerned with the implementation and exploitation of an iterative non-linear programming technique, based on the elastic compensation method, for solving limit load and shakedown problems. Such solutions are required in the design of structures or components subjected to complex combinations of static and cyclic loading, in structural integrity procedures and life cycle assessment. To achieve these aims, a brief review of the problem, the historical development of shakedown theory and recent developments of methods addressing these issues are given in the early chapters. This is followed by the implementation of the above method to generate limit load solutions for elastic-plastic materials subject to the von Mises yield condition. The method was found to be numerically stable and convergence could be guaranteed for upper bound limit load solutions if a number of sufficient convergence criteria are adhered to. These are stated during the provided convergence proofs. Upon studying the behaviour of the method, i.e. quality and sensitivity of solutions, computational effort as well as identifying error sources, this implementation is extended to solve limit load problems for arbitrary yield surfaces. This was found to be possible, but dependent on the nature of the yield surface and limits to the implementation in its present form were identified. The method was then implemented using a different formulation capable of solving limit and, more importantly, shakedown problems for elastic-plastic materials subject to the von Mises yield criterion. A number of benchmark problems were considered, an example of which is the classic Bree problem, which is concerned with shakedown of components subjected to a static mechanical load in combination with thermal transients. The method performed well and was then used to solve novel shakedown problems, such as shakedown states where creep must be considered. Acceptable creep behaviour for a given shakedown state could also be calculated using minor additions. The final issue considered was cyclic creep solutions. Rapid cycle creep solutions could be generated as a stress history can be considered, which is of a similar form to shakedown. Finally, conclusions were drawn and remaining issues discussed.
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Baird, Scott. "Computational modelling of fuel cells." Thesis, Loughborough University, 2001. https://dspace.lboro.ac.uk/2134/10917.

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Industrial applications of fuel cell technologies offer a major research opportunity. To realise the goal of practical commercial applications of this developing technology will involve the integration of the latest developments in electrical, fluid and chemical engineering systems. Although each field is well developed in its own right, the novel concept of combining these technologies within computational models offers the potential for new understanding and design procedures to be created. This multi-disciplinary approach would offer new insights into the fundamental physical phenomena, as well as creating tools that can be used for designing fuel cells and is the major focus of the research described in this thesis. Power storage fuel cells are the subject of this research. This particular fuel cell is a bipolar stack with two, single phase, liquid electrolytes. A review of the current techniques highlighted the need to address the study of the loss mechanisms present in the fuel cell. The prediction of short circuits created by the electrically conductive fluids required an electrical model. The power consumed driving the fluid system compelled a fluid dynamics model. These were combined within this work, to optimise the geometrical properties of this type of fuel cell based on general chemical kinetic and operating parameters. In order to satisfy the operating requirement of even distribution of reactants to the active areas, a finite-volume technique based on a computational fluid dynamics (CFD) code was developed. This enabled the prediction of the transport processes for fluid flow, electrical energy transfer and chemical species conversion throughout the fuel cell. The complexity of the multi-disciplinary CFD method required the use of parallel computers to reduce the lead times. The CFD approach is employed best studying small sections of the fuel cell system highlighting important phenomena. This research has already influenced design variations and has guided the direction of additional research, namely ways of electrically isolating the fluid without interrupting the flow. This work has successfully demonstrated that computational modelling can predict fuel cell electrochemical phenomena in a fraction of the time and cost of experimental procedures. This research is being used to benefit the design process and further the exploitation of fuel cell technologies. Finally, by extending the research into porous media and two phase flow these techniques could be applied to all types of fuel cell.
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Ioannou, Panagiotis. "Computational modelling of working memory." Thesis, University of Surrey, 2014. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.658622.

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Computational modelling empowers scientists to test hypotheses that they could not have done so otherwise, mainly because of the complexity of the system to be tested. In order to investigate particular postulates, computational neuroscientists build quantitative models of the central nervous system in great detail, and in different levels of organisation. In this thesis, by simulating morphologically reconstructed neurons and composing networks consisting of these neurons, we investigate and aim to bridge the gap between neuroscientific hypotheses and levels of organisation. All of our investigations fall under, but are not limited to, the working memory concept, a theoretical system designed to address the information processing in order to achieve cognition. To begin with, we investigate macroscopic neural oscillations as observed during working memory tasks. We show the criticality of inter-regional delay coupling effect on synchronisation phase-shift, and that near zero-lag synchronisation can be achieved via the M3 structural motif. After showing that spiking neurons can successfully model macroscopic phenomena, we focus on the microscopic level, where we simulate a number of interconnecting neurons and proceed to scrutinise their complex behaviour and the information processing capabilities they exhibit. Specifically, we explore the effect of spiking network parameters on polychronization and the sustainability of spikes based on short-term synaptic dynamics. We show that the models are extremely sensitive to neuronal parameters including type of connectivity, axonal delays, density and topology. In the end we investigate two contradicting theories of forgetting in short term memory: the temporal and the non-temporal approaches. We show that the sustained representation of memory cues highly depend on the size of their neuronal counterparts, and that both the temporal and the non temporal approaches can have a role to play in sustaining information, and that they do not necessarily contradict each other.
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Narbutas, Vilius. "Computational modelling of visual search." Thesis, University of Birmingham, 2018. http://etheses.bham.ac.uk//id/eprint/8772/.

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Visual search traditionally has two main competing theories of parallel and serial search and this architectural issue has not been solved to this day. The latest developments in the field have suggested a possibility that response time distributions may aid in differentiating the two competing theories. For this purpose we have used the best available serial model Competitive Guided Search and two biologically-plausible parallel models inspired by the theory of biased competition. The parallel models adopted a winner-take-all mechanism from Selective Attention for Identification Model as base model that was extended to form a novel model for explaining response time distributions. These models are analytically intractable, therefore we adopted a more accurate kernel density estimator for representing unknown probability density function. Introduced robustness properties to the fitness method and developed a more efficient algorithm for finding the parameter solutions. Then these methods were applied for comparison of the respective models and concluded that winner-takes-all model poorly generalises to response time distributions. The results were followed by introducing a novel Asymmetrical Dynamic Neural Network model that managed to explain distributional changes better than Competitive Guided Search model.
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Sheppard, Terence. "Computational modelling of multiphase catalysis." Thesis, Queen's University Belfast, 2015. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.676713.

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Simulating heterogeneous catalytic processes occurring at solid-liquid interfaces requires the use of quantum mechanical methods to allow for a description of bond breaking and bond forming. These methods must also allow a sufficiently sized statistical sampling of the liquid to be gathered. Current approaches based on density functional theory (DFT) are too expensive to satisfy these requirements so it is therefore desirable to develop alternative, faster methods. Self consistent tight binding (TB) methods, which are derived from a second-order expansion of the Kohn-Sham energy functional and use a parametrised Hamiltonian matrix, can be significantly faster than DFT making them ideal for the above task. In this thesis we describe the development of a TB model for organic molecules containing carbon, hydrogen and oxygen. This model has been fitted using a combination of intuition, analytical fitting and genetic optimisation. We have also developed a framework for the description of inter-molecular Van der Waals interactions using long-ranged empirical potentials. We have shown that this model is capable of describing the gas-phase structural and dynamic properties of a range of organic molecules, as well as the structure and dynamics of liquid-phase alcohols and solvated organic molecules. We have also shown how the the model can be used to describe chemical reactions in solution. The model forms part of a larger collection which also includes models for water and titania. All models within this collection share a single transferable oxygen species. When combined with a parametrisation of a metal such as platinum this collection could be used for the study of catalytic processes.
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Bauer, Paul. "Computational modelling of enzyme selectivity." Doctoral thesis, Uppsala universitet, Struktur- och molekylärbiologi, 2017. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-326108.

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Enantioselective reactions are one of the ways to produce pure chiral compounds. Understanding the basis of this selectivity makes it possible to guide enzyme design towards more efficient catalysts. One approach to study enzymes involved in chiral chemistry is through the use of computational models that are able to simulate the chemical reaction taking place. The potato epoxide hydrolase is one enzyme that is known to be both highly enantioselective, while still being robust upon mutation of residues to change substrate scope. The enzyme was used to investigate the epoxide hydrolysis mechanism for a number of different substrates, using the EVB approach to the reaction both in solution and in several enzyme variants. In addition to this, work has been performed on new ways of performing simulations of divalent transition metals, as well as development of new simulation software.
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Boyett, Robin Ernest. "Computational studies of hydrophobic porphyrins." Thesis, University of Sussex, 1994. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.241621.

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Kite, Matthew J. S. "Computational modelling of clay pipe extrusion." Thesis, Available from the University of Aberdeen Library and Historic Collections Digital Resources. Online version available for University members only until June 9, 2014, 2009. http://digitool.abdn.ac.uk:80/webclient/DeliveryManager?application=DIGITOOL-3&owner=resourcediscovery&custom_att_2=simple_viewer&pid=25966.

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Sandström, Malin. "Computational Modelling of Early Olfactory Processing." Doctoral thesis, KTH, Beräkningsbiologi, CB, 2010. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-12090.

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Chemical sensing is believed to be the oldest sensory ability. The chemical senses, olfaction and gustation, developed to detect and analyze information in the form of air- or waterborne chemicals, to find food and mates, and to avoid danger. The organization of the olfactory system follows the same principles in almost all living animals, insects as well as mammals. Likely, the similarities are due to parallel evolution – the same type of organisation seems to have arisen more than once. Therefore, the olfactory system is often assumed to be close to optimally designed for its tasks.Paradoxically, the workings of the olfactory system are not yet well known,although several milestone discoveries have been made during the last decades. The most well-known is probably the disovery of the olfactory receptor gene family,announced in 1991 by Linda Buck and Richard Axel. For this and subsequent work, they were awarded a Nobel Prize Award in 2004. This achievement has been of immense value for both experimentalists and theorists, and forms the basis of the current understanding of olfaction. The olfactory system has long been a focus for scientific interest within several fields, both experimental and theoretical, and it has often been used asa model system. And ever since the field of computational neuroscience was founded, the functions of the olfactory system have been investigated through computational modelling. In this thesis, I present several approaches to biologically realistic computational models of parts of the olfactory system, with an emphasis on the earlier stages of the vertebrate olfactory system – olfactory receptor neurons (ORNs) and the olfactory bulb (OB). I have investigated the behaviour of the enzyme CaMKII, which is known to be critical for olfactory adaptation (suppression of constant odour stimuli) in the ORN, using a biochemical model. By constructing several OB models of different size, I have shown that the size of the OB network has an impact on its ability to process noisy information. Taking into account the reported variability of geometrical, electrical and receptor-dependent neuronal characteristics, I have been able to model the frequency response of a population of ORNs. I have used this model to find the key properties that govern most of the ORN population’s response, and investigated some of the possible implications of these key properties in subsequent studies of the ORN population and the OB – what we call the fuzzy concentration coding hypothesis.
Detektion av kemiska ämnen anses allmänt vara den äldsta sensoriska förmågan. De kemiska sinnena, lukt och smak, utvecklades för att upptäcka och analysera kemisk information i form av luft- eller vattenburna ämnen, för att hitta mat och partners, och för att undvika fara. Luktsystemet är organiserat efter samma principer hos nästan alla djurarter, insekter såväl som däggdjur. Troligen beror likheterna på parallell evolution – samma organisation verkar ha uppstått mer än en gång. Därför antas det ofta att luktsystemet är nära optimalt anpassat för sina arbetsuppgifter.Paradoxalt nog är luktsystemets arbetsprinciper ännu inte väl kända, även om flera banbrytande framsteg gjorts de senaste decennierna. Det mest välkända är nog upptäckten av genfamiljen av luktreceptorer, som tillkännagavs 1991 av Linda Buck och Rikard Axel. För detta och efterföljande arbete belönades de med Nobelpriset år 2004. Upptäckten har varit mycket värdefull för både experimentalister och teoretiker, och är grunden för vår nuvarande förståelse av luktsystemet. Luktsystemet har länge varit ett fokus för vetenskapligt intresse inom flera fält, experimentella såväl som teoretiska, och har ofta använts som ett modellsystem. Och ända sedan fältet beräkningsneurobiologi grundades har luktsystemet undersökts genom datormodellering. I denna avhandling presenterar jag flera ansatser till biologiskt realistiskaberäkningsmodeller av luktsystemet, med tonvikt på de tidigare delarna av ryggradsdjurens luktsystem – luktreceptorceller och luktbulben. Jag har undersökt beteendet hos enzymet CaMKII, som anses vara kritiskt viktigt för adaptation (undertryckning av ständigt närvarande luktstimuli) i luktsystemet, i en biokemisk modell. Genom att konstruera flera olika stora modeller av luktbulben har jag visat att storleken på luktbulbens cellnätverk påverkar dess förmåga att behandla brusig information. Genom att ta hänsyn till nervcellernas rapporterade variationer i geometriska, elektriska och receptor-beroende karaktärsdrag har jag lyckats modellera svarsfrekvenserna från en population av luktreceptorceller. Jag har använt denna modell för att hitta de nyckelprinciper som styr huvuddelen av luktreceptorneuron-populationens svar, ochundersökt några av de tänkbara konsekvenserna av dessa nyckelprinciper i efterföljande studier av luktreceptorneuron-populationen och luktbulben – det vi kallar ”fuzzy concentration coding”-hypotesen.
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Books on the topic "Computationat modelling"

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Bailey, Chris. Computational modelling. Edited by ebrary Inc. Bradford, England: Emerald Group Publishing, 2002.

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Gengnagel, Christoph, Axel Kilian, Norbert Palz, and Fabian Scheurer, eds. Computational Design Modelling. Berlin, Heidelberg: Springer Berlin Heidelberg, 2012. http://dx.doi.org/10.1007/978-3-642-23435-4.

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Billari, Francesco C., Thomas Fent, Alexia Prskawetz, and Jürgen Scheffran, eds. Agent-Based Computational Modelling. Heidelberg: Physica-Verlag HD, 2006. http://dx.doi.org/10.1007/3-7908-1721-x.

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de, Borst René, Mang Herbert, and Meschke Günther, eds. Computational Modelling of Concrete Structures. Abingdon: CRC Press [Imprint], 2010.

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Rashad, M. A. A. Computational modelling of gravity settlers. Manchester: UMIST, 1995.

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Ali, Irfan, Prasenjit Chatterjee, Ali Akbar Shaikh, Neha Gupta, and Ali AlArjani, eds. Computational Modelling in Industry 4.0. Singapore: Springer Singapore, 2022. http://dx.doi.org/10.1007/978-981-16-7723-6.

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Giugliano, Michele, Mario Negrello, and Daniele Linaro, eds. Computational Modelling of the Brain. Cham: Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-030-89439-9.

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Giugliano, Michele, Mario Negrello, and Daniele Linaro, eds. Computational Modelling of the Brain. Cham: Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-030-89439-9.

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Giugliano, Michele, Mario Negrello, and Daniele Linaro, eds. Computational Modelling of the Brain. Cham: Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-030-89439-9.

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Murín, Justín, Vladimír Kompiš, and Vladimír Kutiš, eds. Computational Modelling and Advanced Simulations. Dordrecht: Springer Netherlands, 2011. http://dx.doi.org/10.1007/978-94-007-0317-9.

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Book chapters on the topic "Computationat modelling"

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Yao, Xin. "Evolving Computational Neural Networks Through Evolutionary Computation." In GeoComputational Modelling, 35–70. Berlin, Heidelberg: Springer Berlin Heidelberg, 2001. http://dx.doi.org/10.1007/978-3-662-04637-1_3.

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Simos, T. E. "Atomic structure computations." In Chemical Modelling, 38–142. Cambridge: Royal Society of Chemistry, 2007. http://dx.doi.org/10.1039/9781847553317-00038.

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Kondinski, Aleksandar. "Computational modelling of isomeric polyoxometalates." In Chemical Modelling, 39–71. Cambridge: Royal Society of Chemistry, 2021. http://dx.doi.org/10.1039/9781839162657-00039.

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Besseling, J. F., and E. Van Der Giessen. "Computational aspects." In Mathematical Modelling of Inelastic Deformation, 126–90. Boston, MA: Springer US, 1994. http://dx.doi.org/10.1007/978-1-4899-7186-9_5.

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Wright, N. G., and D. M. Hargreaves. "Environmental Applications of Computational Fluid Dynamics." In Environmental Modelling, 91–109. Chichester, UK: John Wiley & Sons, Ltd, 2013. http://dx.doi.org/10.1002/9781118351475.ch6.

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Kasabov, Nikola K. "Computational Neuro-genetic Modelling." In Springer Series on Bio- and Neurosystems, 545–61. Berlin, Heidelberg: Springer Berlin Heidelberg, 2018. http://dx.doi.org/10.1007/978-3-662-57715-8_16.

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Rothkegel, Annely. "Computational Modelling of Dialogue." In Concepts of dialogue, edited by Edda Weigand, 123–44. Berlin, Boston: De Gruyter, 1994. http://dx.doi.org/10.1515/9783111332062-008.

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Masouros, Spyros D., and Daniel J. Pope. "Fundamentals of Computational Modelling." In Blast Injury Science and Engineering, 61–79. Cham: Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-031-10355-1_5.

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Rosen, Ori, and Ayala Cohen. "Computational Aspects in Maximum Penalized Likelihood Estimation." In Statistical Modelling, 257–65. New York, NY: Springer New York, 1995. http://dx.doi.org/10.1007/978-1-4612-0789-4_32.

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Hosoe, Nobuhiro, Kenji Gasawa, and Hideo Hashimoto. "Computation." In Textbook of Computable General Equilibrium Modelling, 23–40. London: Palgrave Macmillan UK, 2010. http://dx.doi.org/10.1057/9780230281653_3.

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Conference papers on the topic "Computationat modelling"

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Li, Yan. "Opportunities for quantum computation in computational fluid dynamics." In 2nd International Conference on Applied Mathematics, Modelling, and Intelligent Computing (CAMMIC 2022), edited by Chi-Hua Chen, Xuexia Ye, and Hari Mohan Srivastava. SPIE, 2022. http://dx.doi.org/10.1117/12.2639351.

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Derbal, Youcef. "Computational Modeling of Estrogen Metabolism." In Modelling and Simulation. Calgary,AB,Canada: ACTAPRESS, 2013. http://dx.doi.org/10.2316/p.2013.802-046.

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Su, Yu, Jingyu Wang, Ke Zhang, Kurosh Madani, and Xianyu Wang. "Computational Modelling Auditory Awareness." In 10th International Joint Conference on Computational Intelligence. SCITEPRESS - Science and Technology Publications, 2018. http://dx.doi.org/10.5220/0006925401600167.

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Fish, Jacob, Vasilina Filonova, and Zheng Yuan. "Reduced Order Computational Continua." In 25th Conference on Modelling and Simulation. ECMS, 2011. http://dx.doi.org/10.7148/2011-0007-0010.

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McGough, J. S., A. W. Christianson, and R. C. Hoover. "Symbolic Computation of Lyapunov Functions using Evolutionary Algorithms." In Modelling and Simulation. Calgary,AB,Canada: ACTAPRESS, 2010. http://dx.doi.org/10.2316/p.2010.697-093.

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Sinton, D. A., and B. R. Baliga. "Computational Modelling of Continuous Casting." In ASME 2003 International Mechanical Engineering Congress and Exposition. ASMEDC, 2003. http://dx.doi.org/10.1115/imece2003-43967.

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Computer simulations of fluid flow and heat transfer phenonmena in a continuous casting process with direct-chill (DC) boundary conditions are presented and discussed in this paper. The investigation is limited to a steady-state, two-dimensional axisymmetric system, used for DC continuous casting of a zero-freezing-range aluminum-magnesium alloy (A6063). An adaptive-grid numerical method is used in these simulations. The grid is designed to delineate the solid-liquid interface using a structured adaptation technique. The fluid flow and thermal fields are predicted using a control-volume finite element (CVFEM). Comparisons of the calculated solid-liquid interface geometries with those reported in earlier experimental and numerical studies are presented in this paper. In addition, the role of natural convection in this casting process is investigated and presented.
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Schnase, J. L., and J. J. Leggett. "Computational hypertext in biological modelling." In the second annual ACM conference. New York, New York, USA: ACM Press, 1989. http://dx.doi.org/10.1145/74224.74240.

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Betechuoh, Brain Leke, Tshilidzi Marwala, and Jabulile V. Manana. "Computational Intelligence for HIV Modelling." In 2008 International Conference on Intelligent Engineering Systems. IEEE, 2008. http://dx.doi.org/10.1109/ines.2008.4481281.

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Fernandes, Paulo R., and Marta R. Dias. "Computational modelling in bone mechanics." In 2011 1st Portuguese Meeting in Bioengineering ¿ The Challenge of the XXI Century (ENBENG). IEEE, 2011. http://dx.doi.org/10.1109/enbeng.2011.6026079.

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Schaette, Roland. "Computational modelling of tinnitus development." In ICA 2013 Montreal. ASA, 2013. http://dx.doi.org/10.1121/1.4799582.

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Reports on the topic "Computationat modelling"

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Miller, Willard, Sell Jr., Weinberger George, and Hans. Scientific Computation and Mathematical Modelling. Fort Belvoir, VA: Defense Technical Information Center, February 1986. http://dx.doi.org/10.21236/ada173178.

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Paolucci, Samuel, and Joseph M. Powers. A Novel Computational Approach to Combustion Modelling. Fort Belvoir, VA: Defense Technical Information Center, June 2001. http://dx.doi.org/10.21236/ada400632.

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Simon, Tony. Modelling Conceptual Development: A computational Account of Conservation Learning. Fort Belvoir, VA: Defense Technical Information Center, February 1990. http://dx.doi.org/10.21236/ada225800.

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Avdjieva, Irena, Ivan Terziyski, Gergana Zahmanova, Valeria Simeonova, Ognyan Kulev, Evgeny Krustev, Milko Krachunov, Maria Nisheva, and Dimitar Vassilev. Homology Based Computational Modelling of Hepatitis-E Viral Fusion Capsid Protein. Balkan, Black sea and Caspian sea Regional Network for Space Weather Studies, March 2019. http://dx.doi.org/10.7546/crabs.2019.03.10.

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Zheng, Jinhui, Matteo Ciantia, and Jonathan Knappett. On the efficiency of coupled discrete-continuum modelling analyses of cemented materials. University of Dundee, December 2021. http://dx.doi.org/10.20933/100001236.

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Computational load of discrete element modelling (DEM) simulations is known to increase with the number of particles. To improve the computational efficiency hybrid methods using continuous elements in the far-field, have been developed to decrease the number of discrete particles required for the model. In the present work, the performance of using such coupling methods is investigated. In particular, the coupled wall method, known as the “wall-zone” method when coupling DEM and the continuum Finite Differences Method (FDM) using the Itasca commercial codes PFC and FLAC respectively, is here analysed. To determine the accuracy and the efficiency of such a coupling approach, 3-point bending tests of cemented materials are simulated numerically. To validate the coupling accuracy first the elastic response of the beam is considered. The advantage of employing such a coupling method is then investigated by loading the beam until failure. Finally, comparing the results between DEM, DEM-FDM coupled and FDM models, the advantages and disadvantages of each method are outlined.
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Giljarhus, Knut Erik Teigen. Disc Golf Trajectory Modelling Combining Computational Fluid Dynamics and Rigid Body Dynamics. Purdue University, 2022. http://dx.doi.org/10.5703/1288284317502.

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Millis, Andrew. Many Body Methods from Chemistry to Physics: Novel Computational Techniques for Materials-Specific Modelling: A Computational Materials Science and Chemistry Network. Office of Scientific and Technical Information (OSTI), November 2016. http://dx.doi.org/10.2172/1332662.

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Perdigão, Rui A. P. Information physics and quantum space technologies for natural hazard sensing, modelling and prediction. Meteoceanics, September 2021. http://dx.doi.org/10.46337/210930.

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Disruptive socio-natural transformations and climatic change, where system invariants and symmetries break down, defy the traditional complexity paradigms such as machine learning and artificial intelligence. In order to overcome this, we introduced non-ergodic Information Physics, bringing physical meaning to inferential metrics, and a coevolving flexibility to the metrics of information transfer, resulting in new methods for causal discovery and attribution. With this in hand, we develop novel dynamic models and analysis algorithms natively built for quantum information technological platforms, expediting complex system computations and rigour. Moreover, we introduce novel quantum sensing technologies in our Meteoceanics satellite constellation, providing unprecedented spatiotemporal coverage, resolution and lead, whilst using exclusively sustainable materials and processes across the value chain. Our technologies bring out novel information physical fingerprints of extreme events, with recently proven records in capturing early warning signs for extreme hydro-meteorologic events and seismic events, and do so with unprecedented quantum-grade resolution, robustness, security, speed and fidelity in sensing, processing and communication. Our advances, from Earth to Space, further provide crucial predictive edge and added value to early warning systems of natural hazards and long-term predictions supporting climatic security and action.
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de Kemp, E. A., H. A. J. Russell, B. Brodaric, D. B. Snyder, M. J. Hillier, M. St-Onge, C. Harrison, et al. Initiating transformative geoscience practice at the Geological Survey of Canada: Canada in 3D. Natural Resources Canada/CMSS/Information Management, 2022. http://dx.doi.org/10.4095/331097.

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Application of 3D technologies to the wide range of Geosciences knowledge domains is well underway. These have been operationalized in workflows of the hydrocarbon sector for a half-century, and now in mining for over two decades. In Geosciences, algorithms, structured workflows and data integration strategies can support compelling Earth models, however challenges remain to meet the standards of geological plausibility required for most geoscientific studies. There is also missing links in the institutional information infrastructure supporting operational multi-scale 3D data and model development. Canada in 3D (C3D) is a vision and road map for transforming the Geological Survey of Canada's (GSC) work practice by leveraging emerging 3D technologies. Primarily the transformation from 2D geological mapping, to a well-structured 3D modelling practice that is both data-driven and knowledge-driven. It is tempting to imagine that advanced 3D computational methods, coupled with Artificial Intelligence and Big Data tools will automate the bulk of this process. To effectively apply these methods there is a need, however, for data to be in a well-organized, classified, georeferenced (3D) format embedded with key information, such as spatial-temporal relations, and earth process knowledge. Another key challenge for C3D is the relative infancy of 3D geoscience technologies for geological inference and 3D modelling using sparse and heterogeneous regional geoscience information, while preserving the insights and expertise of geoscientists maintaining scientific integrity of digital products. In most geological surveys, there remains considerable educational and operational challenges to achieve this balance of digital automation and expert knowledge. Emerging from the last two decades of research are more efficient workflows, transitioning from cumbersome, explicit (manual) to reproducible implicit semi-automated methods. They are characterized by integrated and iterative, forward and reverse geophysical modelling, coupled with stratigraphic and structural approaches. The full impact of research and development with these 3D tools, geophysical-geological integration and simulation approaches is perhaps unpredictable, but the expectation is that they will produce predictive, instructive models of Canada's geology that will be used to educate, prioritize and influence sustainable policy for stewarding our natural resources. On the horizon are 3D geological modelling methods spanning the gulf between local and frontier or green-fields, as well as deep crustal characterization. These are key components of mineral systems understanding, integrated and coupled hydrological modelling and energy transition applications, e.g. carbon sequestration, in-situ hydrogen mining, and geothermal exploration. Presented are some case study examples at a range of scales from our efforts in C3D.
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Bonatti, Piero, Carsten Lutz, and Frank Wolter. Expressive Non-Monotonic Description Logics Based on Circumscription. Technische Universität Dresden, 2005. http://dx.doi.org/10.25368/2022.149.

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Recent applications of description logics (DLs) strongly suggest the integration of non-monotonic features into DLs, with particular attention to defeasible inheritance. However, the existing non-monotonic extensions of DLs are usually based on default logic or autoepistemic logic, and have to be seriously restricted in expressive power to preserve the decidability of reasoning. In particular, such DLs allow the modelling of defeasible inheritance only in a very restricted form, where non-monotonic reasoning is limited to individuals that are explicitly identified by constants in the knowledge base. In this paper, we consider non-monotonic extensions of expressive DLs based on circumscription. We prove that reasoning in such DLs is decidable even without the usual, strong restrictions in expressive power. We pinpoint the exact computational complexity of reasoning as complete for NPNEXP and NEXPNP, depending on whether or not the number of minimized and fixed predicates is assumed to be bounded by a constant. These results assume that only concept names (and no role names) can be minimized and fixed during minimization. On the other hand, we show that fixing role names during minimization makes reasoning undecidable.
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