A Branch and Bound Algorithm for a Transportation Type Problem with Piecewise Linear Convex Objective Function

A branch and bound type algorithm is presented in this paper to the problem of finding a transportation schedule which minimises the total transportation cost, where the transportation cost over each route is assumed to be a piecewice linear continuous convex function with increasing slopes. The algorithm is an extension of the work done by Balachandran and Perry, in which the transportation cost over each route is assumed to beapiecewise linear discontinuous function with decreasing slopes. A numerical example is solved illustrating the algorithm.

A time minimising transportation problem with quality dependent time

The usual assumption made in time minimising transportation problem is that the time for transporting a positive amount in a route is independent of the actual amount transported in that route. In this paper we make a more general and natural assumption that the time depends on the actual amount transported. We assume that the time function for each route is an increasing piecewise constant function. Four algorithms - (1) a threshold algorithm, (2) an upper bounding technique, (3) a primal dual approach, and (4) a branch and bound algorithm - are presented to solve the given problem. A method is also given to compute the minimum bottle-neck shipment corresponding to the optimal time. A numerical example is solved illustrating the algorithms presented in this paper.

Application of the Conjugate Gradient Method to a Problem on Minimum Time Orbit Transfer

This correspondence considers the problem of optimally controlling the thrust steering angle of an ion-propelled spaceship so as to effect a minimum time coplanar orbit transfer from the mean orbital distance of Earth to mean Martian and Venusian orbital distances. This problem has been modelled as a free terminal time-optimal control problem with unbounded control variable and with state variable equality constraints at the final time. The problem has been solved by the penalty function approach, using the conjugate gradient algorithm. In general, the optimal solution shows a significant departure from earlier work. In particular, the optimal control in the case of Earth-Mars orbit transfer, during the initial phase of the spaceship's flight, is found to be negative, resulting in the motion of the spaceship within the Earth's orbit for a significant fraction of the total optimized orbit transfer time. Such a feature exhibited by the optimal solution has not been reported at all by earlier investigators of this problem.

The non-linear response of a gyrostabilized platform: Effects of correction torque time delay and of random inputs

First, the non-linear response of a gyrostabilized platform to a small constant input torque is analyzed in respect to the effect of the time delay (inherent or deliberately introduced) in the correction torque supplied by the servomotor, which itself may be non-linear to a certain extent. The equation of motion of the platform system is a third order nonlinear non-homogeneous differential equation. An approximate analytical method of solution of this equation is utilized. The value of the delay at which the platform response becomes unstable has been calculated by using this approximate analytical method. The procedure is illustrated by means of a numerical example. Second, the non-linear response of the platform to a random input has been obtained. The effects of several types of non-linearity on reducing the level of the mean square response have been investigated, by applying the technique of equivalent linearization and solving the resulting integral equations by using laguerre or Gaussian integration techniques. The mean square responses to white noise and band limited white noise, for various values of the non-linear parameter and for different types of non-linearity function, have been obtained. For positive values of the non-linear parameter the levels of the non-linear mean square responses to both white noise and band-limited white noise are low as compared to the linear mean square response. For negative values of the non-linear parameter the level of the non-linear mean square response at first increases slowly with increasing values of the non-linear parameter and then suddenly jumps to a high level, at a certain value of the non-linearity parameter.

System integration design in MEMS - A case study of micromachined load cell

One of the critical issues in large scale commercial exploitation of MEMS technology is its system integration. In MEMS, a system design approach requires integration of varied and disparate subsystems with one of a kind interface. The physical scales as well as the magnitude of signals of various subsystems vary widely. Known and proven integration techniques often lead to considerable loss in advantages the tiny MEMS sensors have to offer. Therefore, it becomes imperative to think of the entire system at the outset, at least in terms of the concept design. Such design entails various aspects of the system ranging from selection of material, transduction mechanism, structural configuration, interface electronics, and packaging. One way of handling this problem is the system-in-package approach that uses optimized technology for each function using the concurrent hybrid engineering approach. The main strength of this design approach is the fast time to prototype development. In the present work, we pursue this approach for a MEMS load cell to complete the process of system integration for high capacity load sensing. The system includes; a micromachined sensing gauge, interface electronics and a packaging module representing a system-in-package ready for end characterization. The various subsystems are presented in a modular stacked form using hybrid technologies. The micromachined sensing subsystem works on principles of piezo-resistive sensing and is fabricated using CMOS compatible processes. The structural configuration of the sensing layer is designed to reduce the offset, temperature drift, and residual stress effects of the piezo-resistive sensor. ANSYS simulations are carried out to study the effect of substrate coupling on sensor structure and its sensitivity. The load cell system has built-in electronics for signal conditioning, processing, and communication, taking into consideration the issues associated with resolution of minimum detectable signal. The packaged system represents a compact and low cost solution for high capacity load sensing in the category of compressive type load sensor.

Blockade of estrogen synthesis with an aromatase inhibitor affects luteal function of the pseudopregnant rat

The luteotropic action of estrogen (E) was investigated using immature pseudopregnant rat as the model and CGS 16949A (Fadrozole hydrochloride), a potent aromatase inhibitor (AI), to block E synthesis. Aromatase activity could be inhibited by administering CGS 16949A (50 mu g/day/rat) via a mini osmotic Alzet pump (model 2002) for 3 days during pseudopregnancy. This resulted in significant reduction of serum (40%, P < 0.05) and intraovarian (70.6%, P < 0.001) estradiol-17 beta (E(2)) levels. The serum and intraovarian progesterone (P-4) levels as analyzed on day 4 of pseudopregnancy were also reduced by greater than or equal to 50% (for both, P < 0.01). Simultaneous administration of estradiol-3-benzoate (E(2)B) via an Alzet pump during the Al: treatment period at a dose of 1 mu g/day could completely reverse the Al induced reduction in P-4 secretion. The luteal cells of experimental rats depleted of E in vivo showed a significantly reduced response upon incubation with hCG or dbcAMP in vitro (P < 0.05 and 0.001, respectively). Addition of E(2) (500 pg/tube) at the time of in vitro incubation was able to partially increase the responsiveness to hCG. The luteal cell LH/hCG receptor content and the affinity of hCG binding to the receptor remained unchanged following AI treatment in vivo. Both esterified and total cholesterol content of luteal cells of rats treated with Al in vivo was significantly high (P < 0.05) suggesting that E lack results in an impairment in cholesterol utilization for steroidogenesis. The results clearly show that E regulates luteal function in the pseudopregnant rat by acting at a non-cAMP mediated event and this perhaps involves facilitation of cholesterol utilization at the mitochondrial level for P-4 synthesis.

Changes in testicular function following specific deprivation of LH in the adult male rabbit

Sexually mature male rabbits actively immunized against highly purified ovine LH (oLH) were used as a model system to study the effects of endogenous LH deprivation (and therefore testosterone) on spermatogenesis as well as pituitary FSH secretion. Immunization against oLH generated antibody titres capable of cross-reacting and neutralizing rabbit LH and this resulted in a significant reduction (P<0.01) in serum testosterone levels by 2-4 weeks of immunization. A significant increase in circulating FSH concentration (from a basal level of similar to 1 ng to 60-100 ng/ml; P<0.01) was observed within 4-6 weeks of immunization, perhaps a consequence of the negative feedback effect of the lack of testosterone. The effect of LH deprivation on spermatogenesis assessed by DNA flow cytometry and histological analyses of testicular biopsy tissue revealed that lack of testosterone primarily results in a rapid reduction and complete absence of round (1C) and elongated (HC) spermatids. The immediate effect of LH/testosterone deprivation thus appears to be at the step of meiotic transformation of primary spermatocytes (4C) to 1C. A significant reduction (>80%; P<0.01) in the 4C population and a relative accumulation (>90%; P<0.01) in spermatogonia (2C) was also observed, suggesting a need for testosterone during the transformation of 2C to 1C. In all but one of the rabbits, both qualitative and quantitative recovery in spermatogenesis occurred during the recovery phase, even at a time when only a marginal increase in serum testosterone (compared with the preimmunization) levels was observed as a result of a rapid decline in the cross-reactive antibody titres. These results clearly show that LH/testosterone deprivation in addition to primarily affecting the meiotic step also regulates the conversion of 2C to 4C during spermatogenesis.

A lower bound to the survival probability and an approximate first passage time distribution for Markovian and non-Markovian dynamics in phase space

We derive a very general expression of the survival probability and the first passage time distribution for a particle executing Brownian motion in full phase space with an absorbing boundary condition at a point in the position space, which is valid irrespective of the statistical nature of the dynamics. The expression, together with the Jensen's inequality, naturally leads to a lower bound to the actual survival probability and an approximate first passage time distribution. These are expressed in terms of the position-position, velocity-velocity, and position-velocity variances. Knowledge of these variances enables one to compute a lower bound to the survival probability and consequently the first passage distribution function. As examples, we compute these for a Gaussian Markovian process and, in the case of non-Markovian process, with an exponentially decaying friction kernel and also with a power law friction kernel. Our analysis shows that the survival probability decays exponentially at the long time irrespective of the nature of the dynamics with an exponent equal to the transition state rate constant.

Kernels for large margin time-series classification

In this paper we propose a novel family of kernels for multivariate time-series classification problems. Each time-series is approximated by a linear combination of piecewise polynomial functions in a Reproducing Kernel Hilbert Space by a novel kernel interpolation technique. Using the associated kernel function a large margin classification formulation is proposed which can discriminate between two classes. The formulation leads to kernels, between two multivariate time-series, which can be efficiently computed. The kernels have been successfully applied to writer independent handwritten character recognition.

Probing the aging effect in metallic polypyrrole by terahertz time-domain spectroscopy

Terahertz time-domain spectroscopy has been carried out on a metallic film of polypyrrole (PPy doped by PF6). The sample was exposed to air to investigate how the conductivity of the film varies as a function of time. The absorption and dispersion of the film decrease during initial days, and then tend to saturate. The conductivity of unaged sample follows the Drude model, and upon aging the data fit to the localization-modified Drude model. The fitting parameters show that the number of charge carriers decreases during the aging process. The initial rapid decrease in conductivity suggests that some of the delocalized carriers are localized due to aging. (C) 2007 American Institute of Physics.

Time and Energy Complexity of Distributed Computation of a Class of Functions in Wireless Sensor Networks

We consider a scenario in which a wireless sensor network is formed by randomly deploying n sensors to measure some spatial function over a field, with the objective of computing a function of the measurements and communicating it to an operator station. We restrict ourselves to the class of type-threshold functions (as defined in the work of Giridhar and Kumar, 2005), of which max, min, and indicator functions are important examples: our discussions are couched in terms of the max function. We view the problem as one of message-passing distributed computation over a geometric random graph. The network is assumed to be synchronous, and the sensors synchronously measure values and then collaborate to compute and deliver the function computed with these values to the operator station. Computation algorithms differ in (1) the communication topology assumed and (2) the messages that the nodes need to exchange in order to carry out the computation. The focus of our paper is to establish (in probability) scaling laws for the time and energy complexity of the distributed function computation over random wireless networks, under the assumption of centralized contention-free scheduling of packet transmissions. First, without any constraint on the computation algorithm, we establish scaling laws for the computation time and energy expenditure for one-time maximum computation. We show that for an optimal algorithm, the computation time and energy expenditure scale, respectively, as Theta(radicn/log n) and Theta(n) asymptotically as the number of sensors n rarr infin. Second, we analyze the performance of three specific computation algorithms that may be used in specific practical situations, namely, the tree algorithm, multihop transmission, and the Ripple algorithm (a type of gossip algorithm), and obtain scaling laws for the computation time and energy expenditure as n rarr infin. In particular, we show that the computation time for these algorithms scales as Theta(radicn/lo- g n), Theta(n), and Theta(radicn log n), respectively, whereas the energy expended scales as , Theta(n), Theta(radicn/log n), and Theta(radicn log n), respectively. Finally, simulation results are provided to show that our analysis indeed captures the correct scaling. The simulations also yield estimates of the constant multipliers in the scaling laws. Our analyses throughout assume a centralized optimal scheduler, and hence, our results can be viewed as providing bounds for the performance with practical distributed schedulers.

Solution of MDPS using simulation-based value iteration

This article proposes a three-timescale simulation based algorithm for solution of infinite horizon Markov Decision Processes (MDPs). We assume a finite state space and discounted cost criterion and adopt the value iteration approach. An approximation of the Dynamic Programming operator T is applied to the value function iterates. This 'approximate' operator is implemented using three timescales, the slowest of which updates the value function iterates. On the middle timescale we perform a gradient search over the feasible action set of each state using Simultaneous Perturbation Stochastic Approximation (SPSA) gradient estimates, thus finding the minimizing action in T. On the fastest timescale, the 'critic' estimates, over which the gradient search is performed, are obtained. A sketch of convergence explaining the dynamics of the algorithm using associated ODEs is also presented. Numerical experiments on rate based flow control on a bottleneck node using a continuous-time queueing model are performed using the proposed algorithm. The results obtained are verified against classical value iteration where the feasible set is suitably discretized. Over such a discretized setting, a variant of the algorithm of [12] is compared and the proposed algorithm is found to converge faster.

Step function response of non-linear spring mass systems in the presence of Coulomb damping

The transient response of non-linear spring mass systems with Coulomb damping, when subjected to a step function is investigated. For a restricted class of non-linear spring characteristics, exact expressions are developed for (i) the first peak of the response curves, and (ii) the time taken to reach it. A simple, yet accurate linearization procedure is developed for obtaining the approximate time required to reach the first peak, when the spring characteristic is a general function of the displacement. The results are presented graphically in non-dimensional form.

Direct observation of low frequency confined acoustic phonons in silver nanoparticles: Terahertz time domain spectroscopy

Terahertz time domain spectroscopy has been used to study low frequency confined acoustic phonons of silver nanoparticles embedded in poly (vinyl alcohol) matrix in the spectral range of 0.1-2.5 THz. The real and imaginary parts of the dielectric function show two bands at 0.60 and 2.12 THz attributed to the spheroidal and toroidal modes of silver nanoparticles, thus demonstrating the usefulness of terahertz time domain spectroscopy as a complementary technique to Raman spectroscopy in characterizing the nanoparticles. (C) 2010 American Institute of Physics. [doi:10.1063/1.3456372]

Filter design using radial basis function neural network and genetic algorithm for improved operational health monitoring

The problem of denoising damage indicator signals for improved operational health monitoring of systems is addressed by applying soft computing methods to design filters. Since measured data in operational settings is contaminated with noise and outliers, pattern recognition algorithms for fault detection and isolation can give false alarms. A direct approach to improving the fault detection and isolation is to remove noise and outliers from time series of measured data or damage indicators before performing fault detection and isolation. Many popular signal-processing approaches do not work well with damage indicator signals, which can contain sudden changes due to abrupt faults and non-Gaussian outliers. Signal-processing algorithms based on radial basis function (RBF) neural network and weighted recursive median (WRM) filters are explored for denoising simulated time series. The RBF neural network filter is developed using a K-means clustering algorithm and is much less computationally expensive to develop than feedforward neural networks trained using backpropagation. The nonlinear multimodal integer-programming problem of selecting optimal integer weights of the WRM filter is solved using genetic algorithm. Numerical results are obtained for helicopter rotor structural damage indicators based on simulated frequencies. Test signals consider low order polynomial growth of damage indicators with time to simulate gradual or incipient faults and step changes in the signal to simulate abrupt faults. Noise and outliers are added to the test signals. The WRM and RBF filters result in a noise reduction of 54 - 71 and 59 - 73% for the test signals considered in this study, respectively. Their performance is much better than the moving average FIR filter, which causes significant feature distortion and has poor outlier removal capabilities and shows the potential of soft computing methods for specific signal-processing applications.