Iterated stochastic filters with additive updates for dynamic system identification: Annealing-type iterations and the filter bank

A nonlinear stochastic filtering scheme based on a Gaussian sum representation of the filtering density and an annealing-type iterative update, which is additive and uses an artificial diffusion parameter, is proposed. The additive nature of the update relieves the problem of weight collapse often encountered with filters employing weighted particle based empirical approximation to the filtering density. The proposed Monte Carlo filter bank conforms in structure to the parent nonlinear filtering (Kushner-Stratonovich) equation and possesses excellent mixing properties enabling adequate exploration of the phase space of the state vector. The performance of the filter bank, presently assessed against a few carefully chosen numerical examples, provide ample evidence of its remarkable performance in terms of filter convergence and estimation accuracy vis-a-vis most other competing filters especially in higher dimensional dynamic system identification problems including cases that may demand estimating relatively minor variations in the parameter values from their reference states. (C) 2014 Elsevier Ltd. All rights reserved.

Influence of dynamic operating conditions on the performance of metal hydride based solid sorption cooling systems

The performance of metal hydride based solid sorption cooling systems depends on the driving pressure differential, and the rate of hydrogen transfer between coupled metal hydride beds during cooling and regeneration processes. Conventionally, the mid-plateau pressure difference obtained from `static' equilibrium PCT data are used for the thermodynamic analysis. It is well known that the processes are `dynamic' because the pressure and temperature, and hence the concentration of the hydride beds, are continuously changing. Keeping this in mind, the pair of La0.9Ce0.1Ni5 - LaNi4.7Al0.3 metal hydrides suitable for solid sorption cooling systems were characterised using both static and dynamic methods. It was found that the PCT characteristics, and the resulting enthalpy (Delta H) and entropy (Delta S) values, were significantly different for static and dynamic modes of measurements. In the present study, the solid sorption metal hydride cooling system is analysed taking in to account the actual variation in the pressure difference (Delta P) and the dynamic enthalpy values. Compared to `static' property based analysis, significant decrease in the driving potentials and transferrable amounts of hydrogen, leading to decrease in cooling capacity by 57.8% and coefficient of performance by 31.9% are observed when dynamic PCT data at the flow rate of 80 ml/min are considered. Copyright 2014 (C) Hydrogen Energy Publications, LLC. Published by Elsevier Ltd. All rights reserved.

Trace Driven Dynamic Deadlock Detection and Reproduction

Dynamic analysis techniques have been proposed to detect potential deadlocks. Analyzing and comprehending each potential deadlock to determine whether the deadlock is feasible in a real execution requires significant programmer effort. Moreover, empirical evidence shows that existing analyses are quite imprecise. This imprecision of the analyses further void the manual effort invested in reasoning about non-existent defects. In this paper, we address the problems of imprecision of existing analyses and the subsequent manual effort necessary to reason about deadlocks. We propose a novel approach for deadlock detection by designing a dynamic analysis that intelligently leverages execution traces. To reduce the manual effort, we replay the program by making the execution follow a schedule derived based on the observed trace. For a real deadlock, its feasibility is automatically verified if the replay causes the execution to deadlock. We have implemented our approach as part of WOLF and have analyzed many large (upto 160KLoC) Java programs. Our experimental results show that we are able to identify 74% of the reported defects as true (or false) positives automatically leaving very few defects for manual analysis. The overhead of our approach is negligible making it a compelling tool for practical adoption.

Effects of temperature and clay content on water absorption characteristics of modified MMT clay/cyclic olefin copolymer nanocomposite films: Permeability, dynamic mechanical properties and the encapsulated organic device performance

In the present study, amino-silane modified layered organosilicates were used to reinforce cyclic olefin copolymer to enhance the thermal, mechanical and moisture impermeable barrier properties. The optimum clay loading (4%) in the nanocomposite increases the thermal stability of the film while further loading decreases film stability. Water absorption behavior at 62 degrees C was carried out and compared with the behavior at room temperature and 48 degrees C. The stiffness of the matrix increases with clay content and the recorded strain to failure for the composite films was lower than the neat film. Dynamic mechanical analysis show higher storage modulus and low loss modulus for 2.5-4 wt% clay loading. Calcium degradation test and device encapsulation also show the evidence of optimum clay loading of 4 wt% for improved low water vapor transmission rates compared to other nanocomposite films. (C) 2014 Elsevier Ltd. All rights reserved.

Bayesian parameter identification in dynamic state space models using modified measurement equations

When Markov chain Monte Carlo (MCMC) samplers are used in problems of system parameter identification, one would face computational difficulties in dealing with large amount of measurement data and (or) low levels of measurement noise. Such exigencies are likely to occur in problems of parameter identification in dynamical systems when amount of vibratory measurement data and number of parameters to be identified could be large. In such cases, the posterior probability density function of the system parameters tends to have regions of narrow supports and a finite length MCMC chain is unlikely to cover pertinent regions. The present study proposes strategies based on modification of measurement equations and subsequent corrections, to alleviate this difficulty. This involves artificial enhancement of measurement noise, assimilation of transformed packets of measurements, and a global iteration strategy to improve the choice of prior models. Illustrative examples cover laboratory studies on a time variant dynamical system and a bending-torsion coupled, geometrically non-linear building frame under earthquake support motions. (C) 2015 Elsevier Ltd. All rights reserved.

PriDyn: Enabling Differentiated I/O Services in Cloud Using Dynamic Priorities

Virtualization is one of the key enabling technologies for Cloud computing. Although it facilitates improved utilization of resources, virtualization can lead to performance degradation due to the sharing of physical resources like CPU, memory, network interfaces, disk controllers, etc. Multi-tenancy can cause highly unpredictable performance for concurrent I/O applications running inside virtual machines that share local disk storage in Cloud. Disk I/O requests in a typical Cloud setup may have varied requirements in terms of latency and throughput as they arise from a range of heterogeneous applications having diverse performance goals. This necessitates providing differential performance services to different I/O applications. In this paper, we present PriDyn, a novel scheduling framework which is designed to consider I/O performance metrics of applications such as acceptable latency and convert them to an appropriate priority value for disk access based on the current system state. This framework aims to provide differentiated I/O service to various applications and ensures predictable performance for critical applications in multi-tenant Cloud environment. We demonstrate through experimental validations on real world I/O traces that this framework achieves appreciable enhancements in I/O performance, indicating that this approach is a promising step towards enabling QoS guarantees on Cloud storage.

Spatio-temporal correlations in aqueous systems: computational studies of static and dynamic heterogeneity by 2D-IR spectroscopy

Local heterogeneity is ubiquitous in natural aqueous systems. It can be caused locally by external biomolecular subsystems like proteins, DNA, micelles and reverse micelles, nanoscopic materials etc., but can also be intrinsic to the thermodynamic nature of the aqueous solution itself (like binary mixtures or at the gas-liquid interface). The altered dynamics of water in the presence of such diverse surfaces has attracted considerable attention in recent years. As these interfaces are quite narrow, only a few molecular layers thick, they are hard to study by conventional methods. The recent development of two dimensional infra-red (2D-IR) spectroscopy allows us to estimate length and time scales of such dynamics fairly accurately. In this work, we present a series of interesting studies employing two dimensional infra-red spectroscopy (2D-IR) to investigate (i) the heterogeneous dynamics of water inside reverse micelles of varying sizes, (ii) supercritical water near the Widom line that is known to exhibit pronounced density fluctuations and also study (iii) the collective and local polarization fluctuation of water molecules in the presence of several different proteins. The spatio-temporal correlation of confined water molecules inside reverse micelles of varying sizes is well captured through the spectral diffusion of corresponding 2D-IR spectra. In the case of supercritical water also, we observe a strong signature of dynamic heterogeneity from the elongated nature of the 2D-IR spectra. In this case the relaxation is ultrafast. We find remarkable agreement between the different tools employed to study the relaxation of density heterogeneity. For aqueous protein solutions, we find that the calculated dielectric constant of the respective systems unanimously shows a noticeable increment compared to that of neat water. However, the `effective' dielectric constant for successive layers shows significant variation, with the layer adjacent to the protein having a much lower value. Relaxation is also slowest at the surface. We find that the dielectric constant achieves the bulk value at distances more than 3 nm from the surface of the protein.

Direct measurements of growing amorphous order and non-monotonic dynamic correlations in a colloidal glass-former

The transformation of flowing liquids into rigid glasses is thought to involve increasingly cooperative relaxation dynamics as the temperature approaches that of the glass transition. However, the precise nature of this motion is unclear, and a complete understanding of vitrification thus remains elusive. Of the numerous theoretical perspectives(1-4) devised to explain the process, random first-order theory (RFOT; refs 2,5) is a well-developed thermodynamic approach, which predicts a change in the shape of relaxing regions as the temperature is lowered. However, the existence of an underlying `ideal' glass transition predicted by RFOT remains debatable, largely because the key microscopic predictions concerning the growth of amorphous order and the nature of dynamic correlations lack experimental verification. Here, using holographic optical tweezers, we freeze a wall of particles in a two-dimensional colloidal glass-forming liquid and provide direct evidence for growing amorphous order in the form of a static point-to-set length. We uncover the non-monotonic dependence of dynamic correlations on area fraction and show that this non-monotonicity follows directly from the change in morphology and internal structure of cooperatively rearranging regions(6,7). Our findings support RFOT and thereby constitute a crucial step in distinguishing between competing theories of glass formation.

Dynamic compression behavior of reactive spark plasma sintered ultrafine grained (Hf, Zr)B-2-SiC composites

This paper reports the dynamic compression behavior of ultrafine grained (Hf, Zr)B-2-SiC composites, sintered using reactive spark plasma sintering at 1600 degrees C for 10 min. Dynamic strength of similar to 2.3 GPa has been measured using Split Hopkinson Pressure Bar (SHPB) tests in a reproducible manner at strain rates of 800-1300 s(-1). A comparison with competing boride based armor ceramics, in reference to the spectrum of properties evaluated, establishes the potential of (Hf, Zr)B-2-SiC composites for armor applications. (C) 2015 Elsevier Ltd and Techna Group S.r.l. All rights reserved.

Strengthening and weakening by repeated dynamic impact in microcrystals and nanocrystals

Experiments on micrograined (mg) and nanocrystalline (nc) Ni revealed strengthening and weakening following repeated dynamic impact. The strengthening in mg-Ni arises from intragranular dislocations without a significant change in grain size, whereas the weakening in nc-Ni is due to concurrent grain growth. The strength of mg and nc-Ni samples after deformation settles at similar to 900 MPa, with differing contributions from intragranular dislocations and grain sizes. (C) 2015 Elsevier B.V. All rights reserved.

Dynamic response of a piezoelectric flapping wing

Piezo-composite membranes have advantages over motorized flapping where frequencies are high and certain coupling between bending and twisting is useful to generate lift and forward flight. We draw examples of fruit fly and bumble bee. Wings with Piezo ceramic PZT coating are realized. The passive mechanical response of the wing is characterized experimentally and validated using finite element simulation. Piezoelectric actuation with uniform electrode coating is characterized and optimal frequencies for flapping are identified. The experimental data are used in an empirical model and advanced ratio for a flapping insect like condition for various angular orientations is estimated.

ANRC Hybrid Test Bed Implementation and an End-to-End Performance Characterization of Dynamic Spectrum Access

An abundance of spectrum access and sensing algorithms are available in the dynamic spectrum access (DSA) and cognitive radio (CR) literature. Often, however, the functionality and performance of such algorithms are validated against theoretical calculations using only simulations. Both the theoretical calculations and simulations come with their attendant sets of assumptions. For instance, designers of dynamic spectrum access algorithms often take spectrum sensing and rendezvous mechanisms between transmitter-receiver pairs for granted. Test bed designers, on the other hand, either customize so much of their design that it becomes difficult to replicate using commercial off the shelf (COTS) components or restrict themselves to simulation, emulation /hardware-in-Ioop (HIL), or pure hardware but not all three. Implementation studies on test beds sophisticated enough to combine the three aforementioned aspects, but at the same time can also be put together using COTS hardware and software packages are rare. In this paper we describe i) the implementation of a hybrid test bed using a previously proposed hardware agnostic system architecture ii) the implementation of DSA on this test bed, and iii) the realistic hardware and software-constrained performance of DSA. Snapshot energy detector (ED) and Cumulative Summation (CUSUM), a sequential change detection algorithm, are available for spectrum sensing and a two-way handshake mechanism in a dedicated control channel facilitates transmitter-receiver rendezvous.

Performance of New Dynamic Benefit-Weighted Scheduling Scheme in DiffServ Networks

In this paper, we design a new dynamic packet scheduling scheme suitable for differentiated service (DiffServ) network. Designed dynamic benefit weighted scheduling (DBWS) uses a dynamic weighted computation scheme loosely based on weighted round robin (WRR) policy. It predicts the weight required by expedited forwarding (EF) service for the current time slot (t) based on two criteria; (i) previous weight allocated to it at time (t-1), and (ii) the average increase in the queue length of EF buffer. This prediction provides smooth bandwidth allocation to all the services by avoiding overbooking of resources for EF service and still providing guaranteed services for it. The performance is analyzed for various scenarios at high, medium and low traffic conditions. The results show that packet loss is minimized, end to end delay is minimized and jitter is reduced and therefore meet quality of service (QoS) requirement of a network.

A Perspective to Adopt Continuous Dynamic Cognition for Malicious Node Detection in Heterogeneous Networks

The current day networks use Proactive networks for adaption to the dynamic scenarios. The use of cognition technique based on the Observe, Orient, Decide and Act loop (OODA) is proposed to construct proactive networks. The network performance degradation in knowledge acquisition and malicious node presence is a problem that exists. The use of continuous time dynamic neural network is considered to achieve cognition. The variance in service rates of user nodes is used to detect malicious activity in heterogeneous networks. The improved malicious node detection rates are proved through the experimental results presented in this paper. (C) 2015 The Authors. Published by Elsevier B.V.