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...     

A model of checkpoint behavior for applications that have I/O

Due to the increase and complexity of computer systems, reducing the overhead of fault tolerance techniques has become important in recent years. One technique in fault tolerance is checkpointing, which saves a snapshot with the information that has been computed up to a specific moment, suspending the execution of the application, consuming I/O resources and network bandwidth. Characterizing the files that are generated when performing the checkpoint of a parallel application is useful to determine the resources consumed and their impact on the I/O system. It is also important to characterize the application that performs checkpoints, and one of these characteristics is whether the application does I/O. In this paper, we present a model of checkpoint behavior for parallel applications that performs I/O; this depends on the application and on other factors such as the number of processes, the mapping of processes and the type of I/O used. These characteristics will also influence scalability, the resources consumed and their impact on the IO system. Our model describes the behavior of the checkpoint size based on the characteristics of the system and the type (or model) of I/O used, such as the number I/O aggregator processes, the buffering size utilized by the two-phase I/O optimization technique and components of collective file I/O operations. The BT benchmark and FLASH I/O are analyzed under different configurations of aggregator processes and buffer size to explain our approach. The model can be useful when selecting what type of checkpoint configuration is more appropriate according to the applications’ characteristics and resources available. Thus, the user will be able to know how much storage space the checkpoint consumes and how much the application consumes, in order to establish policies that help improve the distribution of resources.

     

The synthesis of pixelated metamaterial cross polarizer using binary wind driven optimization algorithm

Microsystem Technologies - In this paper synthesis of two wideband Metamaterial Cross Polarizer (MCPs) is proposed. The synthesis of proposed MCPs is done by using Binary Wind Driven Optimization...     

Long short-term cognitive networks

Neural Computing and Applications - In this paper, we present a recurrent neural system named long short-term cognitive networks (LSTCNs) as a generalization of the short-term cognitive network...     

Analysis of the influence of binder properties on the mechanical response of bituminous mixtures

Asphalt mixtures are composed by a mass of aggregates (more than 90% of their total weight), which are bonded by a bituminous binder. Despite the fact that the binder is not the main component of these materials (around 5% of their total weight), it exerts a high influence on their mechanical response. In this sense, the service life of asphalt pavements will directly depend on the type of binder used, and thus an adequate choice is crucial to construct more durable roads. Because of this fact, it is necessary to know the characteristics of the bitumen in order to reduce the impact of different distresses that appear on roads. For this purpose, this paper studies the influence of the binder properties in the appearance of the main distresses that affect asphalt pavements around the world (stripping, fatigue cracking and plastic deformations). Five bitumens with different properties have been analysed during this research using diverse binder (UCL, multiple stress creep and recovery test and dynamic shear rheometer time sweep) and mixture (water sensitivity, wheel tracking and UGR-FACT) tests. The results obtained show that the properties of the binder influence the long-term performance of bituminous mixtures. In this sense, it can be said that flexible binders which are able to recover plastic deformations could extend the service life of the pavements.     

Ball-burnishing effect on deep residual stress on AISI 1038 and AA2017-T4

Ball-burnishing induces compressive residual stresses on treated materials by the effect of plastic deformation. The result is an increase in the fatigue life of the treated part, retarding the initiation of cracks on the surface. Compressive residual stresses have been previously measured by X-ray diffraction near the surface, revealing considerably high values at the maximum analyzed depth, in relation to other finishing processes such as shot peening. However, the maximum analyzed depth is very limited by using this technique. In this paper, the incremental hole drilling (IHD) technique is tested to measure residual stresses, being able to reach a 2-mm measuring depth. To that objective, a commercial strain gage is used and calibrated using finite element model simulations. A second Finite Element Model based on material removal rate is developed to obtain the equations to calculate the strain release through IHD. Finally, residual stresses are measured experimentally with that technique on two different materials, confirming that ball-burnishing increases the compressive residual stresses in layers up to 0.5?mm deep for the testing conditions, which is a good response to industrial needs. The method proves to be suitable, simple and inexpensive way to measure the value of these tensions.     

Honest confidence regions and optimality in high-dimensional precision matrix estimation

We propose methodology for estimation of sparse precision matrices and statistical inference for their low-dimensional parameters in a high-dimensional setting where the number of parameters p can be much larger than the sample size. We show that the novel estimator achieves minimax rates in supremum norm and the low-dimensional components of the estimator have a Gaussian limiting distribution. These results hold uniformly over the class of precision matrices with row sparsity of small order \(\sqrt{n}/\log p\) and spectrum uniformly bounded, under a sub-Gaussian tail assumption on the margins of the true underlying distribution. Consequently, our results lead to uniformly valid confidence regions for low-dimensional parameters of the precision matrix. Thresholding the estimator leads to variable selection without imposing irrepresentability conditions. The performance of the method is demonstrated in a simulation study and on real data.     

Bandwidth selection in kernel density estimation for interval-grouped data

When interval-grouped data are available, the classical Parzen–Rosenblatt kernel density estimator has to be modified to get a computable and useful approach in this context. The new nonparametric grouped data estimator needs of the choice of a smoothing parameter. In this paper, two different bandwidth selectors for this estimator are analyzed. A plug-in bandwidth selector is proposed and its relative rate of convergence obtained. Additionally, a bootstrap algorithm to select the bandwidth in this framework is designed. This method is easy to implement and does not require Monte Carlo. Both proposals are compared through simulations in different scenarios. It is observed that when the sample size is medium or large and grouping is not heavy, both bandwidth selection methods have a similar and good performance. However, when the sample size is large and under heavy grouping scenarios, the bootstrap bandwidth selector leads to better results.     

Stability and electronic properties of armchair boron nitride/carbon nanotubes

In this work are studied the electronic and structural properties of armchair boron nitride/carbon nanotubes using first principles calculations. The density functional within the generalized gradient approximation (HSEh1PBE-GGA) is used. For each composition, different bonding schemes for the construction of the hybrid systems were employed. Among them, structural stability with neutral charge was determined for the following compositions: T1: B₄₀N₃₅C₇₅H₂₀, T2: B₃₅N₄₀C₇₅H₂₀, T3: B₃₇N₃₈C₇₅H₂₀, T4 : B₃₇N₃₇C₇₆H₂₀, and T7: B₃₅N₃₅C₈₀H₂₀. All these hybrid nanotubes have high polarity; the T3, T4 and T7 are semiconductors: whereas T1 and T2 are conductor in character. The formers also have magnetic behavior. These properties together with a low-chemical potential suggest applications as nano-vehicle for drug delivery. These mixed nanotubes also have potential applications in the electronic devices based on the small work function.     

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.