Enhancement of a telemanipulator design with a human arm model

In this chapter we described how the inclusion of a model of a human arm, combined with the measurement of its neural input and a predictor, can provide to a previously proposed teleoperator design robustness under time delay. Our trials gave clear indications of the superiority of the NPT scheme over traditional as well as the modified Yokokohji and Yoshikawa architectures. Its fundamental advantages are: the time-lead of the slave, the more efficient, and providing a more natural feeling manipulation, and the fact that incorporating an operator arm model leads to more credible stability results. Finally, its simplicity allows less likely to fail local control techniques to be employed. However, a significant advantage for the enhanced Yokokohji and Yoshikawa architecture results from the very fact that it’s a conservative modification of current designs. Under large prediction errors, it can provide robustness through directing the master and slave states to their means and, since it relies on the passivity of the mechanical part of the system, it would not confuse the operator. An experimental implementation of the techniques will provide further evidence for the performance of the proposed architectures. The employment of neural networks and fuzzy logic, which will provide an adaptive model of the human arm and robustifying control terms, is scheduled for the near future.

Modelling negative feedback networks for activating transcription factor 3 predicts a dominant role for miRNAs in immediate early gene regulation

Activating transcription factor 3 (Atf3) is rapidly and transiently upregulated in numerous systems, and is associated with various disease states. Atf3 is required for negative feedback regulation of other genes, but is itself subject to negative feedback regulation possibly by autorepression. In cardiomyocytes, Atf3 and Egr1 mRNAs are upregulated via ERK1/2 signalling and Atf3 suppresses Egr1 expression. We previously developed a mathematical model for the Atf3-Egr1 system. Here, we adjusted and extended the model to explore mechanisms of Atf3 feedback regulation. Introduction of an autorepressive loop for Atf3 tuned down its expression and inhibition of Egr1 was lost, demonstrating that negative feedback regulation of Atf3 by Atf3 itself is implausible in this context. Experimentally, signals downstream from ERK1/2 suppress Atf3 expression. Mathematical modelling indicated that this cannot occur by phosphorylation of pre-existing inhibitory transcriptional regulators because the time delay is too short. De novo synthesis of an inhibitory transcription factor (ITF) with a high affinity for the Atf3 promoter could suppress Atf3 expression, but (as with the Atf3 autorepression loop) inhibition of Egr1 was lost. Developing the model to include newly-synthesised miRNAs very efficiently terminated Atf3 protein expression and, with a 4-fold increase in the rate of degradation of mRNA from the mRNA/miRNA complex, profiles for Atf3 mRNA, Atf3 protein and Egr1 mRNA approximated to the experimental data. Combining the ITF model with that of the miRNA did not improve the profiles suggesting that miRNAs are likely to play a dominant role in switching off Atf3 expression post-induction.

Anticipatory engineering: anticipation in sensory-motor systems of human

In visual tracking experiments, distributions of the relative phase be-tween target and tracer showed positive relative phase indicating that the tracer precedes the target position. We found a mode transition from the reactive to anticipatory mode. The proposed integrated model provides a framework to understand the antici-patory behaviour of human, focusing on the integration of visual and soma-tosensory information. The time delays in visual processing and somatosensory feedback are explicitly treated in the simultaneous differential equations. The anticipatory behaviour observed in the visual tracking experiments can be ex-plained by the feedforward term of target velocity, internal dynamics, and time delay in somatosensory feedback.

Blind source separation based on phase and frequency redundancy of cyclostationary signals

This paper presents a new method for blind source separation by exploiting phase and frequency redundancy of cyclostationary signals in a complementary way. It requires a weaker separation condition than those methods which only exploit the phase diversity or the frequency diversity of the source signals. The separation criterion is to diagonalize a polynomial matrix whose coefficient matrices consist of the correlation and cyclic correlation matrices, at time delay .TAU. = 0, of multiple measurements. An algorithm is proposed to perform the blind source separation. Computer simulation results illustrate the performance of the new algorithm in comparison with the existing ones.

Blind separation of cyclostationary signals from instantaneous mixtures

This paper presents a new approach for blind separation of unknown cyclostationary signals from instantaneous mixtures. The proposed method can perfectly separate the mixed source signals so long as they have either different cyclic frequencies or clock phases. This is a weaker condition than those required by the algorithms. The separation criterion is to diagonalize a polynomial matrix whose coefficient matrices consist of the correlation and cyclic correlation matrices, at time delay τ=0, of multiple measurements.

Interactions of Electrons and Rydberg Atoms in Ultra-Cold Plasmas

This thesis discusses an experimental technique for investigating electron temperature control by Rydberg atoms in ultra-cold plasmas. The objective we set ourselves was twofold. Firstly, we sought to gain an insight into the processes whereby the creation of Rydberg atoms within the plasma lengthens the lifetime of the plasma. To this end, we created the plasma using a Littman dye laser and subsequently, at a variable time delay, we excited neutral atoms in the plasma to specific Rydberg states using a narrow bandwidth pulsed dye laser. Secondly, we employed radio-frequency (rf) electric fields to excite electron oscillations within the plasma in order to infer such information as plasma density and electron temperature. Although we found that the introduction of high angular momentum Rydberg states did lengthen the plasma lifetime we were not able to differentiate between the temperature moderation effect due to the Rydberg atoms cooling the plasma, and the binding effect due to an increased positive space charge within the plasma.

3D haptic needle insertion simulator utilising an agent based spherical voxel model

This paper describes a technique for the real-time modeling of deformable tissue. Specifically geared towards needle insertion simulation, the low computational requirements of the model enable highly accurate haptic feedback to a user without introducing noticeable time delay or buzzing generally associated with haptic surgery simulation. Using a spherical voxel array combined with aspects of computational geometry and agent communication and interaction principals, the model is capable of providing haptic update rates of over 1000Hz with real-time visual feedback. Iterating through over 1000 voxels per millisecond to determine collision and haptic response while making use of Vieta’s Theorem for extraneous force culling.

Communications for underwater robotics research platforms

This paper presents a distributed protocol for communication among autonomous underwater vehicles. It is a complementary approach for coordination between the autonomous underwater vehicles. This paper mainly describes different methods for underwater communication. One of the methods is brute force approach in which messages are broadcasted to all the communication nodes, which in turn will broadcast the acknowledgement. Issues relating to this brute force approach are time delay, number of hops, power consumption, message collision and other practical issues. These issues are discussed and solved by proposing a new method to improve efficiency of this proposed approach and its effectiveness in communication among autonomous underwater vehicles.

Where and when to revegetate : a quantitative method for scheduling landscape reconstruction

Restoration of native vegetation is required in many regions of the world, but determining priority locations for revegetation is a complex problem. We consider the problem of determining spatial and temporal priorities for revegetation to maximize habitat for 62 bird species within a heavily cleared agricultural region, 11 000 km2 in area. We show how a reserve-selection framework can be applied to a complex, large-scale restoration-planning problem to account for multi-species objectives and connectivity requirements at a spatial extent and resolution relevant to management. Our approach explicitly accounts for time lags in planting and development of habitat resources, which is intended to avoid future population bottlenecks caused by delayed provision of critical resources, such as tree hollows. We coupled species-specific models of expected habitat quality and fragmentation effects with the dynamics of habitat suitability following replanting to produce species-specific maps for future times. Spatial priorities for restoration were determined by ranking locations (150-m grid cells) by their expected contribution to species habitat through time using the conservation planning tool, ‘‘Zonation.’’ We evaluated solutions by calculating expected trajectories of habitat availability for each species. We produced a spatially explicit revegetation schedule for the region that resulted in a balanced increase in habitat for all species. Priority areas for revegetation generally were clustered around existing vegetation, although not always. Areas on richer soils and with high rainfall were more highly ranked, reflecting their potential to support high-quality habitats that have been disproportionately cleared for agriculture. Accounting for delayed development of habitat resources altered the rank-order of locations in the derived revegetation plan and led to improved expected outcomes for fragmentation-sensitive species. This work demonstrates the potential for systematic restoration planning at large scales that accounts for multiple objectives, which is urgently needed by land and natural resource managers.

A state space based approach in non-linear hemodynamic response modeling with fMRI data

In this paper we use the modified and integrated version of the balloon model in the analysis of fMRI data. We propose a new state space model realization for this balloon model and represent it with the standard A,B,C and D matrices widely used in system theory. A second order Padé approximation with equal numerator and denominator degree is used for the time delay approximation in the modeling of the cerebral blood flow. The results obtained through numerical solutions showed that the new state space model realization is in close agreement to the actual modified and integrated version of the balloon model. This new system theoretic formulation is likely to open doors to a novel way of analyzing fMRI data with real time robust estimators. With further development and validation, the new model has the potential to devise a generalized measure to make a significant contribution to improve the diagnosis and treatment of clinical scenarios where the brain functioning get altered. Concepts from system theory can readily be used in the analysis of fMRI data and the subsequent synthesis of filters and estimators.

Robust functional estimation and fault diagnosis for complex uncertain systems

System monitoring and fault diagnosis capabilities are the most important aspects in improving safety and reliability of automatic control systems. This research proposed new methodologies on fault diagnosis and estimation for complex uncertain systems. As a result of this research, complex industrial plants can now be more effectively controlled.

The microcosmic model of worm propagation

Each year, large amounts of money and labor are spent on patching the vulnerabilities in operating systems and various popular software to prevent exploitation by worms. Modeling the propagation process can help us to devise effective strategies against those worms' spreading. This paper presents a microcosmic analysis of worm propagation procedures. Our proposed model is different from traditional methods and examines deep inside the propagation procedure among nodes in the network by concentrating on the propagation probability and time delay described by a complex matrix. Moreover, since the analysis gives a microcosmic insight into a worm's propagation, the proposed model can avoid errors that are usually concealed in the traditional macroscopic analytical models. The objectives of this paper are to address three practical aspects of preventing worm propagation: (i) where do we patch? (ii) how many nodes do we need to patch? (iii) when do we patch? We implement a series of experiments to evaluate the effects of each major component in our microcosmic model. Based on the results drawn from the experiments, for high-risk vulnerabilities, it is critical that networks reduce the number of vulnerable nodes to below 80%. We believe our microcosmic model can benefit the security industry by allowing them to save significant money in the deployment of their security patching schemes.

Building the capacity of family day care educators to promote children’s social and emotional wellbeing : an exploratory cluster randomised controlled trial

Background: Childhood mental health problems are highly prevalent, experienced by one in five children living in socioeconomically disadvantaged families. Although childcare settings, including family day care are ideal to promote children’s social and emotional wellbeing at a population level in a sustainable way, family day care educators receive limited training in promoting children’s mental health. This study is an exploratory wait-list control cluster randomised controlled trial to test the appropriateness, acceptability, cost, and effectiveness of “Thrive,” an intervention program to build the capacity of family day care educators to promote children’s social and emotional wellbeing. Thrive aims to increase educators’ knowledge, confidence and skills in promoting children’s social and emotional wellbeing.
Methods/Design: This study involves one family day care organisation based in a low socioeconomic area of Melbourne. All family day care educators (term used for registered carers who provide care for children for financial reimbursement in the carers own home) are eligible to participate in the study. The clusters for randomisation will be the fieldworkers (n = 5) who each supervise 10-15 educators. The intervention group (field workers and educators) will participate in a variety of intervention activities over 12 months, including workshops; activity exchanges with other educators; and focused discussion about children’s social and emotional wellbeing during field worker visits. The control group will continue with their normal work practice. The intervention will be delivered to the intervention group and then to the control group after a time delay of 15 months post intervention commencement. A baseline survey will be conducted with all consenting educators and field workers (n = ~70) assessing outcomes at the cluster and individual level. The survey will also be administered at one month, six months and 12 months post-intervention commencement. The survey consists of questions measuring perceived levels of knowledge, confidence and skills in promoting children’s social and emotional wellbeing. As much of this intervention will be delivered by field workers, field worker-family day care educator relationships are key to its success and thus supervisor support will also be measured. All educators will also have an in-home quality of care assessment at baseline, one month, six months and 12 months post-intervention commencement. Process evaluation will occur at one month, six months and 12 months post-intervention commencement. Information regarding intervention fidelity and economics will also be assessed in the survey.
Discussion: A capacity building intervention in child mental health promotion for family day care is an essential contribution to research, policy and practice. This initiative is the first internationally, and essential in building an evidence base of interventions in this extremely policy-timely setting.

Model Prediction Control For Water Management Using Adaptive Prediction Accuracy

In the field of operational water management, Model Predictive Control (MPC) has gained popularity owing to its versatility and flexibility. The MPC controller, which takes predictions, time delay and uncertainties into account, can be designed for multi-objective management problems and for large-scale systems. Nonetheless, a critical obstacle, which needs to be overcome in MPC, is the large computational burden when a large-scale system is considered or a long prediction horizon is involved. In order to solve this problem, we use an adaptive prediction accuracy (APA) approach that can reduce the computational burden almost by half. The proposed MPC scheme with this scheme is tested on the northern Dutch water system, which comprises Lake IJssel, Lake Marker, the River IJssel and the North Sea Canal. The simulation results show that by using the MPC-APA scheme, the computational time can be reduced to a large extent and a flood protection problem over longer prediction horizons can be well solved.

Avaliação de robustez, desempenho e aplicação do controlador adaptativo por posicionamento de pólos e estrutura variável

In this work, the variable structure adaptive pole placement controller (VS-APPC) robustness and performance are evaluated and this algorithm is applied in a motor control system. The controller robustness evaluation will be done through simulations, where will be introduced in the system the following adversities: time delay, actuator response boundeds, disturbances, parametric variation and unmodeled dynamics. The VS-APPC will be compared with PI control, pole placement control (PPC) and adaptive pole placement controller (APPC). The VS-APPC will be simulated to track a step and a sine reference. It will be applied in a three-phase induction motor control system to track a sine signal in the stator reference frame. Simulation and experimental results will prove the efficiency and robustness of this control strategy