Social virtual world continuance among teens: uncovering the moderating role of perceived aggregate network exposure

Engagement in virtual worlds has become pervasive, particularly among the young. At the same time, the number of virtual environments has increased rapidly. Due to intensifying competition, promoting sustained usage, i.e. continuance, has become a top priority for virtual world operators. Prior research has shown that network externalities play a key role in the adoption of communication technologies. However, a small amount of research has examined the role of network externalities in continued IT usage in general or with respect to the virtual world participation in particular. To fill in this gap, we examine how perceived network externalities affect the continuance of social virtual worlds. To this end, we introduce the concept of perceived aggregate network exposure (PANE). We extend the original information systems (IS) continuance model with perceived enjoyment and position PANE as a moderator. We test the model with data collected from 2134 Finnish Habbo Hotel users and employ structural equation modelling in the analysis. The results demonstrate that PANE moderates the influence of motivational factors on continued use intention and satisfaction.     

Voiced/non-voiced speech classification using adaptive thresholding with bivariate EMD

This paper introduces a robust voiced/non-voiced (VnV) speech classification method using bivariate empirical mode decomposition (bEMD). Fractional Gaussian noise (fGn) is employed as the reference signal to derive a data adaptive threshold for VnV discrimination. The analyzing speech signal and fGn are combined to generate a complex signal which is decomposed into a finite number of complex-valued intrinsic mode functions (IMFs) by using bEMD. The real and imaginary parts of the IMFs represent the IMFs of observed speech and fGn, respectively. The log-energies of both types of IMFs are calculated. There exist similarities between the IMF log-energy representation of fGn and unvoiced speech signals. Hence, the upper confidence limit from IMF log-energies of fGn is used as data adaptive threshold for VnV classification. If the subband log-energy of speech segment exceeds the threshold, the segment is classified as voiced and unvoiced otherwise. The experimental results show that the proposed algorithm performs better than the recently reported methods without requiring any training data for a wide range of SNRs.     

Nonlinear Interval Parameter Programming Combined with Cooperative Games: a Tool for Addressing Uncertainty in Water Allocation Using Water Diplomacy Framework

Water Resources Management - This paper shows the utility of a new interval cooperative game theory as an effective water diplomacy tool to resolve competing and conflicting needs of water users...     

Low temperature annealing of metals with electrical wind force effects

Conventional annealing is a slow, high temperature process that involves heating atoms uniformly, i.e., in both defective and crystalline regions. This study explores an electrical alternative for energy efficiency,where moderate current density is used to generate electron wind force that produces the same outcome as the thermal annealing process. We demonstrate this on a zirconium alloy using in-situ electron back scattered diffraction(EBSD) inside a scanning electron microscope(SEM) and juxtaposing the results with that from thermal annealing. Contrary to common belief that resistive heating is the dominant factor, we show that 5 × 10~4 A/cm~2 current density can anneal the material in less than 15 min at only135?C. The resulting microstructure is essentially the same as that obtained with 600?C processing for360 min. We propose that unlike temperature, the electron wind force specifically targets the defective regions, which leads to unprecedented time and energy efficiency. This hypothesis was investigated with molecular dynamics simulation that implements mechanical equivalent of electron wind force to provide the atomistic insights on defect annihilation and grain growth.     

Royal Crown Shaped Polarization Insensitive Perfect Metamaterial Absorber for C-, X-, and Ku-Band Applications

This study proposed a new royal crown-shaped polarisation insensitive double negative triple band microwave range electromagnetic metamaterial absorber (MA). The primary purpose of this study is to utilise the exotic characteristics of this perfect metamaterial absorber (PMA) for microwave wireless communications. The fundamental unit cell of the proposed MA consists of two pentagonal-shaped resonators and two inverse C-shaped metallic components surrounded by a split ring resonator (SRR). The bottom thin copper deposit and upper metallic resonator surface are disjoined by an FR-4 dielectric substrate with 1.6 mm thickness. The CST MW studio, a high-frequency electromagnetic simulator has been deployed for numerical simulation of the unit cell in the frequency range of 4 to 14 GHz. In the TE mode, the offered MA structure demonstrated three different absorption peaks at 6.85 GHz (C-band), 8.87 GHz (X-band), and 12.03 GHz (Ku-band), with 96.82%, 99.24%, and 99.43% absorptivity, respectively. The electric field, magnetic field, and surface current distribution were analysed using Maxwell’s-Curl equations, whereas the angle sensitivity was investigated to comprehend the absorption mechanism of the proposed absorber. The numerical results were verified using the Ansys HFSS (high-frequency structure simulator) and ADS (advanced design system) for equivalent circuit models. Moreover, the proposed MA is polarisation and incident angle independent. Hence, the application of this MA can be extended to a great extent, including airborne radar applications, defence, and stealth-coating technology.     

Harmonic modification and data adaptive filtering based approach to robust pitch estimation

A novel and robust pitch estimation method is presented in this paper. The basic idea is to reshape the speech signal using a combination of the dominant harmonic modification (DHM) and data adaptive time domain filtering techniques. The noisy speech signal is filtered within the ranges of fundamental frequencies to obtain the pre-filtered signal (PFS). The dominant harmonic (DH) of the PFS is determined and enhanced its amplitude. Normalized autocorrelation function (NACF) is applied to that modified signal. Then empirical mode decomposition (EMD) based data adaptive time domain filtering is applied to the NACF signal. Partial reconstruction is performed in EMD domain. The pitch period is determined from the partially reconstructed signal. The experimental results show that the proposed method performs better than the other recently developed methods for noisy and clean speech signals in terms of gross and fine pitch errors.     

The optimal solution for the flow of a fourth-grade fluid with partial slip

The steady flow of a non-Newtonian fluid when slippage between the plate and the fluid occurs is considered. The constitutive equations of the fluid are modeled for a fourth-grade non-Newtonian fluid with partial slip; they give rise to nonlinear boundary value problems. Analytical solutions are obtained using powerful analytic techniques for solving nonlinear problems, homotopy perturbation and optimal homotopy asymptotic methods. The results obtained are compared with the numerical results and it is shown that solutions exist for all values of the non-Newtonian parameters. The solutions valid for the no-slip condition for all values of the non-Newtonian parameters can be derived as special cases of the present analysis. Finally the solutions are discussed using a graphical approach.     

SPACE: A lightweight collaborative caching for clusters

In this paper, we introduce Systematic P2P Aided Cache Enhancement or SPACE, a new collaboration scheme among clients in a computer cluster of a high performance computing facility to share their caches with each other. The collaboration is achieved in a distributed manner, and is designed based on peer-to-peer computing model. The objective is to provide (1) a decentralized solution, and (2) a near optimal performance with reasonably low overhead. Simulation results are given to demonstrate the performance of the proposed scheme. In addition, the results show that SPACE evenly distributes work loads among participators, and entirely eliminates any requirement of a central cache manager.     

A multi-agent system model of a diesel engine using rule induction

The proliferation of a multi-agent system (MAS) and ideas from Artificial Intelligence (AI)/distributed AI have changed the way systems, in general are controlled, and operation of a system (diesel engine) in particular is automated. In this paper a distributed multi-agent architecture for a diesel engine and the knowledge sources that handle electricity generation is developed. Electronic devices and components used for data handling are described. The sensed data are presented in fuzzy logic and calculated in entropy values and depicted in a decision hierarchy. A comparative performance assessment of the proposed multi-agent based system with an existing system is presented and discussed.