EEHC: Energy efficient heterogeneous clustered scheme for wireless sensor networks

In recent years, there has been a growing interest in wireless sensor networks. One of the major issues in wireless sensor network is developing an energy-efficient clustering protocol. Hierarchical clustering algorithms are very important in increasing the network’s life time. Each clustering algorithm is composed of two phases, the setup phase and steady state phase. The hot point in these algorithms is the cluster head selection. In this paper, we study the impact of heterogeneity of nodes in terms of their energy in wireless sensor networks that are hierarchically clustered. We assume that a percentage of the population of sensor nodes is equipped with the additional energy resources. We also assume that the sensor nodes are randomly distributed and are not mobile, the coordinates of the sink and the dimensions of the sensor field are known. Homogeneous clustering protocols assume that all the sensor nodes are equipped with the same amount of energy and as a result, they cannot take the advantage of the presence of node heterogeneity. Adapting this approach, we introduce an energy efficient heterogeneous clustered scheme for wireless sensor networks based on weighted election probabilities of each node to become a cluster head according to the residual energy in each node. Finally, the simulation results demonstrate that our proposed heterogeneous clustering approach is more effective in prolonging the network lifetime compared with LEACH.     

Bridging the gap: effect of text query reformulation in multimodal retrieval

Multimedia Tools and Applications - Multimodal Retrieval provides new paradigms and methods aimed at effectively searching through the enormous volume of data. Multimodal retrieval is a well...     

On negative results when using sentiment analysis tools for software engineering research

Recent years have seen an increasing attention to social aspects of software engineering, including studies of emotions and sentiments experienced and expressed by the software developers. Most of these studies reuse existing sentiment analysis tools such as SentiStrength and NLTK. However, these tools have been trained on product reviews and movie reviews and, therefore, their results might not be applicable in the software engineering domain. In this paper we study whether the sentiment analysis tools agree with the sentiment recognized by human evaluators (as reported in an earlier study) as well as with each other. Furthermore, we evaluate the impact of the choice of a sentiment analysis tool on software engineering studies by conducting a simple study of differences in issue resolution times for positive, negative and neutral texts. We repeat the study for seven datasets (issue trackers and Stack Overflow questions) and different sentiment analysis tools and observe that the disagreement between the tools can lead to diverging conclusions. Finally, we perform two replications of previously published studies and observe that the results of those studies cannot be confirmed when a different sentiment analysis tool is used.     

Linearized motion estimation for articulated planes

In this paper, we describe the explicit application of articulation constraints for estimating the motion of a system of articulated planes. We relate articulations to the relative homography between planes and show that these articulations translate into linearized equality constraints on a linear least-squares system, which can be solved efficiently using a Karush-Kuhn-Tucker system. The articulation constraints can be applied for both gradient-based and feature-based motion estimation algorithms and to illustrate this, we describe a gradient-based motion estimation algorithm for an affine camera and a feature-based motion estimation algorithm for a projective camera that explicitly enforces articulation constraints. We show that explicit application of articulation constraints leads to numerically stable estimates of motion. The simultaneous computation of motion estimates for all of the articulated planes in a scene allows us to handle scene areas where there is limited texture information and areas that leave the field of view. Our results demonstrate the wide applicability of the algorithm in a variety of challenging real-world cases such as human body tracking, motion estimation of rigid, piecewise planar scenes, and motion estimation of triangulated meshes.     

The minimum positional error incurred by any connectivity-based positioning algorithm for mobile wireless systems

A very important problem in many wireless ad-hoc networks, including wireless sensor networks, is positioning or the determination of geographical locations of the wireless nodes. Positioning is used both in infrastructural aspects of sensor networks, like geographic routing and topology maintenance, and in applications like wildlife tracking. Connectivity-based positioning algorithms in mobile wireless systems are studied in this work. These algorithms compute node positions based only on the connectivity, i.e. the neighborhood information of each node. Many algorithms have been proposed for positioning in stationary node systems and bounds on positional error of algorithms have been derived. The design and analysis of positioning algorithms for mobile node systems is a more challenging problem. Node mobility increases the amount of positional information available to a positioning algorithm. The work in this paper establishes a bound on the positional error for connectivity-based algorithms in mobile systems. The formulation from the analysis is used to investigate the benefit of this additional positional information on reducing positional error. There is a limit to the usefulness of positional information from previous node positions due to movement. This captures an important performance tradeoff: historical positional information can yield reduced positional error but requires more connectivity information from the network which requires greater computational resources.     

Automated Cellular Modeling and Prediction on a Large Scale

We describe CHAMP (CHurn Analysis, Modeling, andPrediction), an automated system for modeling cellularsubscriber churn that is predicting which customerswill discontinue cellular phone service. We describevarious issues related to developing and deployingthis system including automating data access from aremote data warehouse, preprocessing, featureselection, model validation, and optimization toreflect business tradeoffs. Using data from GTE'sdata warehouse for cellular phone customers, CHAMP iscapable of developing churn models customized byregion for over one hundred GTE cellular phone marketstotaling over 5 million customers. Every month churnfactors are identified for each geographic region andmodels are updated to generate churn scores predictingwho is likely to churn in the short term. Learningmethods such as decision trees and genetic algorithmsare used for feature selection and a cascade neuralnetwork is used for predicting churn scores. Inaddition to producing churn scores, CHAMP alsoproduces qualitative results in the form of rules andcomparison of market trends that are disseminatedthrough a web based interface.     

Soft computing-based approaches to predict energy consumption and stability margin of six-legged robots moving on gradient terrains

Soft computing-based approaches have been developed to predict specific energy consumption and stability margin of a six-legged robot ascending and descending some gradient terrains. Three different neuro-fuzzy and one neural network-based approaches have been developed. The performances of these approaches are compared among themselves, through computer simulations. Genetic algorithm-tuned multiple adaptive neuro-fuzzy inference system is found to perform better than other three approaches for predicting both the outputs. This could be due to a more exhaustive search carried out by the genetic algorithm in comparison with back-propagation algorithm and the use of two separate adaptive neuro-fuzzy inference systems for two different outputs. A designer may use the developed soft computing-based approaches in order to predict specific energy consumption and stability margin of the robot for a set of input parameters, beforehand.     

A parallel hp‐FEM infrastructure for three‐dimensional structural acoustics

This paper describes a parallel three‐dimensional numerical infrastructure for the solution of a wide range of time‐harmonic problems in structural acoustics and vibration. High accuracy and rate of error‐convergence, in the mid‐frequency regime,is achieved by the use of hp‐finite and infinite element approximations. The infrastructure supports parallel computation in both single and multi‐frequency settings. Multi‐frequency solves utilize concurrent factoring of the frequency‐dependent linear algebraic systems and are naturally scalable. Scalability of large‐scale single‐frequency problems is realized by using FETI‐DP—an iterative domain‐decomposition scheme. Numerical examples are presented to cover applications in vibratory response of fluid‐filled elastic structures as well as radiation and scattering from elastic structures submerged in an infinite acoustic medium. We demonstrate both the numerical accuracy as well as parallel scalability of the infrastructure in terms of problem parameters that include wavenumber and number of frequencies, polynomial degree of finite/infinite element approximations as well as the number of processors. Scalability and accuracy is evaluated for both single and multiple frequency sweeps on four high‐performance parallel computing platforms: SGI Altix, SGI Origin, IBM p690 SP and Linux‐cluster. Results show good performance on shared as well as distributed‐memory architecture. Copyright © 2006 John Wiley & Sons, Ltd.     

Influence of Cl-, Br-, NO 3 - and SO 4 2- ions on the corrosion behaviour of 6061 Al alloy

The effects of anions like Cl^-, Br^-, NO ₃ ^- and SO ₄ ^2- on the anodic dissolution of the monolithic Al 6061 alloy have been investigated at neutral pH through immersion testing and electrochemical techniques like potentiodynamic polarization and a.c. impedance spectroscopy. Scanning electron microscopy was employed to characterize the corroded surface and to observe the extent of pitting in different media. From the evaluated corrosion parameters it was found that the dissolution of the matrix was extensively reduced in presence of aqueous solutions containing Br^-, NO ₃ ^- and SO ₄ ^2- ions while Cl^- ions aggravated corrosion by penetrating into the barrier oxide film on the surface of the material. Pronounced effect of pitting was observed in presence of Cl^- and the level of pitting in NO ₃ ^- and Br^- were mild. In presence of SO ₄ ^2- ions passivity was extended over a wide potential range and breakdown of passivity occurs when the material was polarized beyond pitting potential. The departure of capacitive behaviour towards resistive behaviour was clearly observed through impedance measurements when investigations were conducted in Cl^- media and in presence of the other electrolytes. Corrosion rates were, however, controlled during prolonged exposure in the electrolytic media, specially in case of chloride media, due to the predominance of film repair kinetics.