Grids with multiple batch systems for performance enhancement of multi-component and parameter sweep parallel applications

In this work, we evaluate the benefits of using Grids with multiple batch systems to improve the performance of multi-component and parameter sweep parallel applications by reduction in queue waiting times. Using different job traces of different loads, job distributions and queue waiting times corresponding to three different queuing policies(FCFS, conservative and EASY backfilling), we conducted a large number of experiments using simulators of two important classes of applications. The first simulator models Community Climate System Model (CCSM), a prominent multi-component application and the second simulator models parameter sweep applications. We compare the performance of the applications when executed on multiple batch systems and on a single batch system for different system and application configurations. We show that there are a large number of configurations for which application execution using multiple batch systems can give improved performance over execution on a single system.

A Joint Source-Channel Coding Scheme for Transmission of Correlated Discrete Sources over a Gaussian Multiple Access Channel

We consider the problem of transmission of correlated discrete alphabet sources over a Gaussian Multiple Access Channel (GMAC). A distributed bit-to-Gaussian mapping is proposed which yields jointly Gaussian codewords. This can guarantee lossless transmission or lossy transmission with given distortions, if possible. The technique can be extended to the system with side information at the encoders and decoder.

Multiple excitation nano-spot generation and confocal detection for far-field microscopy

An imaging technique is developed for the controlled generation of multiple excitation nano-spots for far-field microscopy. The system point spread function (PSF) is obtained by interfering two counter-propagating extended depth-of-focus PSF (DoF-PSF), resulting in highly localized multiple excitation spots along the optical axis. The technique permits (1) simultaneous excitation of multiple planes in the specimen; (2) control of the number of spots by confocal detection; and (3) overcoming the point-by-point based excitation. Fluorescence detection from the excitation spots can be efficiently achieved by Z-scanning the detector/pinhole assembly. The technique complements most of the bioimaging techniques and may find potential application in high resolution fluorescence microscopy and nanoscale imaging.

A genetic algorithm with characteristic amplification through multiple geographically isolated populations and varied fitness landscapes

This paper proposes a new approach, wherein multiple populations are evolved on different landscapes. The problem statement is broken down, to describe discrete characteristics. Each landscape, described by its fitness landscape is used to optimize or amplify a certain characteristic or set of characteristics. Individuals from each of these populations are kept geographically isolated from each other Each population is evolved individually. After a predetermined number of evolutions, the system of populations is analysed against a normalized fitness function. Depending on this score and a predefined merging scheme, the populations are merged, one at a time, while continuing evolution. Merging continues until only one final population remains. This population is then evolved, following which the resulting population will contain the optimal solution. The final resulting population will contain individuals which have been optimized against all characteristics as desired by the problem statement. Each individual population is optimized for a local maxima. Thus when populations are merged, the effect is to produce a new population which is closer to the global maxima.

A genetic algorithm with characteristic amplification through multiple geographically isolated populations and varied fitness landscapes

This paper proposes a new approach, wherein multiple populations are evolved on different landscapes. The problem statement is broken down, to describe discrete characteristics. Each landscape, described by its fitness landscape is used to optimize or amplify a certain characteristic or set of characteristics. Individuals from each of these populations are kept geographically isolated from each other Each population is evolved individually. After a predetermined number of evolutions, the system of populations is analysed against a normalized fitness function. Depending on this score and a predefined merging scheme, the populations are merged, one at a time, while continuing evolution. Merging continues until only one final population remains. This population is then evolved, following which the resulting population will contain the optimal solution. The final resulting population will contain individuals which have been optimized against all characteristics as desired by the problem statement. Each individual population is optimized for a local maxima. Thus when populations are merged, the effect is to produce a new population which is closer to the global maxima.

Selection of intrusion detection system threshold bounds for effective sensor fusion

The motivation behind the fusion of Intrusion Detection Systems was the realization that with the increasing traffic and increasing complexity of attacks, none of the present day stand-alone Intrusion Detection Systems can meet the high demand for a very high detection rate and an extremely low false positive rate. Multi-sensor fusion can be used to meet these requirements by a refinement of the combined response of different Intrusion Detection Systems. In this paper, we show the design technique of sensor fusion to best utilize the useful response from multiple sensors by an appropriate adjustment of the fusion threshold. The threshold is generally chosen according to the past experiences or by an expert system. In this paper, we show that the choice of the threshold bounds according to the Chebyshev inequality principle performs better. This approach also helps to solve the problem of scalability and has the advantage of failsafe capability. This paper theoretically models the fusion of Intrusion Detection Systems for the purpose of proving the improvement in performance, supplemented with the empirical evaluation. The combination of complementary sensors is shown to detect more attacks than the individual components. Since the individual sensors chosen detect sufficiently different attacks, their result can be merged for improved performance. The combination is done in different ways like (i) taking all the alarms from each system and avoiding duplications, (ii) taking alarms from each system by fixing threshold bounds, and (iii) rule-based fusion with a priori knowledge of the individual sensor performance. A number of evaluation metrics are used, and the results indicate that there is an overall enhancement in the performance of the combined detector using sensor fusion incorporating the threshold bounds and significantly better performance using simple rule-based fusion.

Self-regularized pseudo time-marching schemes for structural system identification with static measurements

We explore the application of pseudo time marching schemes, involving either deterministic integration or stochastic filtering, to solve the inverse problem of parameter identification of large dimensional structural systems from partial and noisy measurements of strictly static response. Solutions of such non-linear inverse problems could provide useful local stiffness variations and do not have to confront modeling uncertainties in damping, an important, yet inadequately understood, aspect in dynamic system identification problems. The usual method of least-square solution is through a regularized Gauss-Newton method (GNM) whose results are known to be sensitively dependent on the regularization parameter and data noise intensity. Finite time,recursive integration of the pseudo-dynamical GNM (PD-GNM) update equation addresses the major numerical difficulty associated with the near-zero singular values of the linearized operator and gives results that are not sensitive to the time step of integration. Therefore, we also propose a pseudo-dynamic stochastic filtering approach for the same problem using a parsimonious representation of states and specifically solve the linearized filtering equations through a pseudo-dynamic ensemble Kalman filter (PD-EnKF). For multiple sets of measurements involving various load cases, we expedite the speed of thePD-EnKF by proposing an inner iteration within every time step. Results using the pseudo-dynamic strategy obtained through PD-EnKF and recursive integration are compared with those from the conventional GNM, which prove that the PD-EnKF is the best performer showing little sensitivity to process noise covariance and yielding reconstructions with less artifacts even when the ensemble size is small.

Self-regularized pseudo time-marching schemes for structural system identification with static measurements

We explore the application of pseudo time marching schemes, involving either deterministic integration or stochastic filtering, to solve the inverse problem of parameter identification of large dimensional structural systems from partial and noisy measurements of strictly static response. Solutions of such non-linear inverse problems could provide useful local stiffness variations and do not have to confront modeling uncertainties in damping, an important, yet inadequately understood, aspect in dynamic system identification problems. The usual method of least-square solution is through a regularized Gauss-Newton method (GNM) whose results are known to be sensitively dependent on the regularization parameter and data noise intensity. Finite time, recursive integration of the pseudo-dynamical GNM (PD-GNM) update equation addresses the major numerical difficulty associated with the near-zero singular values of the linearized operator and gives results that are not sensitive to the time step of integration. Therefore, we also propose a pseudo-dynamic stochastic filtering approach for the same problem using a parsimonious representation of states and specifically solve the linearized filtering equations through apseudo-dynamic ensemble Kalman filter (PD-EnKF). For multiple sets ofmeasurements involving various load cases, we expedite the speed of the PD-EnKF by proposing an inner iteration within every time step. Results using the pseudo-dynamic strategy obtained through PD-EnKF and recursive integration are compared with those from the conventional GNM, which prove that the PD-EnKF is the best performer showing little sensitivity to process noise covariance and yielding reconstructions with less artifacts even when the ensemble size is small. Copyright (C) 2009 John Wiley & Sons, Ltd.

Effect of insertion of buffer-strip on the response of carbon-epoxy system in short beam tests

dThe work looks at the response to three-point loading of carbon-epoxy (CF-EP) composites with inserted buffer strip (BS) material. Short beam Shear tests were performed to study the load-deflection response as well as fracture features through macroscopy on the CF-EP system containing the interleaved PTFE-coated fabric material. Significant differences were noticed in the response of the CF-EP system to the bending process consequent to the architectural modification. It was inferred that introduction of small amounts of less adherent layers of material at specific locations causes a decrement in the load carrying capability. Further the number and the ease with which interface separation occurs is found to depend on the extent to which the inserted layer is present in either single or multiple layer positions.

Consanguinity, twinning and secondary sex ratio in the population of Karnataka, South India

Consanguineous marriages are strongly favoured in the state of Karnataka. Of 65492 marriages studied 33·07% were consanguineous, equivalent to a coefficient of inbreeding (F) of 0·0298. The twinning rate was low, 6·9 per thousand, whereas the secondary sex ratio, 0·5221, was higher than in comparable major human populations. Consanguinity exerted no significant effect on either parameter. The results also indicate that consanguinity is not associated with excess antenatal losses and suggest the possibility of enhanced selection against mutations at X chromosome loci.

Multiplexing in multiple imaging through the theta modulation technique

We apply the theta modulation technique to simultaneously multiple image more than one object independently with a Fourier plane sampling type of multiple imaging system. Experimental results of multiple imaging two objects is presented.

Optimal reservoir operation for irrigation of multiple crops using genetic algorithms

This paper presents a genetic algorithm (GA) model for obtaining an optimal operating policy and optimal crop water allocations from an irrigation reservoir. The objective is to maximize the sum of the relative yields from all crops in the irrigated area. The model takes into account reservoir inflow, rainfall on the irrigated area, intraseasonal competition for water among multiple crops, the soil moisture dynamics in each cropped area, the heterogeneous nature of soils. and crop response to the level of irrigation applied. The model is applied to the Malaprabha single-purpose irrigation reservoir in Karnataka State, India. The optimal operating policy obtained using the GA is similar to that obtained by linear programming. This model can be used for optimal utilization of the available water resources of any reservoir system to obtain maximum benefits.

Defining the pathway to insulin-like growth factor system targeting in cancer

The insulin-like growth factors (IGEs; IGF-1 and IGF-2) play central roles in cell growth, differentiation, survival, transformation and metastasis. The biologic effects of the IGFs are mediated by the IGF-1 receptor (IGF-1R), a receptor tyrosine kinase with homology to the insulin receptor (IR). Dysregulation of the ICE system is well recognized as a key contributor to the progression of multiple cancers, with IGF-1R activation increasing the tumorigenic potential of breast, prostate, lung, colon and head and neck squamous cell carcinoma (HNSCC). Despite this relationship, targeting the IGF-1R has only recently undergone development as a molecular cancer therapeutic. As it has taken hold, we are witnessing a robust increase and interest in targeting the inhibition of IGF-1R signaling. This is accentuated by the list of over 30 drugs, including monoclonal antibodies (mAbs) and tyrosine kinase inhibitors (TKIs) that are under evaluation as single agents or in combination therapies 1]. The ICE-binding proteins (IGFBPs) represent the third component of the ICE system consisting of a class of six soluble secretory proteins. They represent a unique class of naturally occurring ICE-antagonists that bind to and sequester IGF-1 and IGF-2, inhibiting their access to the IGF-1R. Due to their dual targeting of the IGFs without affecting insulin action, the IGFBPs are an untapped ``third'' class of IGF-1R inhibitors. in this commentary, we highlight some of the significant aspects of and prospects for targeting the IGF-1R and describe what the future may hold. (C) 2010 Elsevier Inc. All rights reserved.

Comparative Analyses of Age- and Sex-Specific Patterns of Vocal Behaviour in Four Species of Old World Monkeys

Sound recordings and behavioural data were collected from four primate species of two genera (Macaca, Presbytis). Comparative analyses of structural and behavioural aspects of vocal communication revealed a high degree of intrageneric similarity but striking intergeneric differences. In the two macaque species (Macaca silenus, Macaca radiata), males and females shared the major part of the repertoire. In contrast, in the two langurs (Presbytis johnii, Presbytis entellus), many calls were exclusive to adult males. Striking differences between both species groups occurred with respect to age-specific patterns of vocal behaviour. The diversity of vocal behaviour was assessed from the number of different calls used and the proportion of each call in relation to total vocal output for a given age/sex class. In Macaca, diversity decreases with the age of the vocalizer, whereas in Presbytis the age of the vocalizer and the diversity of vocal behaviour are positively correlated. A comparison of the data of the two genera does not suggest any causal relationship between group composition (e.g. multi-male vs. one-male group) and communication system. Within each genus, interspecific differences in vocal behaviour can be explained by differences in social behaviour (e.g. group cohesion, intergroup relation, mating behaviour) and functional disparities. Possible factors responsible for the pronounced intergeneric differences in vocal behaviour between Macaca and Presbytis are discussed.

Points-to Analysis as a System of Linear Equations

We propose a novel formulation of the points-to analysis as a system of linear equations. With this, the efficiency of the points-to analysis can be significantly improved by leveraging the advances in solution procedures for solving the systems of linear equations. However, such a formulation is non-trivial and becomes challenging due to various facts, namely, multiple pointer indirections, address-of operators and multiple assignments to the same variable. Further, the problem is exacerbated by the need to keep the transformed equations linear. Despite this, we successfully model all the pointer operations. We propose a novel inclusion-based context-sensitive points-to analysis algorithm based on prime factorization, which can model all the pointer operations. Experimental evaluation on SPEC 2000 benchmarks and two large open source programs reveals that our approach is competitive to the state-of-the-art algorithms. With an average memory requirement of mere 21MB, our context-sensitive points-to analysis algorithm analyzes each benchmark in 55 seconds on an average.