Adding constrained discontinuities to Gaussian process models of wind fields

Gaussian Processes provide good prior models for spatial data, but can be too smooth. In many physical situations there are discontinuities along bounding surfaces, for example fronts in near-surface wind fields. We describe a modelling method for such a constrained discontinuity and demonstrate how to infer the model parameters in wind fields with MCMC sampling.

Amplitude response of a unilaterally constrained nonlinear micromechanical resonator

Dynamical systems that involve impacts frequently arise in engineering. This Letter reports a study of such a system at microscale that consists of a nonlinear resonator operating with an unilateral impact. The microresonators were fabricated on silicon-on-insulator wafers by using a one-mask process and then characterised by using the capacitively driving and sensing method. Numerical results concerning the dynamics of this vibro-impact system were verified by the experiments. Bifurcation analysis was used to provide a qualitative scenario of the system steady-state solutions as a function of both the amplitude and the frequency of the external driving sinusoidal voltage. The results show that the amplitude of resonant peak is levelled off owing to the impact effect and that the bandwidth of impacting is dependent upon the nonlinearity and the operating conditions.

Adding constrained discontinuities to Gaussian process models of wind fields

Gaussian Processes provide good prior models for spatial data, but can be too smooth. In many physical situations there are discontinuities along bounding surfaces, for example fronts in near-surface wind fields. We describe a modelling method for such a constrained discontinuity and demonstrate how to infer the model parameters in wind fields with MCMC sampling.

The development of constrained source localisation algorithms for human brain imaging

This work sets out to evaluate the potential benefits and pit-falls in using a priori information to help solve the Magnetoencephalographic (MEG) inverse problem. In chapter one the forward problem in MEG is introduced, together with a scheme that demonstrates how a priori information can be incorporated into the inverse problem. Chapter two contains a literature review of techniques currently used to solve the inverse problem. Emphasis is put on the kind of a priori information that is used by each of these techniques and the ease with which additional constraints can be applied. The formalism of the FOCUSS algorithm is shown to allow for the incorporation of a priori information in an insightful and straightforward manner. In chapter three it is described how anatomical constraints, in the form of a realistically shaped source space, can be extracted from a subject’s Magnetic Resonance Image (MRI). The use of such constraints relies on accurate co-registration of the MEG and MRI co-ordinate systems. Variations of the two main co-registration approaches, based on fiducial markers or on surface matching, are described and the accuracy and robustness of a surface matching algorithm is evaluated. Figures of merit introduced in chapter four are shown to given insight into the limitations of a typical measurement set-up and potential value of a priori information. It is shown in chapter five that constrained dipole fitting and FOCUSS outperform unconstrained dipole fitting when data with low SNR is used. However, the effect of errors in the constraints can reduce this advantage. Finally, it is demonstrated in chapter six that the results of different localisation techniques give corroborative evidence about the location and activation sequence of the human visual cortical areas underlying the first 125ms of the visual magnetic evoked response recorded with a whole head neuromagnetometer.

Constrained nonparametric estimation of input distance function

This paper proposes a constrained nonparametric method of estimating an input distance function. A regression function is estimated via kernel methods without functional form assumptions. To guarantee that the estimated input distance function satisfies its properties, monotonicity constraints are imposed on the regression surface via the constraint weighted bootstrapping method borrowed from statistics literature. The first, second, and cross partial analytical derivatives of the estimated input distance function are derived, and thus the elasticities measuring input substitutability can be computed from them. The method is then applied to a cross-section of 3,249 Norwegian timber producers.

Multi-level genetic algorithm for the resource-constrained re-entrant scheduling problem in the flow shop

The re-entrant flow shop scheduling problem (RFSP) is regarded as a NP-hard problem and attracted the attention of both researchers and industry. Current approach attempts to minimize the makespan of RFSP without considering the interdependency between the resource constraints and the re-entrant probability. This paper proposed Multi-level genetic algorithm (GA) by including the co-related re-entrant possibility and production mode in multi-level chromosome encoding. Repair operator is incorporated in the Multi-level genetic algorithm so as to revise the infeasible solution by resolving the resource conflict. With the objective of minimizing the makespan, Multi-level genetic algorithm (GA) is proposed and ANOVA is used to fine tune the parameter setting of GA. The experiment shows that the proposed approach is more effective to find the near-optimal schedule than the simulated annealing algorithm for both small-size problem and large-size problem. © 2013 Published by Elsevier Ltd.

Predictors of household hardship in a resource constrained environment:the case of sub-Saharan Africa

Using data from the 2004 wave of the Afrobarometer survey, this study examines correlates of household hardship in three countries of sub-Saharan Africa: Tanzania, Zambia, and Zimbabwe. Findings provide partial support for the hypothesized relationship. Specifically, poverty reduction initiatives and informal assistance are associated with reduced hardship while civic engagement is related to an increase in household hardship. We also note that certain demographic characteristics are linked to hardship. Policy and practice implications are suggested. © The Author(s) 2011.

Weakly-constrained codes for suppression of patterning effects in digital communications

We propose weakly-constrained stream and block codes with tunable pattern-dependent statistics and demonstrate that the block code capacity at large block sizes is close to the the prediction obtained from a simple Markov model published earlier. We demonstrate the feasibility of the code by presenting original encoding and decoding algorithms with a complexity log-linear in the block size and with modest table memory requirements. We also show that when such codes are used for mitigation of patterning effects in optical fibre communications, a gain of about 0.5dB is possible under realistic conditions, at the expense of small redundancy 10%). © 2006 IEEE.

Suppression of patterning effects in digital communications by an adaptive constrained coding

We quantify the error statistics and patterning effects in a 5x 40 Gbit/s WDM RZ-DBPSK SMF/DCF fibre link using hybrid Raman/EDFA amplification. We propose an adaptive constrained coding for the suppression of errors due to patterning effects. It is established, that this coding technique can greatly reduce the bit error rate (BER) value even for large BER (BER > 101). The proposed approach can be used in the combination with the forward error correction schemes (FEC) to correct the errors even when real channel BER is outside the FEC workspace.

Weakly-constrained codes for suppression of patterning effects in digital communications

We propose weakly-constrained stream and block codes with tunable pattern-dependent statistics and demonstrate that the block code capacity at large block sizes is close to the the prediction obtained from a simple Markov model published earlier. We demonstrate the feasibility of the code by presenting original encoding and decoding algorithms with a complexity log-linear in the block size and with modest table memory requirements. We also show that when such codes are used for mitigation of patterning effects in optical fibre communications, a gain of about 0.5dB is possible under realistic conditions, at the expense of small redundancy (≈10%). © 2010 IEEE