Nonlinear dynamic state estimation in instrumented structures with conditionally linear Gaussian substructures

Many problems of state estimation in structural dynamics permit a partitioning of system states into nonlinear and conditionally linear substructures. This enables a part of the problem to be solved exactly, using the Kalman filter, and the remainder using Monte Carlo simulations. The present study develops an algorithm that combines sequential importance sampling based particle filtering with Kalman filtering to a fairly general form of process equations and demonstrates the application of a substructuring scheme to problems of hidden state estimation in structures with local nonlinearities, response sensitivity model updating in nonlinear systems, and characterization of residual displacements in instrumented inelastic structures. The paper also theoretically demonstrates that the sampling variance associated with the substructuring scheme used does not exceed the sampling variance corresponding to the Monte Carlo filtering without substructuring. (C) 2012 Elsevier Ltd. All rights reserved.

A Comparative Kinetic and Thermodynamic Perspective of the sigma-Competition Model in Escherichia coli

Transcription is the most fundamental step in gene expression in any living organism. Various environmental cues help in the maturation of core RNA polymerase (RNAP; alpha(2)beta beta'omega) with different sigma-factors, leading to the directed recruitment of RNAP to different promoter DNA sequences. Thus it is essential to determine the sigma-factors that affect the preferential partitioning of core RNAP among various a-actors, and the role of sigma-switching in transcriptional gene regulation. Further, the macromolecular assembly of holo RNAP takes place in an extremely crowded environment within a cell, and thus far the kinetics and thermodynamics of this molecular recognition process have not been well addressed. In this study we used a site-directed bioaffinity immobilization method to evaluate the relative binding affinities of three different Escherichia coli sigma-factors to the same core RNAP with variations in temperature and ionic strength while emulating the crowded cellular milieu. Our data indicate that the interaction of core RNAP-sigma is susceptible to changes in external stimuli such as osmolytic and thermal stress, and the degree of susceptibility varies among different sigma-factors. This allows for a reversible sigma-switching from housekeeping factors to alternate sigma-factors when the organism senses a change in its physiological conditions.

NUcache: an efficient multicore cache organization based on next-use distance

The effectiveness of the last-level shared cache is crucial to the performance of a multi-core system. In this paper, we observe and make use of the DelinquentPC - Next-Use characteristic to improve shared cache performance. We propose a new PC-centric cache organization, NUcache, for the shared last level cache of multi-cores. NUcache logically partitions the associative ways of a cache set into MainWays and DeliWays. While all lines have access to the MainWays, only lines brought in by a subset of delinquent PCs, selected by a PC selection mechanism, are allowed to enter the DeliWays. The PC selection mechanism is an intelligent cost-benefit analysis based algorithm that utilizes Next-Use information to select the set of PCs that can maximize the hits experienced in DeliWays. Performance evaluation reveals that NUcache improves the performance over a baseline design by 9.6%, 30% and 33% respectively for dual, quad and eight core workloads comprised of SPEC benchmarks. We also show that NUcache is more effective than other well-known cache-partitioning algorithms.

Low-pass filters and differential tympanal tuning in a paleotropical bushcricket with an unusually low frequency call

Low-frequency sounds are advantageous for long-range acoustic signal transmission, but for small animals they constitute a challenge for signal detection and localization. The efficient detection of sound in insects is enhanced by mechanical resonance either in the tracheal or tympanal system before subsequent neuronal amplification. Making small structures resonant at low sound frequencies poses challenges for insects and has not been adequately studied. Similarly, detecting the direction of long-wavelength sound using interaural signal amplitude and/or phase differences is difficult for small animals. Pseudophylline bushcrickets predominantly call at high, often ultrasonic frequencies, but a few paleotropical species use lower frequencies. We investigated the mechanical frequency tuning of the tympana of one such species, Onomarchus uninotatus, a large bushcricket that produces a narrow bandwidth call at an unusually low carrier frequency of 3.2. kHz. Onomarchus uninotatus, like most bushcrickets, has two large tympanal membranes on each fore-tibia. We found that both these membranes vibrate like hinged flaps anchored at the dorsal wall and do not show higher modes of vibration in the frequency range investigated (1.5-20. kHz). The anterior tympanal membrane acts as a low-pass filter, attenuating sounds at frequencies above 3.5. kHz, in contrast to the high-pass filter characteristic of other bushcricket tympana. Responses to higher frequencies are partitioned to the posterior tympanal membrane, which shows maximal sensitivity at several broad frequency ranges, peaking at 3.1, 7.4 and 14.4. kHz. This partitioning between the two tympanal membranes constitutes an unusual feature of peripheral auditory processing in insects. The complex tracheal shape of O. uninotatus also deviates from the known tube or horn shapes associated with simple band-pass or high-pass amplification of tracheal input to the tympana. Interestingly, while the anterior tympanal membrane shows directional sensitivity at conspecific call frequencies, the posterior tympanal membrane is not directional at conspecific frequencies and instead shows directionality at higher frequencies.

USHA: unified software and hardware architecture for video decoding

Video decoders used in emerging applications need to be flexible to handle a large variety of video formats and deliver scalable performance to handle wide variations in workloads. In this paper we propose a unified software and hardware architecture for video decoding to achieve scalable performance with flexibility. The light weight processor tiles and the reconfigurable hardware tiles in our architecture enable software and hardware implementations to co-exist, while a programmable interconnect enables dynamic interconnection of the tiles. Our process network oriented compilation flow achieves realization agnostic application partitioning and enables seamless migration across uniprocessor, multi-processor, semi hardware and full hardware implementations of a video decoder. An application quality of service aware scheduler monitors and controls the operation of the entire system. We prove the concept through a prototype of the architecture on an off-the-shelf FPGA. The FPGA prototype shows a scaling in performance from QCIF to 1080p resolutions in four discrete steps. We also demonstrate that the reconfiguration time is short enough to allow migration from one configuration to the other without any frame loss.

Feature weighting for clustering by particle swarm optimization

Clustering has been the most popular method for data exploration. Clustering is partitioning the data set into sub-partitions based on some measures say the distance measure, each partition has its own significant information. There are a number of algorithms explored for this purpose, one such algorithm is the Particle Swarm Optimization(PSO) which is a population based heuristic search technique derived from swarm intelligence. In this paper we present an improved version of the Particle Swarm Optimization where, each feature of the data set is given significance accordingly by adding some random weights, which also minimizes the distortions in the dataset if any. The performance of the above proposed algorithm is evaluated using some benchmark datasets from Machine Learning Repository. The experimental results shows that our proposed methodology performs significantly better than the previously performed experiments.

Efficient Cache Exploration Method for a Tiled Chip Multiprocessor

Past studies use deterministic models to evaluate optimal cache configuration or to explore its design space. However, with the increasing number of components present on a chip multiprocessor (CMP), deterministic approaches do not scale well. Hence, we apply probabilistic genetic algorithms (GA) to determine a near-optimal cache configuration for a sixteen tiled CMP. We propose and implement a faster trace based approach to estimate fitness of a chromosome. It shows up-to 218x simulation speedup over the cycle-accurate architectural simulation. Our methodology can be applied to solve other cache optimization problems such as design space exploration of cache and its partitioning among applications/ virtual machines.

A divide and conquer strategy for scaling weather simulations with multiple regions of interest

Accurate and timely prediction of weather phenomena, such as hurricanes and flash floods, require high-fidelity compute intensive simulations of multiple finer regions of interest within a coarse simulation domain. Current weather applications execute these nested simulations sequentially using all the available processors, which is sub-optimal due to their sub-linear scalability. In this work, we present a strategy for parallel execution of multiple nested domain simulations based on partitioning the 2-D processor grid into disjoint rectangular regions associated with each domain. We propose a novel combination of performance prediction, processor allocation methods and topology-aware mapping of the regions on torus interconnects. Experiments on IBM Blue Gene systems using WRF show that the proposed strategies result in performance improvement of up to 33% with topology-oblivious mapping and up to additional 7% with topology-aware mapping over the default sequential strategy.

Analysis of the degrees-of-freedom of spatial parallel manipulators in regular and singular configurations

This paper presents a study of the nature of the degrees-of-freedom of spatial manipulators based on the concept of partition of degrees-of-freedom. In particular, the partitioning of degrees-of-freedom is studied in five lower-mobility spatial parallel manipulators possessing different combinations of degrees-of-freedom. An extension of the existing theory is introduced so as to analyse the nature of the gained degree(s)-of-freedom at a gain-type singularity. The gain of one- and two-degrees-of-freedom is analysed in several well-studied, as well as newly developed manipulators. The formulations also present a basis for the analysis of the velocity kinematics of manipulators of any architecture. (C) 2013 Elsevier Ltd. All rights reserved.

Modified particle swarm optimization for pattern clustering

Data clustering is a common technique for statistical data analysis, which is used in many fields, including machine learning and data mining. Clustering is grouping of a data set or more precisely, the partitioning of a data set into subsets (clusters), so that the data in each subset (ideally) share some common trait according to some defined distance measure. In this paper we present the genetically improved version of particle swarm optimization algorithm which is a population based heuristic search technique derived from the analysis of the particle swarm intelligence and the concepts of genetic algorithms (GA). The algorithm combines the concepts of PSO such as velocity and position update rules together with the concepts of GA such as selection, crossover and mutation. The performance of the above proposed algorithm is evaluated using some benchmark datasets from Machine Learning Repository. The performance of our method is better than k-means and PSO algorithm.

A Diffusion-Based Processor Reallocation Strategy for Tracking Multiple Dynamically Varying Weather Phenomena

Many meteorological phenomena occur at different locations simultaneously. These phenomena vary temporally and spatially. It is essential to track these multiple phenomena for accurate weather prediction. Efficient analysis require high-resolution simulations which can be conducted by introducing finer resolution nested simulations, nests at the locations of these phenomena. Simultaneous tracking of these multiple weather phenomena requires simultaneous execution of the nests on different subsets of the maximum number of processors for the main weather simulation. Dynamic variation in the number of these nests require efficient processor reallocation strategies. In this paper, we have developed strategies for efficient partitioning and repartitioning of the nests among the processors. As a case study, we consider an application of tracking multiple organized cloud clusters in tropical weather systems. We first present a parallel data analysis algorithm to detect such clouds. We have developed a tree-based hierarchical diffusion method which reallocates processors for the nests such that the redistribution cost is less. We achieve this by a novel tree reorganization approach. We show that our approach exhibits up to 25% lower redistribution cost and 53% lesser hop-bytes than the processor reallocation strategy that does not consider the existing processor allocation.

Curvature based mobility analysis and form closure of smooth planar curves with multiple contacts

This paper presents a simple second-order, curvature based mobility analysis of planar curves in contact. The underlying theory deals with penetration and separation of curves with multiple contacts, based on relative configuration of osculating circles at points of contact for a second-order rotation about each point of the plane. Geometric and analytical treatment of mobility analysis is presented for generic as well as special contact geometries. For objects with a single contact, partitioning of the plane into four types of mobility regions has been shown. Using point based composition operations based on dual-number matrices, analysis has been extended to computationally handle multiple contacts scenario. A novel color coded directed line has been proposed to capture the contact scenario. Multiple contacts mobility is obtained through intersection of the mobility half-spaces. It is derived that mobility region comprises a pair of unbounded or a single bounded convex polygon. The theory has been used for analysis and synthesis of form closure configurations, revolute and prismatic kinematic pairs. (C) 2013 Elsevier Ltd. All rights reserved.

Allosteric regulation and substrate activation in cytosolic nucleotidase II from Legionella pneumophila

Cytosolic nucleotidase II (cN-II) from Legionellapneumophila (Lp) catalyzes the hydrolysis of GMP and dGMP displaying sigmoidal curves, whereas catalysis of IMP hydrolysis displayed a biphasic curve in the initial rate versus substrate concentration plots. Allosteric modulators of mammalian cN-II did not activate LpcN-II although GTP, GDP and the substrate GMP were specific activators. Crystal structures of the tetrameric LpcN-II revealed an activator-binding site at the dimer interface. A double mutation in this allosteric-binding site abolished activation, confirming the structural observations. The substrate GMP acting as an activator, partitioning between the allosteric and active site, is the basis for the sigmoidicity of the initial velocity versus GMP concentration plot. The LpcN-II tetramer showed differences in subunit organization upon activator binding that are absent in the activator-bound human cN-II structure. This is the first observation of a structural change induced by activator binding in cN-II that may be the molecular mechanism for enzyme activation. DatabaseThe coordinates and structure factors reported in this paper have been submitted to the Protein Data Bank under the accession numbers and . The accession number of GMP complexed LpcN-II is . Structured digital abstract andby() andby() Structured digital abstract was added on 5 March 2014 after original online publication]

Divvying up an incubator: How parasitic and mutualistic fig wasps use space within their nursery microcosm

Differential occupancy of space can lead to species coexistence. The fig-fig wasp pollination system hosts species-specific pollinating and parasitic wasps that develop within galls in a nursery comprising a closed inflorescence, the syconium. This microcosm affords excellent opportunities for investigating spatial partitioning since it harbours a closed community in which all wasp species are dependent on securing safe sites inside the syconium for their developing offspring while differing in life history, egg deposition strategies and oviposition times relative to nursery development. We determined ontogenetic changes in oviposition sites available to the seven-member fig wasp community of Ficus racemosa comprising pollinators, gallers and parasitoids. We used species distribution models (SDMs) for the first time at a microcosm scale to predict patterns of spatial occurrence of nursery occupants. SDMs gave high true-positive and low false-positive site occupancy rates for most occupants indicating species specificity in oviposition sites. The nursery microcosm itself changed with syconium development and sequential egg-laying by different wasp species. The number of sites occupied by offspring of the different wasp species was negatively related to the risk of syconium abortion by the plant host following oviposition. Since unpollinated syconia are usually aborted, parasitic wasps ovipositing into nurseries at the same time as the pollinator targeted many sites, suggesting response to lower risk of syconium abortion owing to reduced risk of pollination failure compared to those species ovipositing before pollination. Wasp life history and oviposition time relative to nursery development contributed to the co-existence of nursery occupants.

Length-scale dependent mechanical properties of Al-Cu eutectic alloy: Molecular dynamics based model and its experimental verification

This paper attempts to gain an understanding of the effect of lamellar length scale on the mechanical properties of two-phase metal-intermetallic eutectic structure. We first develop a molecular dynamics model for the in-situ grown eutectic interface followed by a model of deformation of Al-Al2Cu lamellar eutectic. Leveraging the insights obtained from the simulation on the behaviour of dislocations at different length scales of the eutectic, we present and explain the experimental results on Al-Al2Cu eutectic with various different lamellar spacing. The physics behind the mechanism is further quantified with help of atomic level energy model for different length scale as well as different strain. An atomic level energy partitioning of the lamellae and the interface regions reveals that the energy of the lamellae core are accumulated more due to dislocations irrespective of the length-scale. Whereas the energy of the interface is accumulated more due to dislocations when the length-scale is smaller, but the trend is reversed when the length-scale is large beyond a critical size of about 80 nm. (C) 2014 Author(s).