An Efficient Load Distribution Strategy for a Distributed Linear Network of Processors with Communication Delays

In this paper, we present an improved load distribution strategy, for arbitrarily divisible processing loads, to minimize the processing time in a distributed linear network of communicating processors by an efficient utilization of their front-ends. Closed-form solutions are derived, with the processing load originating at the boundary and at the interior of the network, under some important conditions on the arrangement of processors and links in the network. Asymptotic analysis is carried out to explore the ultimate performance limits of such networks. Two important theorems are stated regarding the optimal load sequence and the optimal load origination point. Comparative study of this new strategy with an earlier strategy is also presented.

Unsteady-Flow Of A Viscous-Fluid Between 2 Parallel Disks With A Time-Varying Gap Width And A Magnetic-Field

The unsteady incompressible viscous fluid flow between two parallel infinite disks which are located at a distance h(t*) at time t* has been studied. The upper disk moves towards the lower disk with velocity h'(t*). The lower disk is porous and rotates with angular velocity Omega(t*). A magnetic field B(t*) is applied perpendicular to the two disks. It has been found that the governing Navier-Stokes equations reduce to a set of ordinary differential equations if h(t*), a(t*) and B(t*) vary with time t* in a particular manner, i.e. h(t*) = H(1 - alpha t*)(1/2), Omega(t*) = Omega(0)(1 - alpha t*)(-1), B(t*) = B-0(1 - alpha t*)(-1/2). These ordinary differential equations have been solved numerically using a shooting method. For small Reynolds numbers, analytical solutions have been obtained using a regular perturbation technique. The effects of squeeze Reynolds numbers, Hartmann number and rotation of the disk on the flow pattern, normal force or load and torque have been studied in detail

Unsteady flow over a stretching surface with a magnetic field in a rotating fluid

The effect of the magnetic field on the unsteady flow over a stretching surface in a rotating fluid has been studied. The unsteadiness in the flow field is due to the time-dependent variation of the velocity of the stretching surface and the angular velocity of the rotating fluid. The Navier-Stokes equations and the energy equation governing the flow and the heat transfer admit a self-similar solution if the velocity of the stretching surface and the angular velocity of the rotating fluid vary inversely as a linear function of time. The resulting system of ordinary differential equations is solved numerically using a shooting method. The rotation parameter causes flow reversal in the component of the velocity parallel to the strerching surface and the magnetic field tends to prevent or delay the flow reversal. The surface shear stresses dong the stretching surface and in the rotating direction increase with the rotation parameter, but the surface heat transfer decreases. On the other hand, the magnetic field increases the surface shear stress along the stretching surface, but reduces the surface shear stress in the rotating direction and the surface heat transfer. The effect of the unsteady parameter is more pronounced on the velocity profiles in the rotating direction and temperature profiles.

Fault-tolerant characteristics and topological properties of a hierarchical network of hypercubes

We analyse the fault-tolerant parameters and topological properties of a hierarchical network of hypercubes. We take a close look at the Extended Hypercube (EH) and the Hyperweave (HW) architectures and also compare them with other popular architectures. These two architectures have low diameter and constant degree of connectivity making it possible to expand these networks without affecting the existing configuration. A scheme for incrementally expanding this network is also presented. We also look at the performance of the ASCEND/DESCEND class of algorithms on these architectures.

Supramolecular control of the magnetic anisotropy in two-dimensional high-spin Fe arrays at a metal interface

Magnetic atoms at surfaces are a rich model system for solid-state magnetic bits exhibiting either classical(1,2) or quantum(3,4) behaviour. Individual atoms, however, are difficult to arrange in regular patterns(1-5). Moreover, their magnetic properties are dominated by interaction with the substrate, which, as in the case of Kondo systems, often leads to a decrease or quench of their local magnetic moment(6,7). Here, we show that the supramolecular assembly of Fe and 1,4-benzenedicarboxylic acid molecules on a Cu surface results in ordered arrays of high-spin mononuclear Fe centres on a 1.5nm square grid. Lateral coordination with the molecular ligands yields unsaturated yet stable coordination bonds, which enable chemical modification of the electronic and magnetic properties of the Fe atoms independently from the substrate. The easy magnetization direction of the Fe centres can be switched by oxygen adsorption, thus opening a way to control the magnetic anisotropy in supramolecular layers akin to that used in metallic thin films.

A comparative social network analysis of wasp colonies and classrooms: Linking network structure to functioning

A major question in current network science is how to understand the relationship between structure and functioning of real networks. Here we present a comparative network analysis of 48 wasp and 36 human social networks. We have compared the centralisation and small world character of these interaction networks and have studied how these properties change over time. We compared the interaction networks of (1) two congeneric wasp species (Ropalidia marginata and Ropalidia cyathiformis), (2) the queen-right (with the queen) and queen-less (without the queen) networks of wasps, (3) the four network types obtained by combining (1) and (2) above, and (4) wasp networks with the social networks of children in 36 classrooms. We have found perfect (100%) centralisation in a queen-less wasp colony and nearly perfect centralisation in several other queen-less wasp colonies. Note that the perfectly centralised interaction network is quite unique in the literature of real-world networks. Differences between the interaction networks of the two wasp species are smaller than differences between the networks describing their different colony conditions. Also, the differences between different colony conditions are larger than the differences between wasp and children networks. For example, the structure of queen-right R. marginata colonies is more similar to children social networks than to that of their queen-less colonies. We conclude that network architecture depends more on the functioning of the particular community than on taxonomic differences (either between two wasp species or between wasps and humans).

Flow and heat transfer in a stagnation-point flow over a stretching sheet with a magnetic field

The flow and heat transfer problem in the boundary layer induced by a continuous moving surface is important in many manufacturing processes in industry such as the boundary layer along material handling conveyers, the aerodynamic extrusion of plastic sheet, the cooling of an infinite metalic plate in a cooling bath (which may also be electrolyte). Glass blowing, continuous casting and spinning of fibres also involve the flow due to a stretching surface. Sakiadis [1] was the first to study the flow induced by a semi-infinite moving wall in an ambient fluid. On the other hand, Crane [2] first studied the flow over a linearly stretching sheet in an ambient fluid. Subsequently, Crane [3] also investigated the corresponding heat transfer problem. Since then several authors [4-8] have studied various aspects of this problem such as the effects of mass transfer, variable wall temperature, constant heat flux, magnetic field etc. Recently, Andersson [9] has obtained an exact solution of the Navier-Stokes equations for the MHD flow over a linearly stretching sheet in an ambient fluid. Also Chiam [10] has studied the heat transfer with variable thermal conductivity on a stretching sheet when the velocities of the sheet and the free stream are equal.

Magnetization, magnetotransport and electron magnetic resonance studies of nanoparticles and nanowires of Pr0.5Sr0.5MnO3

In this paper, we present the preparation and characterization of nanoparticles and nanowires of Pr0.5Sr0.5MnO3 (PSMO). The main results of this investigation are as follows: (a) a comparison with the properties of the bulk material shows that the ferromagnetic (FM) transition at 270 K remains unaffected but the anti-ferromagnetic (AFM) transition at TN = 150 K disappears in the nanoparticles, (b) the size induced ground state magnetic phase (below 150 K) is predominantly FM, coexisting with a residual AFM phase, and (c) the temperature dependence of magnetic anisotropy shows complex behaviour, being higher in the nanoparticles at high temperatures and lower at moderately lower temperatures in comparison with the bulk. The results obtained from the extensive magnetization, magnetotransport and electron magnetic resonance studies made on various samples are presented and discussed in detail.

Electrical and mechanical properties of diluted magnetic semiconductor Zn1-xMnxS nanocrystalline films

Nanostructured Zn1-xMnxS films (0 less-than-or-equals, slant x less-than-or-equals, slant 0.25) were deposited on glass substrates by simple resistive thermal evaporation technique. All the films were deposited at 300 K in a vacuum of 2*10-6 m bar. All the films temperature dependence of resistivity revealed semiconducting behaviour of the samples. Hot probe test revealed that all the samples exhibited n-type conductivity. The nanohardness of the films ranges from 4.7 to 9.9 GPa, Young's modulus value ranging 69.7-94.2 GPa.

A linear programming approach for estimating the structure of a sparse linear genetic network from transcript profiling data

Background: A genetic network can be represented as a directed graph in which a node corresponds to a gene and a directed edge specifies the direction of influence of one gene on another. The reconstruction of such networks from transcript profiling data remains an important yet challenging endeavor. A transcript profile specifies the abundances of many genes in a biological sample of interest. Prevailing strategies for learning the structure of a genetic network from high-dimensional transcript profiling data assume sparsity and linearity. Many methods consider relatively small directed graphs, inferring graphs with up to a few hundred nodes. This work examines large undirected graphs representations of genetic networks, graphs with many thousands of nodes where an undirected edge between two nodes does not indicate the direction of influence, and the problem of estimating the structure of such a sparse linear genetic network (SLGN) from transcript profiling data. Results: The structure learning task is cast as a sparse linear regression problem which is then posed as a LASSO (l1-constrained fitting) problem and solved finally by formulating a Linear Program (LP). A bound on the Generalization Error of this approach is given in terms of the Leave-One-Out Error. The accuracy and utility of LP-SLGNs is assessed quantitatively and qualitatively using simulated and real data. The Dialogue for Reverse Engineering Assessments and Methods (DREAM) initiative provides gold standard data sets and evaluation metrics that enable and facilitate the comparison of algorithms for deducing the structure of networks. The structures of LP-SLGNs estimated from the INSILICO1, INSILICO2 and INSILICO3 simulated DREAM2 data sets are comparable to those proposed by the first and/or second ranked teams in the DREAM2 competition. The structures of LP-SLGNs estimated from two published Saccharomyces cerevisae cell cycle transcript profiling data sets capture known regulatory associations. In each S. cerevisiae LP-SLGN, the number of nodes with a particular degree follows an approximate power law suggesting that its degree distributions is similar to that observed in real-world networks. Inspection of these LP-SLGNs suggests biological hypotheses amenable to experimental verification. Conclusion: A statistically robust and computationally efficient LP-based method for estimating the topology of a large sparse undirected graph from high-dimensional data yields representations of genetic networks that are biologically plausible and useful abstractions of the structures of real genetic networks. Analysis of the statistical and topological properties of learned LP-SLGNs may have practical value; for example, genes with high random walk betweenness, a measure of the centrality of a node in a graph, are good candidates for intervention studies and hence integrated computational – experimental investigations designed to infer more realistic and sophisticated probabilistic directed graphical model representations of genetic networks. The LP-based solutions of the sparse linear regression problem described here may provide a method for learning the structure of transcription factor networks from transcript profiling and transcription factor binding motif data.

Synthesis and magnetic studies of flower-like nickel nanocones

Flower-like nickel nanocone structures are synthesized by a simple chemical reduction method using hydrazine hydrate as the reducing agent. The structure, morphology and magnetic properties of as synthesized products are studied by X-ray diffraction (XRD), field emission scanning electron microscopy (FESEM), transmission electron microscopy (TEM) and SQUID magnetometer. The morphology evolution is studied by varying the reaction temperature and concentration of nickel chloride keeping other conditions unchanged.

Latency, Power and Performance Trade-offs in Network-on-Chips by Link Microarchitecture Exploration

This paper presents a power, latency and throughput trade-off study on NoCs by varying microarchitectural (e.g. pipelining) and circuit level (e.g. frequency and voltage) parameters. We change pipelining depth, operating frequency and supply voltage for 3 example NoCs - 16 node 2D Torus, Tree network and Reduced 2D Torus. We use an in-house NoC exploration framework capable of topology generation and comparison using parameterized models of Routers and links developed in SystemC. The framework utilizes interconnect power and delay models from a low-level modelling tool called Intacte[1]1. We find that increased pipelining can actually reduce latency. We also find that there exists an optimal degree of pipelining which is the most energy efficient in terms of minimizing energy-delay product.

Synthesis and magnetic studies of flower-like nickel nanocones

Flower-like nickel nanocone structures are synthesized by a simple chemical reduction method using hydrazine hydrate as the reducing agent. The structure, morphology and magnetic properties of as synthesized products are studied by X-ray diffraction (XRD), field emission scanning electron microscopy (FESEM), transmission electron microscopy (TEM) and SQUID magnetometer. The morphology evolution is studied by varying the reaction temperature and concentration of nickel chloride keeping other conditions unchanged.

On-Chip Clock Network Skew Measurement using Sub-Sampling

We present a technique for an all-digital on-chip delay measurement system to measure the skews in a clock distribution network. It uses the principle of sub-sampling. Measurements from a prototype fabricated in a 65 nm industrial process, indicate the ability to measure delays with a resolution of 0.5ps and a DNL of 1.2 ps.

High-Pressure Magnetic-Susceptibility Studies of Spin-State Transaction

High-pressure magnetic susceptibility measurements have been carried out on Fe(dipy)2(NCS)2 and Fe(phen)2(NCS)2 in the pressure range 1–10 kbar and tempeature range 80–300 K in order to investigate the factors responsible for the spin-state transitions. The transitions change from first order to second or higher order upon application of pressure. The temperature variation of the susceptibility at different pressures has been analysed quantitatively within the framework of available models. It is shown that the relative magnitudes of the ΔG0 of high-spin and low-spin conversion and the ferromagnetic interaction between high-spin complexes determines the nature of the transition.