Efficient Monte Carlo computation of Fisher information matrix using prior information

The Fisher information matrix (FIM) is a critical quantity in several aspects of mathematical modeling, including input selection and confidence region calculation. Analytical determination of the FIM in a general setting, especially in nonlinear models, may be difficult or almost impossible due to intractable modeling requirements or/and intractable high-dimensional integration.To circumvent these difficulties, a Monte Carlo simulation based technique, known as resampling algorithm, is usually recommended, in which values of the log-likelihood function or its exact stochastic gradient computed based on a set of pseudo-data vectors are used. The current work proposes an extension of this resampling algorithm in order to enhance the statistical qualities of the estimator of the FIM. This modified resampling algorithm is useful in those cases when some elements of the FIM are analytically known from prior information and the rest of the elements are unknown. The estimator of the FIM resulting from the proposed algorithm simultaneously preserves the analytically known elements and reduces variances of the estimators of the unknown elements. This is achieved by capitalizing on the information contained in the known elements.     

Inferring Phylogenetic Trees Using Answer Set Programming

We describe the reconstruction of a phylogeny for a set of taxa, with a character-based cladistics approach, in a declarative knowledge representation formalism, and show how to use computational methods of answer set programming to generate conjectures about the evolution of the given taxa. We have applied this computational method in two domains: historical analysis of languages and historical analysis of parasite-host systems. In particular, using this method, we have computed some plausible phylogenies for Chinese dialects, for Indo-European language groups, and for Alcataenia species. Some of these plausible phylogenies are different from the ones computed by other software. Using this method, we can easily describe domain-specific information (e.g., temporal and geographical constraints), and thus prevent the reconstruction of some phylogenies that are not plausible. This paper is a revised and extended version of [3].     

Recognition of emergent human behaviour in a smart home: A data mining approach

Motivated by a growing need for intelligent housing to accommodate ageing populations, we propose a novel application of intertransaction association rule (IAR) mining to detect anomalous behaviour in smart home occupants. An efficient mining algorithm that avoids the candidate generation bottleneck limiting the application of current IAR mining algorithms on smart home data sets is detailed. An original visual interface for the exploration of new and changing behaviours distilled from discovered patterns using a new process for finding emergent rules is presented. Finally, we discuss our observations on the emergent behaviours detected in the homes of two real world subjects.     

Model simplification for switched hybrid systems

This paper is concerned with the problem of model reduction for switched system, which is an important class of hybrid systems frequently encountered in practical situations. Two sharply different approaches are proposed to solve this problem. The first approach casts the model reduction into a convex optimization problem, which is the first attempt to solve the model reduction problem by using linearization procedure. The second one, based on the cone complementarity linearization idea, casts the model reduction problem into a sequential minimization problem subject to linear matrix inequality constraints. Both approaches have their own advantages and disadvantages concerning conservatism and computational complexity. A numerical example illustrates the effectiveness of the proposed theories.     

Reduced-complexity nonlinear H/sup /spl infin// control of discrete-time systems

In this note, we describe a reduced-complexity solution to the nonlinear H/sup /spl infin// control problem. This reduction applies to systems where some of the states are perfectly known, and is an intermediate problem between full state feedback and the standard measurement feedback problem. The reduction of computational complexity is significant and of practical importance. Online implementation is feasible with 2003 computer technology for a range of practical engineering design problems.     

Evapotranspiration on western U.S. rivers estimated using the Enhanced Vegetation Index from MODIS and data from eddy covariance and Bowen ratio flux towers

We combined remote sensing and in-situ measurements to estimate evapotranspiration (ET) from riparian vegetation over large reaches of western U.S. rivers and ET by individual plant types. ET measured from nine flux towers (eddy covariance and Bowen ratio) established in plant communities dominated by five major plant types on the Middle Rio Grande, Upper San Pedro River, and Lower Colorado River was strongly correlated with Enhanced Vegetation Index (EVI) values from the Moderate Resolution Imaging Spectrometer (MODIS) sensor on the NASA Terra satellite. The inclusion of maximum daily air temperatures (T_a) measured at the tower sites further improved this relationship. Sixteen-day composite values of EVI and T_a were combined to predict ET across species and tower sites (r² = 0.74); the regression equation was used to scale ET for 2000-2004 over large river reaches with T_a from meteorological stations. Measured and estimated ET values for these river segments were moderate when compared to historical, and often indirect, estimates and ranged from 851-874 mm yr^− 1. ET of individual plant communities ranged more widely. Cottonwood (Populus spp.) and willow (Salix spp.) stands generally had the highest annual ET rates (1100-1300 mm yr^− 1), while mesquite (Prosopis velutina) (400-1100 mm yr^− 1) and saltcedar (Tamarix ramosissima) (300-1300 mm yr^− 1) were intermediate, and giant sacaton (Sporobolus wrightii) (500-800 mm yr^− 1) and arrowweed (Pluchea sericea) (300-700 mm yr^− 1) were the lowest. ET rates estimated from the flux towers and by remote sensing in this study were much lower than values estimated for riparian water budgets using crop coefficient methods for the Middle Rio Grande and Lower Colorado River.     

Synaptic plasticity based model for epileptic seizures

In this paper, a new dynamic model describing the epileptic seizure initiation through transition from interictal to ictal state in a brain predisposed to epilepsy is suggested. The model follows Freeman’s approach where the brain is viewed as a network of interconnected oscillators. The proposed nonlinear model is experimentally motivated and relies on changes in synaptic strength in response to excitatory spikes. This model exhibits a threshold beyond which a bifurcation toward a short-term plasticity state occurs leading to seizure onset. A resulting explanatory assumption is that when considering epilepsy, brain regions are characterized by abnormally low thresholds toward short-term synaptic plasticity. It is shown by simulation that the proposed model enables some experimentally observed qualitative features to be reproduced. Moreover, a preliminary discussion on the impact of the underlying assumptions on the fundamental issue of seizure control is proposed through an EEG based feedback control scheme.     

Ptuba: a tool for the visualization of helix surfaces in proteins

Projection of transmembrane helices using a Uniform B-spline Algorithm is a tool for the visualization of interactions between helices in membrane proteins. It allows the user to generate projections of 3D helices, no matter what their deviations from a canonical helix might be. When associated with adapted coloring schemes it facilitates the comprehension of helix-helix interactions. Examples of transmembrane proteins were chosen to illustrate the advantages that this method provides. In the glycophorin A dimer we can easily appreciate the structural features behind homodimerisation. Using the structure of the fumarate reductase we analyze the contact surfaces inside a helical bundle and thanks to structures from a molecular dynamics simulation we see how modifications in structure and electrostatics relate to their interaction. We propose the use of this tool as an aid to the visualization and analysis of transmembrane helix surfaces and properties.