Optimal Placement Algorithms for Virtual Machines

Cloud computing provides a computing platform for the users to meet their demands in an efficient, cost-effective way. Virtualization technologies are used in the clouds to aid the efficient usage of hardware. Virtual machines (VMs) are utilized to satisfy the user needs and are placed on physical machines (PMs) of the cloud for effective usage of hardware resources and electricity in the cloud. Optimizing the number of PMs used helps in cutting down the power consumption by a substantial amount. In this paper, we present an optimal technique to map virtual machines to physical machines (nodes) such that the number of required nodes is minimized. We provide two approaches based on linear programming and quadratic programming techniques that significantly improve over the existing theoretical bounds and efficiently solve the problem of virtual machine (VM) placement in data centers

Modified SPLICE and its Extension to Non-Stereo Data for Noise Robust Speech Recognition

In this paper, a modification to the training process of the popular SPLICE algorithm has been proposed for noise robust speech recognition. The modification is based on feature correlations, and enables this stereo-based algorithm to improve the performance in all noise conditions, especially in unseen cases. Further, the modified framework is extended to work for non-stereo datasets where clean and noisy training utterances, but not stereo counterparts, are required. Finally, an MLLR-based computationally efficient run-time noise adaptation method in SPLICE framework has been proposed. The modified SPLICE shows 8.6% absolute improvement over SPLICE in Test C of Aurora-2 database, and 2.93% overall. Non-stereo method shows 10.37% and 6.93% absolute improvements over Aurora-2 and Aurora-4 baseline models respectively. Run-time adaptation shows 9.89% absolute improvement in modified framework as compared to SPLICE for Test C, and 4.96% overall w.r.t. standard MLLR adaptation on HMMs.Comment: Submitted to Automatic Speech Recognition and Understanding (ASRU) 2013 Worksho

Relaxation of Collective Excitations in LJ-13 Cluster

We have performed classical molecular dynamics simulation of $Ar_{13}$ cluster to study the behavior of collective excitations. In the solid ``phase'' of the cluster, the collective oscillation of the monopole mode can be well fitted to a damped harmonic oscillator. The parameters of the equivalent damped harmonic oscillator-- the damping coefficient, spring constant, time period of oscillation and the mass of the oscillator -- all show a sharp change in behavior at a kinetic temperature of about $7.0^oK$. This marks yet another characteristic temperature of the system, a temperature $T_s$ below which collective excitations are very stable, and at higher temperatures the single particle excitations cause the damping of the collective oscillations. We argue that so long as the cluster remains confined within the global potential energy minimum the collective excitations do not decay; and once the cluster comes out of this well, the local potential energy minima pockets act as single particle excitation channels in destroying the collective motion. The effect is manifest in almost all the physical observables of the cluster.Comment: Revised and enlarged. 6 pages RevTeX style. 7 eps figures available on request. To appear in J Chem Phy

The Economic Reality of Underutilised Crops for Climate Resilience, Food Security and Nutrition: Assessing Finger Millet Productivity in India

In spite of the considerable potential contribution of neglected and underutilised crops to climate resilience, food security and nutrition; widespread adoption of these crops remains a challenge. Uptake is inhibited by poor economic performance due to low yields, compounded further by various social factors. Using farm survey data and aggregated time-series data from four states in southern India, this study examines factors influencing productivity in finger millet cultivation. A farm-level yield gap analysis is complemented by an analysis of total factor productivity (TFP) growth between 1999 and 2014 to better understand the role of research and innovation. Results suggest that there is considerable potential for improved growing practices to achieve better yields, but also education levels and technical support emerge as crucial factors for boosting finger millet productivity. The TFP analysis indicates a moderate level of growth, with a high variability and conflicting trends between states, suggesting a need to invest more in research and development, extension and infrastructure. Sustained productivity gains will require research efforts that respond to the needs expressed by farmers and that finger millet forms part of an overall strategy for sustainable intensification

Functional characterization of a glutamate/aspartate transporter from the mosquito Aedes aegypti

Glutamate elicits a variety of effects in insects, including inhibitory and excitatory signals at both neuromuscular junctions and brain. Insect glutamatergic neurotransmission has been studied in great depth especially from the standpoint of the receptor-mediated effects, but the molecular mechanisms involved in the termination of the numerous glutamatergic signals have only recently begun to receive attention. In vertebrates, glutamatergic signals are terminated by Na^+/K^+-dependent high-affinity excitatory amino acid transporters (EAAT), which have been cloned and characterized extensively. Cloning and characterization of a few insect homologues have followed, but functional information for these homologues is still limited. Here we report a study conducted on a cloned mosquito EAAT homologue isolated from the vector of the dengue virus, Aedes aegypti. The deduced amino acid sequence of the protein, AeaEAAT, exhibits 40–50% identity with mammalian EAATs, and 45–50% identity to other insect EAATs characterized thus far. It transports l-glutamate as well as l- and d-aspartate with high affinity in the micromolar range, and demonstrates a substrate-elicited anion conductance when heterologously expressed in Xenopus laevis oocytes, as found with mammalian homologues. Analysis of the spatial distribution of the protein demonstrates high expression levels in the adult thorax, which is mostly observed in the thoracic ganglia. Together, the work presented here provides a thorough examination of the role played by glutamate transport in Ae. aegypti

Anisotropy of the Stone-Wales Defect and Warping of Graphene Nano-ribbons: A First-principles Analysis

Stone-Wales (SW) defects, analogous to dislocations in crystals, play an important role in mechanical behavior of $sp^2$-bonded carbon based materials. Here, we show using first-principles calculations that a marked anisotropy in the interaction among the SW defects has interesting consequences when such defects are present near the edges of a graphene nano-ribbon: depending on their orientation with respect to edge, they result in compressive or tensile stress, and the former is responsible to depression or warping of the graphene nano-ribbon. Such warping results in delocalization of electrons in the defect states.Comment: 8 page