Influence limitation in multi-campaign social networks: A Shapley value based approach

We investigate the problem of influence limitation in the presence of competing campaigns in a social network. Given a negative campaign which starts propagating from a specified source and a positive/counter campaign that is initiated, after a certain time delay, to limit the the influence or spread of misinformation by the negative campaign, we are interested in finding the top k influential nodes at which the positive campaign may be triggered. This problem has numerous applications in situations such as limiting the propagation of rumor, arresting the spread of virus through inoculation, initiating a counter-campaign against malicious propaganda, etc. The influence function for the generic influence limitation problem is non-submodular. Restricted versions of the influence limitation problem, reported in the literature, assume submodularity of the influence function and do not capture the problem in a realistic setting. In this paper, we propose a novel computational approach for the influence limitation problem based on Shapley value, a solution concept in cooperative game theory. Our approach works equally effectively for both submodular and non-submodular influence functions. Experiments on standard real world social network datasets reveal that the proposed approach outperforms existing heuristics in the literature. As a non-trivial extension, we also address the problem of influence limitation in the presence of multiple competing campaigns.

Interface capturing simulations of acoustically driven bubble dynamics in and near tissue

Tissue injury during therapeutic ultrasound or lithotripsy is thought, in cases, to be due to the action of cavitation bubbles. Assessing this and mitigating it is challenging since bubble dynamics in the complex confinement of tissues or in small blood vessels are challenging to predict. Simulations tools require specialized algorithms to simultaneously represent strong acoustic waves and shocks, topologically complex liquid‐vapor phase boundaries, and the complex viscoelastic material dynamics of tissue. We discuss advances in a simulation tool for such situations. A single‐mesh Eulerian solver is used to solve the governing equations. Special sharpening terms maintain the liquid‐vapor interface in face of the finite numerical dissipation included in the scheme to accurately capture shocks. A recent enhancement to this formulation has significantly improved this interface capturing procedure, which is demonstrated for simulation of the Rayleigh collapse of a bubble. The solver also transports elastic stresses and can thus be used to assess the effects of elastic properties on bubble dynamics. A shock‐induced bubble collapse adjacent to a model elastic tissue is used to demonstrate this and draw some conclusions regarding the injury suppressing role that tissue elasticity might play.

Discrimination of alpha-Amino Acids Using Green Tea Flavonoid (-)-Epigallocatechin Gallate as a Chiral Solvating Agent

We report a special, hitherto-unexplored property of (-)-epigallocatechin gallate (EGCG) as a chiral solvating agent for enantiodiscrimination of alpha-amino acids in the polar solvent DMSO. This phenomenon has been investigated by H-1 NMR spectroscopy. The mechanism of the interaction property of EGCG with alpha-amino acids has been understood as arising out of hydrogen-bonded noncovalent interactions, where the -OH groups of two phenyl rings of EGCG play dominant roles. The conversion of the enantiomeric mixture into diastereomers yielded well-resolved peaks for D and L amino acids permitting the precise measurement of enantiomeric composition. Often one encounters complex situations when the spectra are severely overlapped or partially resolved hampering the testing of enantiopurity and the precise measurement of enantiomeric excess (ee). Though higher concentration of EGCG yielded better discrimination, the use of lower concentration being economical, we have exploited an appropriate 2D NMR experiment in overcoming such problems. Thus, in the present study we have successfully demonstrated the utility of the bioflavonoid (-)-EGCG, a natural product as a chiral solvating agent for the discrimination of large number of alpha-amino acids in a polar solvent DMSO. Another significant advantage of this new chiral sensing agent is that it is a natural product and does not require tedious multistep synthesis unlike many other chiral auxiliaries.

Tutorial: implementing a pedestrian tracker using inertial sensors

Shoe-mounted inertial sensors offer a convenient way to track pedestrians in situations where other localization systems fail. This tutorial outlines a simple yet effective approach for implementing a reasonably accurate tracker. This Web extra presents the Matlab implementation and a few sample recordings for implementing the pedestrian inertial tracking system using an error-state Kalman filter for zero-velocity updates (ZUPTs) and orientation estimation.

Fuzzy data envelopment analysis for performance evaluation of an irrigation system

Sixteen irrigation subsystems of the Mahi Bajaj Sagar Project, Rajasthan, India, are evaluated and selection of the most suitable/best is made using data envelopment analysis (DEA) in both deterministic and fuzzy environments. Seven performance-related indicators, namely, land development works (LDW), timely supply of inputs (TSI), conjunctive use of water resources (CUW), participation of farmers (PF), environmental conservation (EC), economic impact (EI) and crop productivity (CPR) are considered. Of the seven, LDW, TSI, CUW, PF and EC are considered inputs, whereas CPR and EI are considered outputs for DEA modelling purposes. Spearman rank correlation coefficient values are also computed for various scenarios. It is concluded that DEA in both deterministic and fuzzy environments is useful for the present problem. However, the outcome of fuzzy DEA may be explored for further analysis due to its simple, effective data and discrimination handling procedure. It is inferred that the present study can be explored for similar situations with suitable modifications.

Prioritisation of micro-catchments based on morphology

Two multicriterion decision-making methods, namely `compromise programming' and the `technique for order preference by similarity to an ideal solution' are employed to prioritise 22 micro-catchments (A1 to A22) of Kherthal catchment, Rajasthan, India and comparative analysis is performed using the compound parameter approach. Seven criteria - drainage density, bifurcation ratio, stream frequency, form factor, elongation ratio, circulatory ratio and texture ratio - are chosen for the evaluation. The entropy method is employed to estimate weights or relative importance of the criterion which ultimately affects the ranking pattern or prioritisation of micro-catchments. Spearman rank correlation coefficients are estimated to measure the extent to which the ranks obtained are correlated. Based on the average ranking approach supported by sensitivity analysis, micro-catchments A6, A10, A3 are preferred (owing to their low ranking) for further improvements with suitable conservation and management practices, and other micro-catchments can be processed accordingly at a later phase on a priority basis. It is concluded that the present approach can be explored for other similar situations with appropriate modifications.

Identification of fault location in power distribution system with distributed generation using support vector machines

This paper presents a multi-class support vector machine (SVMs) approach for locating and diagnosing faults in electric power distribution feeders with the penetration of Distributed Generations (DGs). The proposed approach is based on the three phase voltage and current measurements which are available at all the sources i.e. substation and at the connection points of DG. To illustrate the proposed methodology, a practical distribution feeder emanating from 132/11kV-grid substation in India with loads and suitable number of DGs at different locations is considered. To show the effectiveness of the proposed methodology, practical situations in distribution systems (DS) such as all types of faults with a wide range of varying fault locations, source short circuit (SSC) levels and fault impedances are considered for studies. The proposed fault location scheme is capable of accurately identify the fault type, location of faulted feeder section and the fault impedance. The results demonstrate the feasibility of applying the proposed method in practical in smart grid distribution automation (DA) for fault diagnosis.

Integrated sustainable irrigation planning with multiobjective Fuzzy optimization approach

Multiobjective fuzzy methodology is applied to a case study of Khadakwasla complex irrigation project located near Pune city of Maharashtra State, India. Three objectives, namely, maximization of net benefits, crop production and labour employment are considered. Effect of reuse of wastewater on the planning scenario is also studied. Three membership functions, namely, nonlinear, hyperbolic and exponential are analyzed for multiobjective fuzzy optimization. In the present study, objective functions are considered as fuzzy in nature whereas inflows are considered as dependable. It is concluded that exponential and hyperbolic membership functions provided similar cropping pattern for most of the situations whereas nonlinear membership functions provided different cropping pattern. However, in all the three cases, irrigation intensities are more than the existing irrigation intensity.

Intensity profile of light scattered from a rough surface

We present in this paper, approximate analytical expressions for the intensity of light scattered by a rough surface, whose elevation. xi(x,y) in the z-direction is a zero mean stationary Gaussian random variable. With (x,y) and (x',y') being two points on the surface, we have h. = 0 with a correlation, = sigma(2)g(r), where r = (x - x')(2) + ( y - y')(2)](1/2) is the distance between these two points. We consider g(r) = exp-r/l)(beta)] with 1 <= beta <= 2, showing that g(0) = 1 and g(r) -> 0 for r >> l. The intensity expression is sought to be expressed as f(v(xy)) = {1 + (c/2y)v(x)(2) + v(y)(2)]}(-y), where v(x) and v(y) are the wave vectors of scattering, as defined by the Beckmann notation. In the paper, we present expressions for c and y, in terms of sigma, l, and beta. The closed form expressions are verified to be true, for the cases beta = 1 and beta = 2, for which exact expressions are known. For other cases, i.e., beta not equal 1, 2 we present approximate expressions for the scattered intensity, in the range, v(xy) = (v(x)(2) + v(y)(2))(1/2) <= 6.0 and show that the relation for f(v(xy)), given above, expresses the scattered intensity quite accurately, thus providing a simple computational methods in situations of practical importance.

Does lean imply green?: a study of the power performance implications of Java runtime bloat

The presence of software bloat in large flexible software systems can hurt energy efficiency. However, identifying and mitigating bloat is fairly effort intensive. To enable such efforts to be directed where there is a substantial potential for energy savings, we investigate the impact of bloat on power consumption under different situations. We conduct the first systematic experimental study of the joint power-performance implications of bloat across a range of hardware and software configurations on modern server platforms. The study employs controlled experiments to expose different effects of a common type of Java runtime bloat, excess temporary objects, in the context of the SPECPower_ssj2008 workload. We introduce the notion of equi-performance power reduction to characterize the impact, in addition to peak power comparisons. The results show a wide variation in energy savings from bloat reduction across these configurations. Energy efficiency benefits at peak performance tend to be most pronounced when bloat affects a performance bottleneck and non-bloated resources have low energy-proportionality. Equi-performance power savings are highest when bloated resources have a high degree of energy proportionality. We develop an analytical model that establishes a general relation between resource pressure caused by bloat and its energy efficiency impact under different conditions of resource bottlenecks and energy proportionality. Applying the model to different "what-if" scenarios, we predict the impact of bloat reduction and corroborate these predictions with empirical observations. Our work shows that the prevalent software-only view of bloat is inadequate for assessing its power-performance impact and instead provides a full systems approach for reasoning about its implications.

Resource usage monitoring for KVM based virtual machines

Realization of cloud computing has been possible due to availability of virtualization technologies on commodity platforms. Measuring resource usage on the virtualized servers is difficult because of the fact that the performance counters used for resource accounting are not virtualized. Hence, many of the prevalent virtualization technologies like Xen, VMware, KVM etc., use host specific CPU usage monitoring, which is coarse grained. In this paper, we present a performance monitoring tool for KVM based virtualized machines, which measures the CPU overhead incurred by the hypervisor on behalf of the virtual machine along-with the CPU usage of virtual machine itself. This fine-grained resource usage information, provided by the above tool, can be used for diverse situations like resource provisioning to support performance associated QoS requirements, identification of bottlenecks during VM placements, resource profiling of applications in cloud environments, etc. We demonstrate a use case of this tool by measuring the performance of web-servers hosted on a KVM based virtualized server.

FUSION OF ALGORITHMS FOR COMPRESSED SENSING

Numerous algorithms have been proposed recently for sparse signal recovery in Compressed Sensing (CS). In practice, the number of measurements can be very limited due to the nature of the problem and/or the underlying statistical distribution of the non-zero elements of the sparse signal may not be known a priori. It has been observed that the performance of any sparse signal recovery algorithm depends on these factors, which makes the selection of a suitable sparse recovery algorithm difficult. To take advantage in such situations, we propose to use a fusion framework using which we employ multiple sparse signal recovery algorithms and fuse their estimates to get a better estimate. Theoretical results justifying the performance improvement are shown. The efficacy of the proposed scheme is demonstrated by Monte Carlo simulations using synthetic sparse signals and ECG signals selected from MIT-BIH database.

Active yaw control of a vehicle using a Fuzzy logic algorithm

Yaw rate of a vehicle is highly influenced by the lateral forces generated at the tire contact patch to attain the desired lateral acceleration, and/or by external disturbances resulting from factors such as crosswinds, flat tire or, split-μ braking. The presence of the latter and the insufficiency of the former may lead to undesired yaw motion of a vehicle. This paper proposes a steer-by-wire system based on fuzzy logic as yaw-stability controller for a four-wheeled road vehicle with active front steering. The dynamics governing the yaw behavior of the vehicle has been modeled in MATLAB/Simulink. The fuzzy controller receives the yaw rate error of the vehicle and the steering signal given by the driver as inputs and generates an additional steering angle as output which provides the corrective yaw moment. The results of simulations with various drive input signals show that the yaw stability controller using fuzzy logic proposed in the current study has a good performance in situations involving unexpected yaw motion. The yaw rate errors of a vehicle having the proposed controller are notably smaller than an uncontrolled vehicle's, and the vehicle having the yaw stability controller recovers lateral distance and desired yaw rate more quickly than the uncontrolled vehicle.