Exploring isospectral spring-mass systems with firefly algorithm

This paper investigates in-line spring-mass systems (An), fixed at one end and free at the other, with n-degrees of freedom (d.f.). The objective is to find feasible in-line systems (B(n)) that are isospectral to a given system. The spring-mass systems, A(n) and B(n), are represented by Jacobi matrices. An error function is developed with the help of the Jacobi matrices A(n) and B(n). The problem of finding the isospectral systems is posed as an optimization problem with the aim of minimizing the error function. The approach for creating isospectral systems uses the fact that the trace of two isospectral Jacobi matrices A(n) and B(n) should be identical. A modification is made to the diagonal elements of the given Jacobi matrix (A(n)), to create the isospectral systems. The optimization problem is solved using the firefly algorithm augmented by a local search procedure. Numerical results are obtained and resulting isospectral systems are shown for 4 d.f. and 10 d.f. systems.

A fast algorithm for finding frequent episodes in event streams

Frequent episode discovery is a popular framework for mining data available as a long sequence of events. An episode is essentially a short ordered sequence of event types and the frequency of an episode is some suitable measure of how often the episode occurs in the data sequence. Recently,we proposed a new frequency measure for episodes based on the notion of non-overlapped occurrences of episodes in the event sequence, and showed that, such a definition, in addition to yielding computationally efficient algorithms, has some important theoretical properties in connecting frequent episode discovery with HMM learning. This paper presents some new algorithms for frequent episode discovery under this non-overlapped occurrences-based frequency definition. The algorithms presented here are better (by a factor of N, where N denotes the size of episodes being discovered) in terms of both time and space complexities when compared to existing methods for frequent episode discovery. We show through some simulation experiments, that our algorithms are very efficient. The new algorithms presented here have arguably the least possible orders of spaceand time complexities for the task of frequent episode discovery.

On the magnetization reversal of the oxide-based exchange spring magnet

The role of the soft phase (Ni0.8Zn0.2Fe2O4) on the magnetization reversal and coercivity mechanism of the Ni0.8Zn0.2Fe2O4/BaFe12O19 nanocomposite has been investigated. The presence of the interacting field and the disorder in the nanocomposite has been confirmed by the variation of Jr/Jr(∞) vs Jd/Jr(∞) and the irreversible magnetization. To understand the relative strength of the pinning and the nucleation, the magnetic viscosity measurement has been done and the thermal activation volume has been estimated. From the Barbier plot and the activation volume measurement, the dominant mechanism governing the magnetization reversal process has been proposed.

Fast algorithms for frequent episode discovery in event sequences

In this paper we consider the process of discovering frequent episodes in event sequences. The most computationally intensive part of this process is that of counting the frequencies of a set of candidate episodes. We present two new frequency counting algorithms for speeding up this part. These, referred to as non-overlapping and non-inteleaved frequency counts, are based on directly counting suitable subsets of the occurrences of an episode. Hence they are different from the frequency counts of Mannila et al [1], where they count the number of windows in which the episode occurs. Our new frequency counts offer a speed-up factor of 7 or more on real and synthetic datasets. We also show how the new frequency counts can be used when the events in episodes have time-durations as well.

Generalized frequent episodes in Event Sequences

Discovering patterns in temporal data is an important task in Data Mining. A successful method for this was proposed by Mannila et al. [1] in 1997. In their framework, mining for temporal patterns in a database of sequences of events is done by discovering the so called frequent episodes. These episodes characterize interesting collections of events occurring relatively close to each other in some partial order. However, in this framework(and in many others for finding patterns in event sequences), the ordering of events in an event sequence is the only allowed temporal information. But there are many applications where the events are not instantaneous; they have time durations. Interesting episodesthat we want to discover may need to contain information regarding event durations etc. In this paper we extend Mannila et al.’s framework to tackle such issues. In our generalized formulation, episodes are defined so that much more temporal information about events can be incorporated into the structure of an episode. This significantly enhances the expressive capability of the rules that can be discovered in the frequent episode framework. We also present algorithms for discovering such generalized frequent episodes.

Delay Optimal Event Detection on Ad Hoc Wireless Sensor Networks

We consider a small extent sensor network for event detection, in which nodes periodically take samples and then contend over a random access network to transmit their measurement packets to the fusion center. We consider two procedures at the fusion center for processing the measurements. The Bayesian setting, is assumed, that is, the fusion center has a prior distribution on the change time. In the first procedure, the decision algorithm at the fusion center is network-oblivious and makes a decision only when a complete vector of measurements taken at a sampling instant is available. In the second procedure, the decision algorithm at the fusion center is network-aware and processes measurements as they arrive, but in a time-causal order. In this case, the decision statistic depends on the network delays, whereas in the network-oblivious case, the decision statistic does not. This yields a Bayesian change-detection problem with a trade-off between the random network delay and the decision delay that is, a higher sampling rate reduces the decision delay but increases the random access delay. Under periodic sampling, in the network-oblivious case, the structure of the optimal stopping rule is the same as that without the network, and the optimal change detection delay decouples into the network delay and the optimal decision delay without the network. In the network-aware case, the optimal stopping problem is analyzed as a partially observable Markov decision process, in which the states of the queues and delays in the network need to be maintained. A sufficient decision statistic is the network state and the posterior probability of change having occurred, given the measurements received and the state of the network. The optimal regimes are studied using simulation.

A spring-mass-lever model, stiffness and inertia maps for single-input, single-output compliant mechanisms

A spring-mass-lever (SML) model is introduced in this paper for a single-input-single-output compliant mechanism to capture its static and dynamic behavior. The SML model is a reduced-order model, and its five parameters provide physical insight and quantify the stiffness and inertia(1) at the input and output ports as well as the transformation of force and displacement between the input and output. The model parameters can be determined with reasonable accuracy without performing dynamic or modal analysis. The paper describes two uses of the SML model: computationally efficient analysis of a system of which the compliant mechanism is a part; and design of compliant mechanisms for the given user-specifications. During design, the SML model enables determining the feasible parameter space of user-specified requirements, assessing the suitability of a compliant mechanism to meet the user-specifications and also selecting and/or re-designing compliant mechanisms from an existing database. Manufacturing constraints, material choice, and other practical considerations are incorporated into this methodology. A micromachined accelerometer and a valve mechanism are used as examples to show the effectiveness of the SML model in analysis and design. (C) 2012 Published by Elsevier Ltd.

Analysis of large-amplitude stratospheric mountain wave event observed from the AIRS and MLS sounders over the western Himalayan region

Mountain waves in the stratosphere have been observed over elevated topographies using both nadir-looking and limb-viewing satellites. However, the characteristics of mountain waves generated over the Himalayan Mountain range and the adjacent Tibetan Plateau are relatively less explored. The present study reports on three-dimensional (3-D) properties of a mountain wave event that occurred over the western Himalayan region on 9 December 2008. Observations made by the Atmospheric Infrared Sounder on board the Aqua and Microwave Limb Sounder on board the Aura satellites are used to delineate the wave properties. The observed wave properties such as horizontal (lambda(x), lambda(y)) and vertical (lambda(z)) wavelengths are 276 km (zonal), 289 km (meridional), and 25 km, respectively. A good agreement is found between the observed and modeled/analyzed vertical wavelength for a stationary gravity wave determined using the Modern Era Retrospective Analysis for Research and Applications (MERRA) reanalysis winds. The analysis of both the National Centers for Environmental Prediction/National Center for Atmospheric Research reanalysis and MERRA winds shows that the waves are primarily forced by strong flow across the topography. Using the 3-D properties of waves and the corrected temperature amplitudes, we estimated wave momentum fluxes of the order of similar to 0.05 Pa, which is in agreement with large-amplitude mountain wave events reported elsewhere. In this regard, the present study is considered to be very much informative to the gravity wave drag schemes employed in current general circulation models for this region.

Exchange-spring mechanism of soft and hard ferrite nanocomposites

The paper reports exchange-spring soft and hard ferrite nanocomposites synthesized by chemical co-precipitation with or without the application of ultrasonic vibration. The composites contained BaFe12O19 as the hard phase and CoFe2O4/MgFe2O4 as the soft phase. X-ray diffraction patterns of the samples in the optimum calcined condition indicated the presence of soft ferrites as face-centred cubic (fcc) and hard ferrites as hexagonal close packed (hcp) structure respectively. Temperature dependence of magnetization in the range of 20-700 degrees C demonstrated distinct presence of soft and hard ferrites as magnetic phases which are characterized by wide difference in magnetic anisotropy and coercivity. Exchange-spring mechanism led these nanocomposite systems to exchange-coupled, which ultimately produced convex hysteresis loops characteristic of a single-phase permanent magnet. Fairly high value of coercivity and maximum energy product were observed for the samples in the optimum calcined conditions with a maximum applied field of 1600 kA/m (2 T).

Analysis of large-amplitude stratospheric mountain wave event observed from the AIRS and MLS sounders over the western Himalayan region

Mountain waves in the stratosphere have been observed over elevated topographies using both nadir-looking and limb-viewing satellites. However, the characteristics of mountain waves generated over the Himalayan Mountain range and the adjacent Tibetan Plateau are relatively less explored. The present study reports on three-dimensional (3-D) properties of a mountain wave event that occurred over the western Himalayan region on 9 December 2008. Observations made by the Atmospheric Infrared Sounder on board the Aqua and Microwave Limb Sounder on board the Aura satellites are used to delineate the wave properties. The observed wave properties such as horizontal (lambda(x), lambda(y)) and vertical (lambda(z)) wavelengths are 276 km (zonal), 289 km (meridional), and 25 km, respectively. A good agreement is found between the observed and modeled/analyzed vertical wavelength for a stationary gravity wave determined using the Modern Era Retrospective Analysis for Research and Applications (MERRA) reanalysis winds. The analysis of both the National Centers for Environmental Prediction/National Center for Atmospheric Research reanalysis and MERRA winds shows that the waves are primarily forced by strong flow across the topography. Using the 3-D properties of waves and the corrected temperature amplitudes, we estimated wave momentum fluxes of the order of similar to 0.05 Pa, which is in agreement with large-amplitude mountain wave events reported elsewhere. In this regard, the present study is considered to be very much informative to the gravity wave drag schemes employed in current general circulation models for this region.

Investigation on non-exchange spring behaviour and exchange spring behaviour: A first order reversal curve analysis

The First Order Reversal Curve (FORC) method has been utilised to understand the magnetization reversal and the extent of the irreversible magnetization of the soft CoFe2O4-hard SrFe12O19 nanocomposite in the nonexchange spring and the exchange spring regime. The single peak switching behaviour in the FORC distribution of the exchange spring composite confirms the coherent reversal of the soft and hard phases. The onset of the nucleation field and the magnetization reversal by domain wall movement are also evident from the FORC measurements. (C) 2013 AIP Publishing LLC.

Simulations and experiments in punching spring-steel devices with sub-millimeter features

This work demonstrates the feasibility of mesoscale (100 μm to mm) punching of multiple holes of intricate shapes in metals. Analytical modeling, finite element (FE)simulation, and experimentations are used in this work. Two dimensional FE simulations in ABAQUS were done with an assumed material modeling and plane-strain condition. A known analytical model was used and compared with the ABAQUS simulation results to understand the effects of clearance between the punch and the die. FE simulation in ABAQUS was done for different clearances and corner radii at punch, die, and holder. A set of punches and dies were used to punch out a miniature spring-steel gripper. Comparison of compliant grippers manufactured by wire-cut electro discharge machining(EDM) and punching shows that realizing sharp interior and re-entrant corners by punching is not easy to achieve. Punching of circular holes with 5 mm and 2.5 mm diameter is achieved. The possibility of realizing meso-scale parts with complicated shapes through punching is demonstrated in this work; and some strategies are suggested for improvement.