Neural networks for identification of nonlinear systems under random piecewise polynomial disturbances

The problem of identification of a nonlinear dynamic system is considered. A two-layer neural network is used for the solution of the problem. Systems disturbed with unmeasurable noise are considered, although it is known that the disturbance is a random piecewise polynomial process. Absorption polynomials and nonquadratic loss functions are used to reduce the effect of this disturbance on the estimates of the optimal memory of the neural-network model.

Early identification of stimulant treatment responders, partial responders and non-responders using objective measures in children and adolescents with hyperkinetic disorder

Background: The aim of this study was to evaluate stimulant medication response following a single dose of methylphenidate (MPH) in children and young people with hyperkinetic disorder using infrared motion analysis combined with a continuous performance task (QbTest system) as objective measures. The hypothesis was put forward that a moderate testdose of stimulant medication could determine a robust treatment response, partial response and non-response in relation to activity, attention and impulse control measures. Methods: The study included 44 children and young people between the ages of 7-18 years with a diagnosis of hyperkinetic disorder (F90 & F90.1). A single dose-protocol incorporated the time course effects of both immediate release MPH and extended release MPH (Concerta XL, Equasym XL) to determine comparable peak efficacy periods post intake. Results: A robust treatment response with objective measures reverting to the population mean was found in 37 participants (84%). Three participants (7%) demonstrated a partial response to MPH and four participants (9%) were determined as non-responders due to deteriorating activity measures together with no improvements in attention and impulse control measures. Conclusion: Objective measures provide early into prescribing the opportunity to measure treatment response and monitor adverse reactions to stimulant medication. Most treatment responders demonstrated an effective response to MPH on a moderate testdose facilitating a swift and more optimal titration process.

Neurofuzzy state identification using prefiltering

A new state estimator algorithm is based on a neurofuzzy network and the Kalman filter algorithm. The major contribution of the paper is recognition of a bias problem in the parameter estimation of the state-space model and the introduction of a simple, effective prefiltering method to achieve unbiased parameter estimates in the state-space model, which will then be applied for state estimation using the Kalman filtering algorithm. Fundamental to this method is a simple prefiltering procedure using a nonlinear principal component analysis method based on the neurofuzzy basis set. This prefiltering can be performed without prior system structure knowledge. Numerical examples demonstrate the effectiveness of the new approach.

Identification and minimization of IIR tap coefficients for the cancellation of complex multipath in terrestrial television

By using a deterministic approach, an exact form for the synchronous detected video signal under a ghosted condition is presented. Information regarding the phase quadrature-induced ghost component derived from the quadrature forming nature of the vestigial sideband (VSB) filter is obtained by crosscorrelating the detected video with the ghost cancel reference (GCR) signal. As a result, the minimum number of taps required to correctly remove all the ghost components is subsequently presented. The results are applied to both National Television System Committee (NTSC) and phase alternate line (PAL) television.

Linear-wavelet models applied to the identification of a two-link manipulator

This paper shows that a wavelet network and a linear term can be advantageously combined for the purpose of non linear system identification. The theoretical foundation of this approach is laid by proving that radial wavelets are orthogonal to linear functions. A constructive procedure for building such nonlinear regression structures, termed linear-wavelet models, is described. For illustration, sim ulation data are used to identify a model for a two-link robotic manipulator. The results show that the introduction of wavelets does improve the prediction ability of a linear model.

Exploring behavioural change through an agent-oriented system dynamics model: the use of personal protective equipment among pesticide applicators in Colombia

The misuse of Personal Protective Equipment results in health risk among smallholders in developing countries, and education is often proposed to promote safer practices. However, evidence point to limited effects of education. This paper presents a System Dynamics model which allows the identification of risk-minimizing policies for behavioural change. The model is based on the IAC framework and survey data. It represents farmers' decision-making from an agent-oriented standpoint. The most successful intervention strategy was the one which intervened in the long term, targeted key stocks in the systems and was diversified. However, the results suggest that, under these conditions, no policy is able to trigger a self sustaining behavioural change. Two implementation approaches were suggested by experts. One, based on constant social control, corresponds to a change of the current model's parameters. The other, based on participation, would lead farmers to new thinking, i.e. changes in their decision-making structure.

Real-time identification and modelling in pervasive mining

This paper introduces an architecture for identifying and modelling in real-time at a copper mine using new technologies as M2M and cloud computing with a server in the cloud and an Android client inside the mine. The proposed design brings up pervasive mining, a system with wider coverage, higher communication efficiency, better fault-tolerance, and anytime anywhere availability. This solution was designed for a plant inside the mine which cannot tolerate interruption and for which their identification in situ, in real time, is an essential part of the system to control aspects such as instability by adjusting their corresponding parameters without stopping the process.

Automated identification and tracking of polar-cap plasma patches at solar minimum

A method of automatically identifying and tracking polar-cap plasma patches, utilising data inversion and feature-tracking methods, is presented. A well-established and widely used 4-D ionospheric imaging algorithm, the Multi-Instrument Data Assimilation System (MIDAS), inverts slant total electron content (TEC) data from ground-based Global Navigation Satellite System (GNSS) receivers to produce images of the free electron distribution in the polar-cap ionosphere. These are integrated to form vertical TEC maps. A flexible feature-tracking algorithm, TRACK, previously used extensively in meteorological storm-tracking studies is used to identify and track maxima in the resulting 2-D data fields. Various criteria are used to discriminate between genuine patches and "false-positive" maxima such as the continuously moving day-side maximum, which results from the Earth's rotation rather than plasma motion. Results for a 12-month period at solar minimum, when extensive validation data are available, are presented. The method identifies 71 separate structures consistent with patch motion during this time. The limitations of solar minimum and the consequent small number of patches make climatological inferences difficult, but the feasibility of the method for patches larger than approximately 500 km in scale is demonstrated and a larger study incorporating other parts of the solar cycle is warranted. Possible further optimisation of discrimination criteria, particularly regarding the definition of a patch in terms of its plasma concentration enhancement over the surrounding background, may improve results.

Operational active fire mapping and burnt area identification applicable to Mexican Nature Protection Areas using MODIS and NOAA-AVHRR direct readout data

Since 1999, the National Commission for the Knowledge and Use of the Biodiversity (CONABIO) in Mexico has been developing and managing the “Operational program for the detection of hot-spots using remote sensing techniques”. This program uses images from the MODerate resolution Imaging Spectroradiometer (MODIS) onboard the Terra and Aqua satellites and from the Advanced Very High Resolution Radiometer of the National Oceanic and Atmospheric Administration (NOAA-AVHRR), which are operationally received through the Direct Readout station (DR) at CONABIO. This allows the near-real time monitoring of fire events in Mexico and Central America. In addition to the detection of active fires, the location of hot spots are classified with respect to vegetation types, accessibility, and risk to Nature Protection Areas (NPA). Besides the fast detection of fires, further analysis is necessary due to the considerable effects of forest fires on biodiversity and human life. This fire impact assessment is crucial to support the needs of resource managers and policy makers for adequate fire recovery and restoration actions. CONABIO attempts to meet these requirements, providing post-fire assessment products as part of the management system in particular for satellite-based burnt area mapping. This paper provides an overview of the main components of the operational system and will present an outlook to future activities and system improvements, especially the development of a burnt area product. A special focus will also be placed on the fire occurrence within NPAs of Mexico

Using virtual environments for trigger identification in addiction treatment

This paper presents a novel application of virtual environments to assist in encouraging behavior change in individuals who misuse drugs or alcohol. We describe the user-centered design of a series of scenes to engage users in the identification of triggers and to encourage discussions about relevant coping skills. Results from the initial testing of this application with six service users showed variation in user responses. Results also suggested that the system should encourage group discussion and that it was linked to a small improvement in users’ confidence in understanding and identifying triggers.

Body-centric modelling, identification, and acceleration tracking control of a quadrotor UAV

This paper presents the mathematical development of a body-centric nonlinear dynamic model of a quadrotor UAV that is suitable for the development of biologically inspired navigation strategies. Analytical approximations are used to find an initial guess of the parameters of the nonlinear model, then parameter estimation methods are used to refine the model parameters using the data obtained from onboard sensors during flight. Due to the unstable nature of the quadrotor model, the identification process is performed with the system in closed-loop control of attitude angles. The obtained model parameters are validated using real unseen experimental data. Based on the identified model, a Linear-Quadratic (LQ) optimal tracker is designed to stabilize the quadrotor and facilitate its translational control by tracking body accelerations. The LQ tracker is tested on an experimental quadrotor UAV and the obtained results are a further means to validate the quality of the estimated model. The unique formulation of the control problem in the body frame makes the controller better suited for bio-inspired navigation and guidance strategies than conventional attitude or position based control systems that can be found in the existing literature.

A Lagrangian identification of major sources of moisture over Central Brazil and La Plata Basin

[1] This work examines the main sources of moisture over Central Brazil and La Plata Basin during the year through a new Lagrangian diagnosis method which identifies the humidity contributions to the moisture budget over a region. This methodology computes budgets of evaporation minus precipitation by calculating changes in the specific humidity along back-trajectories for the previous 10 d. The origin of all air masses residing over each region was tracked during a period of 5 years (2000-2004). These regions were selected because they coincide with two centers of action of a known dipole precipitation variability mode observed in different temporal scales (from intra seasonal up to inter decadal timescales) and are related to the climatic variability of the South American Monsoon System. The results suggested the importance of the tropical south Atlantic as a moisture source for Central Brazil, and of recycling for La Plata basin. It seems that the Tropical South Atlantic plays an important role as a moisture source for Central Brazil and La Plata basin along the year, particularly during the austral summer. The north Atlantic is also an additional source for both regions during the austral summer.

Characterization of Caulobacter crescentus response to low temperature and identification of genes involved in freezing resistance

Free-living bacteria must respond to a wide range of temperature changes, and have developed specific mechanisms to survive in extreme environments. In this work we describe a remarkable resistance of mesophilic bacterium Caulobacter crescentus to several cycles of freezing at -80 degrees C, which was able to grow at low temperatures. Exponentially growing cells and late stationary-phase cells presented higher freezing resistance at both -20 and -80 degrees C than early stationary-phase cells. Cryotolerance was observed when log-phase cultures grown at 30 degrees C were preincubated at 5, 15 or 20 degrees C before freezing at -20 degrees C. A transposon library was screened to identify mutants sensitive to freezing at -80 degrees C and three strains presenting < 10% survival were isolated. Identification of genes disrupted in each mutant showed that they encoded an AddA family DNA helicase, a DEAD/DEAH box RNA helicase and a putative RND (resistance, nodulation, cell division) efflux system component. These strains showed longer generation times than wild-type cells when growing at 15 degrees C, with the RNA helicase mutant presenting a severe growth defect. These analyses suggest that the singular intrinsic resistance to freezing of C. crescentus is in fact a consequence of several independent traits, especially the maintenance of a proper degree of supercoiling of nucleic acids.

The transcriptional response to cadmium, organic hydroperoxide, singlet oxygen and UV-A mediated by the sigma(E)-ChrR system in Caulobacter crescentus

Caulobacter crescentus sigma(E) belongs to the ECF (extracytoplasmic function) subfamily of RNA polymerase sigma factors, whose members regulate gene expression in response to distinct environmental stresses. During physiological growth conditions, data indicate that sigma(E) is maintained in reduced levels due to the action of ChrR, a negative regulator of rpoE gene expression and function. However, once bacterial cells are exposed to cadmium, organic hydroperoxide, singlet oxygen or UV-A irradiation, transcription of rpoE is induced in a sigma(E)-dependent manner. Site-directed mutagenesis indicated that residue C188 in ChrR is critical for the cadmium response while residues H140 and H142 are required for the bacterial response to organic hydroperoxide, singlet oxygen and UV-A. Global transcriptional analysis showed that sigma(E) regulates genes involved in protecting cells against oxidative damages. A combination of transcriptional start site identification and promoter prediction revealed that some of these genes contain a putative sigma(E)-dependent motif in their upstream regions. Furthermore, deletion of rpoE and two sigma(E)-dependent genes (cfaS and hsp20) impairs Caulobacter survival when singlet oxygen is constantly generated in the cells.

Identification of protein-coding and intronic noncoding RNAs down-regulated in clear cell renal carcinoma

The clear cell subtype of renal cell carcinoma (RCC) is the most lethal and prevalent cancer of the urinary system. To investigate the molecular changes associated with malignant transformation in clear cell RCC, the gene expression profiles of matched samples of tumor and adjacent non-neoplastic tissue were obtained from six patients. A custom-built cDNA microarray platform was used, comprising 2292 probes that map to exons of genes and 822 probes for noncoding RNAs mapping to intronic regions. Intronic transcription was detected in all normal and neoplastic renal tissues. A subset of 55 transcripts was significantly down-regulated in clear cell RCC relative to the matched nontumor tissue as determined by a combination of two statistical tests and leave-one-out patient cross-validation. Among the down-regulated transcripts, 49 mapped to untranslated or coding exons and 6 were intronic relative to known exons of protein-coding genes. Lower levels of expression of SIN3B, TRIP3, SYNJ2BP and NDE1 (P<0.02), and of intronic transcripts derived from SND1 and ACTN4 loci (P<0.05), were confirmed in clear cell RCC by Real-time RT-PCR. A subset of 25 transcripts was deregulated in additional six nonclear cell RCC samples, pointing to common transcriptional alterations in RCC irrespective of the histological subtype or differentiation state of the tumor. Our results indicate a novel set of tumor suppressor gene candidates, including noncoding intronic RNAs, which may play a significant role in malignant transformations of normal renal cells. (C) 2008 Wiley-Liss, Inc.