Optimizing spatiotemporal sensors placement for nutrient monitoring: a stochastic optimization framework

Nutrient monitoring is very important for the area of food–energy–water nexus. The sensor network for nutrient monitoring requires dynamic sensing where the positions of the sensors change with time. In this work, we have proposed a methodology to optimize a dynamic sensor network which can address the spatiotemporal aspect of nutrient movement in a watershed. This is a first paper in the series where an algorithmic and methodological framework for spatiotemporal sensor placement problem is proposed. Dynamic sensing is widely used in wireless sensors, and the current approaches to solving this problem are data intensive. This is the first time we are introducing a stochastic optimization approach to dynamic sensing which is efficient. This framework is based on a novel stochastic optimization algorithm called Better Optimization of Nonlinear Uncertain Systems (BONUS). A small case study of the dynamic sensor placement problem is presented to illustrate the approach. In the second paper of this series, we will present a detailed case study of nutrient monitoring in a watershed.     

A recursive maximum a posteriori estimator

Kalman Filter (KF) is the optimal state estimator for linear dynamical systems in the presence of zero mean white Gaussian noise. It is a minimum mean square error (MMSE) estimator. In the present work a recursive maximum a posteriori estimator (RMAPE) has been developed from basic principles of estimation. This estimator may be used for realtime state estimation of linear dynamical systems in presence of zero mean white Gaussian noise. It is further shown here that the KF can be derived from this RMAPE algorithm, i.e. this work shows an alternative method way to derive the KF. Copyright © 2010 John Wiley and Sons Asia Pte Ltd and Chinese Automatic Control Society     

Learning with continuous experts using drifting games

We consider the problem of learning to predict as well as the best in a group of experts making continuous predictions. We assume the learning algorithm has prior knowledge of the maximum number of mistakes of the best expert. We propose a new master strategy that achieves the best known performance for on-line learning with continuous experts in the mistake bounded model. Our ideas are based on drifting games, a generalization of boosting and on-line learning algorithms. We prove new lower bounds based on the drifting games framework which, though not as tight as previous bounds, have simpler proofs and do not require an enormous number of experts. We also extend previous lower bounds to show that our upper bounds are exactly tight for sufficiently many experts. A surprising consequence of our work is that continuous experts are only as powerful as experts making binary or no prediction in each round.     

Parameter-uniform hybrid numerical scheme for time-dependent convection-dominated initial-boundary-value problems

In this paper, we propose a numerical scheme which is almost second-order spatial accurate for a one-dimensional singularly perturbed parabolic convection-diffusion problem exhibiting a regular boundary layer. The proposed numerical scheme consists of classical backward-Euler method for the time discretization and a hybrid finite difference scheme for the spatial discretization. We analyze the scheme on a piecewise-uniform Shishkin mesh for the spatial discretization to establish uniform convergence with respect to the perturbation parameter. Numerical results are presented to validate the theoretical results.     

Sensitivity improvement using optimized heater design for dual axis thermal accelerometers

This paper investigates the sensitivity improvement of an air filled cavity based thermal accelerometer. The accelerometer does not contain any solid proof mass and it is realizable in CMOS technology. The sensitivity has been improved by a new square ring shaped heater structure. The sensitivity of accelerometer performance is compared with other different heater shapes. It is found that, heater design having higher heat dissipation in the suspended beam gives higher sensitivity. The simulation is carried out using commercial FEM simulator COMSOL Multiphysics. For the peak heater temperature of 609 K, the proposed square ring shaped heater provides a sensitivity of 0.335 K/g. Under same conditions, sensitivity of an accelerometer with a meander shaped heater structure is only 0.098 K/g and diamond shaped structure is 0.229 K/g.     

Richardson extrapolation technique for singularly perturbed parabolic convection–diffusion problems

This paper deals with the study of a post-processing technique for one-dimensional singularly perturbed parabolic convection–diffusion problems exhibiting a regular boundary layer. For discretizing the time derivative, we use the classical backward-Euler method and for the spatial discretization the simple upwind scheme is used on a piecewise-uniform Shishkin mesh. We show that the use of Richardson extrapolation technique improves the ε-uniform accuracy of simple upwinding in the discrete supremum norm from O (N ⁻¹ ln N + Δt) to O (N ⁻² ln² N + Δt ²), where N is the number of mesh-intervals in the spatial direction and Δt is the step size in the temporal direction. The theoretical result is also verified computationally by applying the proposed technique on two test examples.     

A stability-based distributed routing mechanism to support unicast and multicast routing in ad hoc wireless network

An ad hoc network can be envisioned as a collection of mobile routers, each equipped with a wireless transceiver, which are free to move about arbitrarily. In ad hoc wireless networks, even if two nodes are outside the wireless transmission range of each other, they may still be able to communicate in multiple hops using other intermediate nodes. However, the dynamics of these networks, as a consequence of mobility and disconnection of mobile hosts, pose a number of problems in designing routing schemes for effective communication between any pair of source and destination. In this paper, a stability-based unicast routing mechanism, that considers both link affinity and path stability in order to find out a stable route from source to destination, is proposed. It is then extended to support multicast routing as well where only local state information (at source) is utilized for constructing a multicast tree. The performance of the proposed scheme is evaluated on a simulated environment to show that the stability-based scheme provides a unified framework for both unicast and multicast routing and reduces the probability of route error drastically in both the cases.     

High temperature creep of polyvinyl chloride

The creep behaviour of polyvinyl chloride (PVC) has been studied in the temperature range 280 to 340° F under constant stress varying from 3.4 to 22.7 p.s.i. It is shown that the steady-state creep rate is an exponential function of stress as suggested by Norton but the exponent decreases with temperature. The activation energy for creep is determined using an activated-state rate process and it is found to be a decreasing function of stress with a higher value at temperatures 320° F and above. It is shown that the time dependent strain can be represented by $$\gamma = \gamma _0 + \dot \gamma _s t + \gamma _T \left[ {1 - \exp \left( { - K\dot \gamma _s t} \right)} \right]$$ where γ ₀ is the instantaneous strain on stressing, \(\dot \gamma _s\) the secondary creep rate, γ _T transient strain, and K is a constant. Scanning electron micrograph studies of the fracture surface and the change in activation energy apparently support the probability of two different deformation mechanisms i.e., domain flow and chain segmental or molecular flow at temperatures below and above 320° F, respectively.