An efficient optimistic message logging scheme for recoverable mobile computing systems

A number of checkpointing and message logging algorithms have been proposed to support fault tolerance of mobile computing systems. However, little attention has been paid to the optimistic message logging scheme. Optimistic logging has a lower failure-free operation cost compared to other logging schemes. It also has a lower failure recovery cost compared to the checkpointing schemes. This paper presents an efficient scheme to implement optimistic logging for the mobile computing environment. In the proposed scheme, the task of logging is assigned to the mobile support station so that volatile logging can be utilized. In addition, to reduce the message overhead, the mobile support station takes care of dependency tracking and the potential dependency between mobile hosts is inferred from the dependency between mobile support stations. The performance of the proposed scheme is evaluated by an extensive simulation study. The results show that the proposed scheme requires a small failure-free overhead and the cost of unnecessary rollback caused by the imprecise dependency is adjustable by properly selecting the logging frequency.     

Eigen filter to detect volitional EMG signals in autogenic EMG-controlled FES

Presented is an eigen filter to remove autogenic electrical stimulation artefacts and M-waves while preserving the volitional electromyographic signal. The optimality of the eigen filter is shown, along with simulated and measured data to indicate its superior performance over conventional prediction error filters.     

Pervaporation separation of aqueous mixtures using crosslinked poly(vinyl alcohol), I. Characterization of the reaction between PVA and amic acid

For the purposes of new membrane material development for pervaporation separation based on crosslinked polyvinyl alcohol (PVA), IR spectroscopy and DSC were used to characterize the crosslinking reaction and the imidization of the (PVA)-amic acid system. The IR spectra and the thermal analysis were performed on specimens that had been reacted for several different times at 150°C. The crosslinking reaction between the hydroxy groups of PVA and the carboxylic groups of amic acid was faster than the imidization of the amic acid. The best reaction times were about 30 min for the crosslinking reaction and 90 min for the imidization. The effects of the reaction time and the amic acid content on the thermal and mechanical properties have also been investigated.     

Development of the semi-empirical equation of state for square-well chain fluid based on the Statistical Associating Fluid Theory (SAFT)

A semi-empirical equation of state for the freely jointed square-well chain fluid is developed. This equation of state is based on Wertheim’s thermodynamic perturbation theory (TPT) and the statistical associating fluid theory (SAFT). The compressibility factor and radial distribution function of square-well monomer are obtained from Monte Carlo simulations. These results are correlated using density expansion. In developing the equation of state the exact analytical expressions are adopted for the second and third virial coefficients for the compressibility factor and the first two terms of the radial distribution function, while the higher order coefficients are determined from regression using the simulation data. In the limit of infinite temperature, the present equation of state and the expression for the radial distribution function are represented by the Carnahan-Starling equation of state. This semi-empirical equation of state gives at least comparable accuracy with other empirical equation of state for the square-well monomer fluid. With the new SAFT equation of state from the accurate expressions for the monomer reference and covalent terms, we compare the prediction of the equation of state to the simulation results for the compressibility factor and radial distribution function of the square-well monomer and chain fluids. The predicted compressibility factors for square well chains are found to be in a good agreement with simulation data. The high accuracy of the present equation of state is ascribed to the fact that rigorous simulation results for the reference fluid are used, especially at low temperatures and low densities. This paper was presented at the 8th APCChE (Asia Pacific Confederation of Chemical Engineering) Congress held at Seoul between August 16 and 19, 1999.     

Analysis of microbial adaptation at enzyme level for enhancing biodegradation rate of BTX

Catechol was found to be a common intermediate in the degradation of benzene and toluene byAlcaligenes xyhsoxidans Y234, and the ring cleavage of the catechol mediated by catechol 1,2-dioxygenase was a rate-determining step. Since benzene induced higher level of catechol 1,2-dioxygenase than toluene, the cells pre-adapted to benzene showed higher degradation rate of benzene and toluene. The degradation rate ofm-xylene was also increased significantly when benzene-adapted cells were inoculated.m-Xylene was metabolized via 3-methyl catechol which was effectively cleaved by catechol 1,2-dioxygenase.     

On the modeling of electro-hydrodynamic flow in a wire-plate electrostatic precipitator

Modeling of the flow velocity fields for the electrohydrodynamic (EHD) flow in a wire-to-plate type electrostatic precipitator (ESP) was achieved. Solutions of the steady, two-dimensional Navier-Stokes equations have been computed. The equations were solved in the conservative finite-difference form on a fine uniform rectilinear grid of sufficient resolution to accurately capture the momentum boundary layers. The numerical procedure for differential equations was used by SIMPLEST [Michel, 2002], a derivative of Patankar’s SIMPLE algorithm, to bring rapid convergence. The Phoenics (Version 3.5.1) CFD code, coupled with Poisson’s and ion transport equations and electric body force in the momentum equation, developed in this study, was used for the numerical simulation. From calculations for the flow employing different flow models, the Chen-Kimk-ε turbulent model appeared to be the most appropriate choice to obtain a quantitative image of the resulting mean flow field and downstream wake flow of the rear wire, although this was obtained from a qualitative analysis due to the lack of experimental verification. The flow velocity field pattern showed a strong EHD secondary flow, which was clearly visible in the downstream regions of the corona wire despite the low Reynolds number for the electrode (Re_CW=12.4). Secondary flow vortices were also caused by the EHD with increases in the discharge current     

Robust person re-identification via graph convolution networks

Person re-identification (re-id) aims to identity the same person over multiple cameras; it has been successfully applied to various computer vision applications as a fundamental method. Owing to the development of deep learning, person re-id methods, which typically use triplet networks based on triplet loss, have demonstrated great success. However, the appearances of people are similar and hence difficult to distinguish in many cases. Therefore, we present a novel graph convolution network and enhances traditional triplet loss functions. Our method defines reference, positive, and negative features for triplet loss as three vertices of a graph, respectively, and adjusts their mutual distance through learning. The method adopts graph convolutions efficiently, thereby affording low computational costs. Experimental results demonstrate that our method is superior to the baseline on the Market-1501 dataset. The proposed GCN-based triplet loss considerably contributes to improve re-identification methods quantitatively and qualitatively.

     

Correlating the 3D melt electrospun polycaprolactone fiber diameter and process parameters using neural networks

In the present work, we developed an artificial neural networks (ANN) model to predict and analyze the polycaprolactone fiber diameter as a function of 3D melt electrospinning process parameters. A total of 35 datasets having various combinations of electrospinning writing process variables (collector speed, tip to nozzle distance, applied pressure, and voltage) and resultant fiber diameter were considered for model development. The designed stand-alone ANN software extracts relationships between the process variables and fiber diameter in a 3D melt electrospinning system. The developed model could predict the fiber diameter with reasonable accuracy for both train (28) and test (7) datasets. The relative index of importance revealed the significance of process variables on the fiber diameter. Virtual melt spinning system with the mean values of the process variables identifies the quantitative relationship between the fiber diameter and process variables.     

A resource allocation policy for delay minimization in fetching capacitated feeds

As social media services such as Twitter and Facebook are gaining popularity, the amount of information published from those services is explosively growing. Most of them use feeds to facilitate distribution of a huge volume of content they publish. In this context, many users subscribe to feeds to acquire up-to-date information through feed aggregation services, and recent real-time search engines also increasingly utilize feeds to promptly find recent web content when it is produced. Accordingly, it is necessary for such services to effectively fetch feeds for minimizing fetching delay, while at the same time maximizing the number of fetched entries. Fetching delay is a time lag between entry publication and retrieval, which is primarily incurred by finiteness of fetching resources. In this paper, we consider a polling-based approach among the methods applicable to fetching feeds, which bases on a specific schedule for visiting feeds. While the existing polling-based approaches have focused on the allocation of fetching resources to feeds in order to either reduce the fetching delay or increase the number of fetched entries, we propose a resource allocation policy that can optimize both objectives. Extensive experiments have been carried out to evaluate the proposed model, in comparison with the existing alternative methods.     

Chiral Se Nanobrooms with Wavelength and Polarization Sensitive Scattering

High-index dielectric nanostructures offer strong magnetic and electric resonances in the visible range and low optical losses, stimulating research interest in their use for light manipulation technologies. Lithographic fabrication of dielectric nanostructures, while providing precise control over the pattern dimensions, limits the scalability of this approach for practical applications due to an inefficient fabrication process and limited production quantity. Here, the colloidal synthesis of high-index chiral dielectric nanostructures with a broom-like geometry made from trigonal Se is demonstrated. The anisotropic morphology and crystal structure of Se nanobrooms enable both linearly and circularly polarized scattering, as well as spectrum variation along the particle axis, which is, to the authors’ knowledge, the first observation of such behavior from dielectric colloidal nanostructures. To show the versatility of the highly scattering Se NB suspensions, 2D and 3D printing of Se NB inks are demonstrated as a proof of concept. This approach provides a way to manipulate light using aqueous dispersions of high-index dielectric nanostructures, unlocking their potential to fit in various morphologies and dimensions in 2D and 3D for broad applications.