A Strategy of Density-Based Partitioning for Scalability Problem in Network Self-management

A density-based partitioning strategy is proposed for large domain networks in order to deal with the scalability issue found in autonomic networks considering, as a scenario, the autonomic Quality of Service （QoS） management context. The approach adopted focus as on obtaining dense network partitions having more paths for a given vertices set in the domain. It is demonstrated that dense partitions improve autonomic processing scalability, for instance, reducing routing process complexity. The solution looks for a significant trade-off between partition autonomic algorithm execution time and path selection quality in large domains. Simulation scenarios for path selection execution time are presented and discussed. Authors argue that autonomic networks may benefit from the dense partition approach proposed by achieving scalable, efficient and near real-time support for autonomic management systems.     

Generative face alignment through 2.5D active appearance models

This work addresses the matching of a 3D deformable face model to 2D images through a 2.5D Active Appearance Models (AAM). We propose a 2.5D AAM that combines a 3D metric Point Distribution Model (PDM) and a 2D appearance model whose control points are defined by a full perspective projection of the PDM. The advantage is that, assuming a calibrated camera, 3D metric shapes can be retrieved from single view images. Two model fitting algorithms and their computational efficient approximations are proposed: the Simultaneous Forwards Additive (SFA) and the Normalization Forwards Additive (NFA), both based on the Lucas–Kanade framework. The SFA algorithm searches for shape and appearance parameters simultaneously whereas the NFA projects out the appearance from the error image and searches only for the shape parameters. SFA is therefore more accurate. Robust solutions for the SFA and NFA are also proposed in order to take into account the self-occlusion or partial occlusion of the face. Several performance evaluations for the SFA, NFA and theirs efficient approximations were performed. The experiments include evaluating the frequency of converge, the fitting performance in unseen data and the tracking performance in the FGNET Talking Face sequence. All results show that the 2.5D AAM can outperform both the 2D + 3D combined models and the 2D standard methods. The robust extensions to occlusion were tested on a synthetic sequence showing that the model can deal efficiently with large head rotation.     

A Web services-based framework for building componentized digital libraries

We present a new Web services-based framework for building componentized digital libraries (DLs). We particularly demonstrate how traditional RDBMS technology can be easily deployed to support several common digital library services. Configuration and customization of the framework to build specialized systems is supported by a wizard-like tool which is based on a generic metamodel for DLs. Such a tool implements a workflow process that segments the DL design tasks into well-defined steps and drives the designer along these steps. Both the framework and the configuration tool are evaluated in terms of several performance and usability criteria. Our experimental evaluation demonstrates the feasibility and superior performance of our framework, as well as the effectiveness of the wizard tool for setting up DLs.     

GMAC: An overlay multicast network for mobile agent platforms

The lack of proper support for multicast services in the Internet has hindered the widespread use of applications that rely on group communication services such as mobile software agents. Although they do not require high bandwidth or heavy traffic, these types of applications need to cooperate in a scalable, fair and decentralized way. This paper presents GMAC, an overlay network that implements all multicast related functionality–including membership management and packet forwarding–in the end systems. GMAC introduces a new approach for providing multicast services for mobile agent platforms in a decentralized way, where group members cooperate in a fair way, minimize the protocol overhead, thus achieving great scalability. Simulations comparing GMAC with other approaches, in aspects such as end-to-end group propagation delay, group latency, group bandwidth, protocol overhead, resource utilization and failure recovery, show that GMAC is a scalable and robust solution to provide multicast services in a decentralized way to mobile software agent platforms with requirements similar to MoviLog.     

On Nirenberg-type conditions for higher-order systems on time scales

We study the existence of periodic solutions for a nonlinear system of nth-order differential equations on time scales. Assuming a suitable Nirenberg-type condition, we prove the existence of at least one solution of the problem using Mawhin’s coincidence degree.     

AC electrokinetic pumping on symmetric electrode arrays

AC electro-osmotic (ACEO) pumping is experimentally demonstrated on a symmetric gold electrode array. Using asymmetric connection of electrodes to the applied AC voltage, spatial asymmetry along the array is created, which produces unidirectional flow of electrolyte. An aqueous solution of 100 μM KCl is selected as the pumping fluid. The liquid velocity obtained as a function of voltage and frequency is compared to that generated using travelling-wave electroosmosis (TWEO) with the same electrode array. The expected velocities from the linear electrokinetic models of ACEO and TWEO are computed numerically. The comparison shows that TWEO generates greater velocity amplitudes and the streamlines are smoother than those generated by ACEO.     

Investigation on the styrene-butadiene rubber cleavage with periodic acid under the influence of ultrasonic radiation

Summary The cleavage of styrene-butadiene rubber (SBR) with periodic acid (H₅IO₆) and simultaneous injection of ultrasonic radiation has been performed. Two frequencies, 25 and 40 kHz, respectively, have been used. The results demonstrate clearly that 40 kHz ultrasound radiation accelerates significantly the cleavage reaction. The Pearl String Model theory had been used to elucidate this process.     

Energy-efficient design of a presbyopia correction wearable powered by mobile GPUs and FPGAs

The Journal of Supercomputing - This paper presents an energy-efficient design and evaluation of a novel portable device for the automatic correction of presbyopia in human eyes driven by the use...     

Photocatalytic activity of a new composite material of Fe (III) oxide nanoparticles wrapped by a matrix of polymeric carbon nitride and amorphous carbon

Polymeric carbon nitride was synthesized from urea and doped with Cu and Fe to act as co-catalysts. The material doped with Fe was a new composite material composed of Fe(III) oxides (acting as a co-catalyst) wrapped by the polymer layers and amorphous carbon. Furthermore, the copper doped material was described in a previous report. The photocatalytic degradation of the azo dye direct blue 1 (DB) was studied using as photocatalysts: pure carbon nitride (CN), carbon nitride doped with Cu (CN-Cu) and carbon nitride doped with Fe (CN-Fe). The catalysts were characterized by Fourier transform infrared (FTIR) spectroscopy, X-ray diffraction (XRD), by X-ray photoelectron spectroscopy (XPS) and Brunauer–Emmett–Teller method (BET), etc. The adsorption phenomenon was studied using the Langmuir and Freundlich models. For the kinetic study, a solution of 500 mg L^?1 of DB1 was treated with each catalyst, visible light and H₂O₂. The dye concentration was measured by spectrophotometry at the wavelength of 565 nm, and the removal of the total organic content (TOC) was quantified. BET analysis yielded surface areas of 60.029, 20.116 and 70.662 m²g^?1 for CN, CN-Cu and CN-Fe, respectively. The kinetics of degradation were pseudo-first order, whose constants were 0.093, 0.039 and 0.110 min^?1 for CN, CN-Cu and CN-Fe, respectively. The total organic carbon (TOC) removal reached the highest value of 14.46% with CN-Fe.     

Heavy metal removal from simulated wastewater using electrochemical technology: optimization of copper electrodeposition in a membraneless fluidized bed electrode

Heavy metal removal from industrial wastewaters has been intensively studied, since it is well known that they can cause severe problems to human health and aquatic life, even at very low concentrations. In this work, it was demonstrated that electrodeposition in fluidized bed electrode (FBE) can be efficiently employed to remove metal ions from solution, avoid contamination, and recover the metal. Copper electrodeposition from diluted solutions was efficiently performed using a membraneless FBE. The average current efficiency (ACE), average energy consumption (AEC), and space–time yield (AY) was optimized taking into account the operational and process variables. It was noted that for all response variables studied, the raise of supporting electrolyte concentration (C _s) contributed to improvements in the process. The operational conditions current (I) and bed expansion (E) determined the values of CE, Y, and EC under activated control, but the initial copper concentration (C ₀) determined how long the electrodeposition process will work under activated or mass transfer control, thus affecting the average values of CE, Y, and EC. Considering C ₀ of 500 mg L^?1, copper can be optimally recovered with ACE >60 %, AY >38 kg h^?1 m^?3, and AEC <4.0 kWh kg^?1 by applying the lowest I and the highest levels of E and C _s. It was concluded that the electrochemical technology using a membraneless FBE reactor is economically competitive and be applied for the treatment of wastewaters contaminated with copper or other metals.