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Flexible and rigid pavements are commonly built for airport pavements to support the moving loads of aircraft during the pavement design life. At the planning stage, the pavement structure, materials, aircraft loads, environmental conditions, and pavement damage models should be evaluated. Comparing with road pavement design, airport pavement structural design is unique in terms of the traffic loads supported by pavements with high load magnitude, significant tire pressure, and dynamic traffic conditions. With the transition from conventional empirical design to mechanistic-empirical approaches, the mechanistic-empirical approaches are adopted in the various computer programs as the main methods for pavement structural design. The methods developed by the Federal Aviation Administration (FAA) and other approaches of airport pavement structural design are discussed in this paper to compare their analysis methodology and identify the advancement of each design method. A highlight of this paper is to examine the recent specifications for airport pavement structural design (FAA AC 150/5320–6 G) and the structural evaluation (FAA AC 150/5335–5D) released by the FAA. In addition, in order to support the maintenance and rehabilitation (M&R) strategy, the pavement structural condition and material properties can be assessed by a Falling Weight Deflectometer (FWD) or a Heavy Weight Deflectometer (HWD) test. Future structural design of airport pavements should consider potential pavement failure patterns caused by complex gear loading types, and continuous pavement M&R using FWD or HWD tests. • Airport pavement structural design is unique in terms of the traffic loads. • The difference between traditional empirical and mechanistic methods is reviewed. • The latest specifications for airport pavement structural design are reviewed. • The application of nondestructive tests in the pavement design is reviewed. • The maintenance and rehabilitation (M&R) strategies of pavements are reviewed. [ABSTRACT FROM AUTHOR]

We present a method for fast computation of highly oscillatory Fourier-type integrals with monomial phase functions and Jacobi-type singularities. It is shown that on an appropriately chosen contour in the complex plane the original integral can be expressed as the sum of two nonoscillatory and rapidly decaying integrals, each of which can be efficiently computed by the generalized Gauss-Laguerre rule or by the double exponential method. For moderate and large frequencies, the proposed method is stable and more efficient than the existing methods. We also give a Mathematica program for the implementation of the method on a computer. The effectiveness and accuracy is tested by means of numerical examples. [ABSTRACT FROM AUTHOR]

Detection energy window of Makrofol detector irradiated with alpha particles and chemically treated by PEW (potassium hydroxide, ethanol, water) solution was investigated. Detectors were exposed to 241 Am source through the cylindrical collimators in order to control incident alpha particle energies and angles. Alpha particles were detected in the wide energy range from 0.4 MeV to above 5 MeV. The dependence of track diameter on particle incident energy was also examined. Changes of etchant concentration and bulk etch rate (V b) during two-hour etching were investigated. A slight increase of etchant concentration was observed while V b was nearly constant during the whole etching process. Alpha particle passage through collimators with various dimensions and the corresponding energy distribution were also simulated theoretically using Monte Carlo Method and computer program written in Fortran90. • Detection energy window of Makrofol irradiated with alpha particles was investigated. • Particles in the energy range from 0.4 MeV to above 5 MeV were detected. • The dependence of track diameter on particle incident energy followed Bragg curve. • A slight increase of etchant concentration was observed; V b was nearly constant. [ABSTRACT FROM AUTHOR]

Abstract Most cryptographic schemes are designed in a model where perfect secrecy of the secret key is assumed. In most physical implementations, however, some form of information leakage is inherent and unavoidable. To deal with this, a flurry of works showed how to construct basic cryptographic primitives that are resilient to various forms of leakage. Dodis et al. (FOCS '10) formalized and constructed leakage resilient one-way functions. These are one-way functions f such that given a random image f (x) and leakage g (x) it is still hard to invert f (x). Based on any one-way function, Dodis et al. constructed such a one-way function that is leakage resilient assuming that an attacker can leak any lossy function g of the input. In this work we consider the problem of constructing leakage resilient one-way functions that are secure with respect to arbitrary computationally hiding leakage (a.k.a. auxiliary-input). We consider both types of leakage – selective and adaptive – and prove various possibility and impossibility results. On the negative side, we show that if the leakage is an adaptively-chosen arbitrary one-way function, then it is impossible to construct leakage resilient one-way functions. The latter is proved both in the random oracle model (without any further assumptions) and in the standard model based on a strong vector-variant of DDH. On the positive side, we observe that when the leakage is chosen ahead of time, there are leakage resilient one-way functions based on a variety of assumption. [ABSTRACT FROM AUTHOR]

X-Frame core sandwich structures are fabricated with carbon fiber reinforced polymer (CFRP) face sheets and aluminum alloy cores. The hybrid combination enables composite face sheets to maximize specific flexural stiffness and X-Frame metal core to improve the impact resistance. The effects of impact energy, impact site and face sheet material type on the impact response and resulting damage state have are investigated experimentally and numerically. The low-velocity impact tests are carried out to study the impact response in terms of the impact load, absorbed energy and failure modes. Meanwhile, finite element analysis is implemented to simulate the impact behaviors and failure mechanisms by the VUMAT subroutine in ABAQUS/Explicit, using a progressive damage model based on the Hashin and Yeh delamination failure criteria. For comparison, all-metallic sandwich structures are also studied to better understand the influence of face sheet materials. These studies reveal that impact response and resulting damage state are strongly dependent on the impact energy and impact site. Composite sandwich structure absorbs more impact energy than aluminum sandwich structure for the perforation case, indicating that the former has better impact resistance. The predicted results of the low-velocity impact response are fairly consistent with the experimental measurements, which suggests that the numerical procedure could be a helpful tool in developing novel lightweight multifunctional structures. [ABSTRACT FROM AUTHOR]

In this work, we address to boost the discriminative capability of deep neural network by alleviating the over-fitting problem. Previous works often deal with the problem of learning a neural network by optimizing one or more objective functions with some existing regularization methods (such as dropout, weight decay, stochastic pooling, data augmentation, etc.). We argue that these approaches may be difficult to further improve the classification performance of a neural network, due to not well employing its own learned knowledge. In this paper, we introduce a self-regularized strategy for learning a neural network, named as a Self-Regularized Neural Network (SRNN). The intuition behind the SRNN is that the sample-wise soft targets of a neural network may have potentials to drag its own neural network out of its local optimum. More specifically, an initial neural network is firstly pre-trained by optimizing one or more objective functions with ground truth labels. We then gradually mine sample-wise soft targets, which enables to reveal the correlation/similarity among classes predicted from its own neural network. The parameters of neural network are further updated for fitting its sample-wise soft targets. This self-regularization learning procedure minimizes the objective function by integrating the sample-wise soft targets of neural network and the ground truth label of training samples. Three characteristics in this SRNN are summarized as: (1) gradually mining the learned knowledge from a single neural network, and then correcting and enhancing this part of learned knowledge, resulting in the sample-wise soft targets; (2) regularly optimizing the parameters of this neural network with their sample-wise soft targets; (3) boosting the discriminative capability of a neural network with the self-regularization strategy. Extensive experiments on four public datasets, i.e., CIFAR-10, CIFAR-100, Caltech101 and MIT, well demonstrate the effectiveness of the proposed SRNN for image classification. [ABSTRACT FROM AUTHOR]

This paper presents the development of a simulation model, which was incorporated into a Geographic Information System (GIS) in order to calculate the maximum intensity of urban heat islands (UHI max ) based on urban geometry data (using a H/W parameter). This tool is called THIS – Tool for Heat Island Simulation. The urban heat island phenomenon is defined by the temperature rise in dense city centers compared with the surrounding countryside. The methodology of this study is based on a theoretical-numerical basis (Oke model), followed by the development of a calculation algorithm incorporated into the GIS platform, which is then adjusted and applied as exemplification. This adjustment was made by calibrating the Oke model for a case study based on two Brazilian cities and different various trends for different roughness length ranges were found. As a consequence, this work has resulted in the automation of an algorithm to obtain maximum intensity values of heat islands based on a simplified model. After finishing the subroutine, the application of the THIS in a simulation of different urban scenarios showed different trends in the UHI max value for the H/W ratio and the roughness length. The UHI max increases when the H/W ratio increases, but the urban canyons with greater roughness (larger areas of facades and more heterogeneous heights, Z 0 ≥ 2.0) result in UHI max values of approximately two times smaller than canyons with less roughness (homogeneous with highest average areas occupied by buildings, Z 0 < 2.0) for the same value as the H/W ratio. Overall, the developed tool has one aim: to simulate the effect of the isolated variable of urban geometry on the maximum intensity of nocturnal heat islands, considering different urban scenarios. [ABSTRACT FROM AUTHOR]

We prove a necessary and sufficient condition for a function being a polynomial function over a finite, commutative, unital ring. Further, we give an algorithm running in quasilinear time that determines whether or not a function given by its function table can be represented by a polynomial, and if the answer is yes then it provides one such polynomial. [ABSTRACT FROM AUTHOR]

Over the last 20 years, the study of accidents involving ship collisions and strandings has led to the development of different methodologies, and to simulate numerically the material's ductile fracture, several failure criteria have been applied. Most of the failure criteria used in these problems are based on a critical value of the equivalent plastic strain, where it is admitted that fracture initiates when this value is reached. In the literature, there is still a great diversification of failure criteria alternatives, but the idea of considering the accumulated damage in the material has been more and more gaining ground. With this perspective, this article considers a new approach for the application of numerical analysis to ship collision and stranding, based on the Continuum Damage Mechanics (CDM), where new internal variables are inserted in the material constitutive equations, related to the damage produced by the stress field. The objective of the present paper is to propose and assess a modification in Lemaitre's damage model, which is the substitution of the constant denominator of damage by a function, called Model with Denominator of Damage Function (MDDF), for the prediction of the location and time instant of the material fracture initiation. This paper also describes the implementation of the proposed model, using the UMATs subroutines integrated to the LS-DYNA program. To validate the proposed fracture criterion, comparisons are conducted with the experimental results, present in the literature, of two stiffened panels subject to indentation, and also with the Rice-Tracey-Cockroft-Latham (RTCL) and Bressan-Williams-Hill (BWH) criteria applied to these panels. In such comparisons, the results in terms of the fracture location and the force versus displacement curve are excellent. Finally, a methodology is developed to simulate ship collisions using the proposed model as material failure criterion. The methodology is applied to a case study of a ship collision scenario and compared to RTCL and BWH failure criteria, resulting in a larger collision internal energy. [ABSTRACT FROM AUTHOR]

In this paper, a Decision Support System (DSS) for generating a suitable portfolio for an investor in an uncertain multi-criteria framework is proposed. We model uncertain parameters like return and illiquidity of various assets using L–R fuzzy numbers belonging to a power reference function family. Such usage of L–R fuzzy numbers is more generic as compared to the conventional triangular or trapezoidal fuzzy numbers and is a closer representation of uncertain behavior of the asset parameters. The credibility measure which has an advantage of being self-dual as compared to usual possibility measure marks the uncertain context of the entire setup and adds a new dimension to existing studies. We use an “Entropy-Cross Entropy (ECE) Algorithm”, for finding the solution of the optimization problem meant for finding the best fit L–R fuzzy number corresponding to uncertain asset parameters. This automates the entire subjective exercise where, otherwise, a human intervention is required for feeding the parameters required for fitting L–R fuzzy number. Once the L–R fuzzy number are created around various assets available for the portfolio formation, the portfolio optimization problem is solved using Hybrid Intelligent Algorithm (HIA). HIA is designed by embedding fuzzy simulation within the “MIBEX-SM” genetic algorithm. To demonstrate the entire solution approach, four portfolio optimization models are solved using historical data from the National Stock Exchange (NSE) of India. The performance of the models is compared using a modified Sharpe ratio in the fuzzy context, namely the “Credibilistic Sharpe Ratio (CrSR)”. To carry out the empirical study, firstly we use the data from the period of 2008–2013 for training the optimization models. Thereafter, to test the performance of the models, the data set from the two year period 2013–2015 is used. The process of validation of the results is then carried out using the data set of the one year period from 2015 to 2016. [ABSTRACT FROM AUTHOR]

The present study developed and implemented a new visco-hyperelastic model that is capable of predicting the time-dependent biomechanical behavior of the periodontal ligament. The constitutive model has been implemented into the finite element package ABAQUS by means of a user-defined material subroutine (UMAT). The stress response is decomposed into two constitutive parts in parallel which are a hyperelastic and a time-dependent viscoelastic stress response. In order to identify the model parameters, the indentation equation based on V-W hyperelastic model and the indentation creep model are developed. Then the parameters are determined by fitting them to the corresponding nanoindentation experimental data of the PDL. The nanoindentation experiment was simulated by finite element analysis to validate the visco-hyperelastic model. The simulated results are in good agreement with the experimental data, which demonstrates that the visco-hyperelastic model developed is able to accurately predict the time-dependent mechanical behavior of the PDL. [ABSTRACT FROM AUTHOR]

A challenging class of problems arising in many GPU applications, called batched problems, involves linear algebra operations on many small-sized matrices. We designed batched BLAS (Basic Linear Algebra Subroutines) routines, and in particular the Level-2 BLAS GEMV and the Level-3 BLAS GEMM routines, to solve them. We proposed device functions and big-tile settings in our batched BLAS design. We adopted auto-tuning to optimize different instances of GEMV routines. We illustrated our batched BLAS approach to optimize batched bi-diagonalization progressively on a K40c GPU. The optimization techniques in this paper are applicable to the other two-sided factorizations as well. [ABSTRACT FROM AUTHOR]

A numerical investigation was carried out to analyze in details the perforation process of target AA5754-O Aluminum plate when subjected to normal impact at low (up to 25 ms − 1 ) and moderate velocities (ranged between 25 − 50 ms − 1 ). A fully coupled elasto-visco-plastic-damage model is implemented into a user-defined material (VUMAT) subroutine for the commercial finite element code ABAQUS/Explicit. The strain rate effect is considered. Comparison between isotropic J 2 and orthotropic Hill yield criteria associated with isotropic and mixed non-linear isotropic/kinematic hardening was conducted. A parametric study of the effect of anisotropy, plate thickness and impactor nose shapes on ballistic limit and petal forming is carried out. A good agreement is found between numerical and experimental results conducted by other researchers. [ABSTRACT FROM AUTHOR]

We consider the NP-hard m - parallel two-stage flowshop problem, abbreviated as the ( m , 2 ) -PFS problem, where we need to schedule n jobs to m parallel identical two-stage flowshops in order to minimize the makespan, i.e. the maximum completion time of all the jobs on the m flowshops. The ( m , 2 ) -PFS problem can be decomposed into two subproblems: to assign the n jobs to the m parallel flowshops, and for each flowshop to schedule the jobs assigned to the flowshop. We first present a pseudo-polynomial time dynamic programming algorithm to solve the ( m , 2 ) -PFS problem optimally, for any fixed m , based on an earlier idea for solving the ( 2 , 2 ) -PFS problem. Using the dynamic programming algorithm as a subroutine, we design a fully polynomial-time approximation scheme (FPTAS) for the ( m , 2 ) -PFS problem. [ABSTRACT FROM AUTHOR]

Gerchberg-Saxton Algorithm is a common tool for designing Computer Generated Holograms. There exist some standard functions for evaluating the quality of the final results. However, the use of randomized initial guess leads to different results, increasing the variability of the evaluation functions values. This fact is especially detrimental when the computing time is elevated. In this work, a new tool is presented, able to describe the fidelity of the results with a notably reduced variability after multiple attempts of the Gerchberg-Saxton Algorithm. This new tool results very helpful for topical fields such as 3D digital holography. [ABSTRACT FROM AUTHOR]

The analysis of multidimensional data has been a topic of continuous research for many years. This type of data can be found in several different areas of science. A common task while analyzing such data is to investigate patterns by interacting with spatializations of the data in a visual domain. Understanding the relation between the underlying dataset characteristics and the technique used to provide its visual representation is of fundamental importance since it can provide a better intuition on what to expect from the spatialization. In this paper, we propose the usage of concepts from non-parametric statistics, namely depth functions, as a quality measure for spatializations. We evaluate the action of multidimensional projection techniques on such estimates. We apply both qualitative and quantitative analyses on four different multidimensional techniques selected according to the properties they aim to preserve. We evaluate them with datasets of different characteristics: synthetic, real world, high dimensional; and contaminated with outliers. As a straightforward application, we propose to use depth information to guide multidimensional projection techniques which rely on interaction through control point selection and positioning. Even for techniques which do not intend to preserve any centrality measure, interesting results can be achieved by separating regions possibly contaminated with outliers. [ABSTRACT FROM AUTHOR]

Ensemble is a widely used technique to improve the predictive performance of a learning method by using several competing expert systems. In this study, we propose a new ensemble combination scheme using a latent consensus function that relates each predictor to the other. The proposed method is designed to adapt and self-correct weights even when a number of expert systems malfunction and become corrupted. To compare the performance of the proposed method with existing methods, experiments are performed on simulated data with corrupted outputs as well as on real-world data sets. Results show that the proposed method is effective and it improves the predictive performance even when a number of individual classifiers are malfunctioning. [ABSTRACT FROM AUTHOR]

JADE and CoDE are two well-known state-of-the-art DE algorithms for solving global optimization problems (GOPs). JADE is found to be suitable for solving unimodal and simple multimodal functions as an exploitation mutation strategy, i.e. “DE/current-to- p best/1”, is employed, while CoDE is shown to fit for handling complicated multimodal functions due to its exploration mutation strategies, such as “DE/rand/1/bin”, “DE/currant-to-rand/1”, and “DE/rand/2/bin”. To combine their merits for tackling different types of GOPs, a novel hybrid framework is designed based on the modified JADE (MJADE) and modified CoDE (MCoDE), named HMJCDE. Different from the simple combination of MJADE and MCoDE, they are operated alternatively according to the improvement rate of the fitness value. To assess the performance of HMJCDE, 30 benchmark problems taken from CEC2014 competition on real parameter optimization are employed. When compared with JADE, CoDE, other state-of-the-art DE variants and non-DE heuristic algorithms, HMJCDE performs better than all the competitors on most of test problems. Moreover, the sensitivity analysis of some parameters in HMJCDE is conducted and the effectiveness of our proposed hybrid framework is also justified experimentally. [ABSTRACT FROM AUTHOR]

Amongst all the multilevel thresholding techniques, standard histogram based thresholding approaches are very impressive for bi-level thresholding. But, it is not effective to select spatial contextual information of the image for choosing optimal thresholds. In this paper, a new color image thresholding technique is presented by using an energy function to generate the energy curve of an image by considering spatial contextual information of the image. The property of this energy curve is very much similar to histogram of the image. To estimate the spatial contextual information for thresholding practice, in place of histogram, the energy curve function is used as an input. A new energy curve based color image segmentation approach using three well known objective functions named Kapur’s entropy, between-class-variance, and Tsalli’s entropy is proposed. In this paper, cuckoo search (CS) and egg lying radius-cuckoo search (ELR-CS) optimization algorithms with different parameter analysis have been used for solving the color image multilevel thresholding problem. The experimental results demonstrate that the proposed CS-Kapur’s energy curve based segmentation can powerfully and accurately search the multilevel thresholds. [ABSTRACT FROM AUTHOR]

The objective of this paper is to assess the reliability and effectiveness of the method of finite spheres, a truly meshless overlapping finite element method, for the solution of practical three-dimensional linear elasticity problems. Advantages include simplified discretization and the elimination of element distortion. The method is implemented in the ADINA finite element program through a user-supplied element subroutine. The solutions of three increasingly complex three-dimensional problems are studied (1) to establish the reliability of the method for practical linear elasticity problems and (2) to assess the effectiveness of the method as compared to the standard finite element method. The solutions indicate that the method of finite spheres is between one and two orders of magnitude more expensive in computational time than the standard finite element method. This is still a promising result since there are significant time savings for the method of finite spheres during the pre-processing phase, particularly in the discretization of complicated three-dimensional geometries and because the overlapping sphere elements can be directly coupled to traditional finite elements. [ABSTRACT FROM AUTHOR]

Chaboche kinematic hardening, Yoshida–Uemori, and homogenous anisotropic hardening (HAH) models were evaluated in terms of their prediction capability of flow stress and evolutionary r-value under loading path changes. The first two models are based on kinematic hardening, whereas the HAH model is based on distortional hardening. Continuous compression–tension (CT) tests with pre-strains for dual-phase 780 and transformation-induced plasticity (TRIP) 780 steel sheets were conducted. For the initial anisotropy described by the Yld2000-2d model, uniaxial tension tests for three material orientations and a biaxial test were performed. During the CT tests, both stress and r-value variations with plastic strain were measured. All the models were implemented into the finite element software ABAQUS using user material subroutines. Experimentally, both sheets exhibited typical anisotropic hardening features such as the Bauschinger effect, transient hardening, and long-range softening. The TRIP 780 exhibited small work-hardening stagnation. In addition, the evolutionary r-value during the second loading was significant. The three models could predict most of the features in the stress–strain curves during the second loading. However, only the HAH model could predict the experimentally observed r-value evolution. This evolutionary r-value predicted by the HAH model could be explained by distortion of the yield locus during the first loading and its rapid recovery toward the initial yield locus shape. [ABSTRACT FROM AUTHOR]

This paper presents PinMesh, a very fast algorithm with implementation to preprocess a polyhedral mesh, also known as a multi-material mesh, in order to perform 3D point location queries. PinMesh combines several innovative components to efficiently handle the largest available meshes. Because of a 2-level uniform grid, the expected preprocessing time is linear in the input size, and the code parallelizes well on a shared memory machine. Querying time is almost independent of the dataset size. PinMesh uses exact arithmetic with rational numbers to prevent roundoff errors, and symbolic perturbation with Simulation of Simplicity (SoS) to handle geometric degeneracies or special cases. PinMesh is intended to be a subroutine in more complex algorithms. It can preprocess a dataset and perform 1 million queries up to 27 times faster than RCT (Relative Closest Triangle), the current fastest algorithm. Preprocessing a sample dataset with 50 million triangles took only 14 elapsed seconds on a 16-core Xeon processor. The mean query time was 0.6μs. [ABSTRACT FROM AUTHOR]

Johnson–Cook (J-C) material model is often used for Finite Element (FE) modeling of cutting processes and it affects significantly the results of simulation. Since experimentally determination of J-C equation parameters is an expensive and time-consuming task, in this paper, a new and efficient methodology was implemented based on the evolutionary optimization algorithm to identify new J-C material constants for Inconel 718 superalloy. Then, orthogonal cutting process of Inconel 718 was simulated using the new material models. The results of simulation were compared extensively with experimental results of cutting forces, chip geometry, and maximum temperature to select and then validate the most suitable material model. After that, a user subroutine was implemented in FE code to model microstructure changes using the dynamic recrystallization mechanism in cutting process of Inconel 718. The Zener–Hollomon and Hall–Petch equations were used to respectively predict the grain size and hardness. The results of simulation were verified successfully with corresponding experiments in terms of near-surface profile. At the end, the effect of tool edge geometry including honed and chamfered tool edge was investigated on microstructure changes. [ABSTRACT FROM AUTHOR]

Braided textile composite exhibits an efficient mechanism to distribute loads throughout its structure and have excellent impact resistant properties. Despite many works in the past, the successful prediction of braided textile composites strength still remains a challenge today. In this paper, a numerical simulation model based on a meso-scale approach is presented to predict the strength and damage behavior of braided textile composites. A meso-scale homogenized representative unit cell was built for the study using finite element analysis (FEA) method. 3D-Hashin and Stassi failure criteria were respectively selected for the yarn and the pure matrix, and coded in a subroutine in Abaqus finite element solver to study the individual constituents damages. From the different numerical studies, the failure mechanisms were observed to change with the braiding angle. The meso-scale computed results were also seen to agree closely with experimental and simulation results computed using a micro-mechanics failure approach. [ABSTRACT FROM AUTHOR]

Lateral-torsional buckling (LTB) is an ultimate limit state that can occur in the hogging moment regions of continuous composite steel and concrete beams. This limit state is characterised by the buckling of the steel profile compressed flange (bottom flange) about the minor axis, together with a distortion of the steel profile web. The European Standard EN 1994-1-1:2004 provides an approximate procedure for LTB design that is applicable to continuous composite beams, but only those with a plane web steel profile. The most important step of this procedure is the determination of the elastic critical moment. In this paper, a finite element analysis (FEA) model was developed using the software ANSYS to determine the elastic critical moments of continuous composite steel and concrete beams with corrugated sinusoidal-web steel profiles, which were evaluated against numerical data from the literature. Ultimately, a study involving 45 models was conducted based on FEA modelling, and a procedure for predicting the elastic critical moment of composite beams with sinusoidal-web steel profiles was proposed. [ABSTRACT FROM AUTHOR]

Under the framework of the commemoration of Nuevo Leon Heritage (March 8th, 2015) arises the idea of bringing back to life a beloved Norteño artist, Eulalio Gonzalez “Piporro”, singing in company of real artists and musicians in an event called “Mujer Neoleonesa: Musa y Creadora” which also had the intention to recognize the Nuevo Leon women's talent and dedication by presenting numbers authored and performed by renowned women. Using a variation of so-called Pepper's ghost effect, nowadays known as ‘holographic projection’, Computer Graphics technologies and chroma key filming techniques, a three-dimensional computer-generated face of Piporro was successfully superimposed onto a professional imitator's body. After only two weeks of planning and almost six weeks of production, three functions were presented the day of the event in which Piporro was able to perform once again in front of his fans who were delighted by hearing the “Corrido a Monterrey’, a song that was never performed by Piporro in his life. [ABSTRACT FROM AUTHOR]

In cutting and packing problems, Dual Feasible Functions (DFFs) represent a well established tool for deriving high quality lower bounds in very short times. A well-known DFF lower bounding approach consists of using DFFs to rapidly generate feasible values for the dual variables of a Column Generation (CG) program ( i.e. , of an extended formulation commonly associated to CG). This paper presents a method for extending this approach to problems such as Capacitated p - Median , Distance Constrained General Routing and related variants ( e.g. , Capacitated Arc-Routing ). In contrast to classical DFF bounds for cutting and packing, our extended DFF bounds deal with non-equal column costs , i.e. , the column costs (primal objective function coefficients) have a more complex structure depending on some sums of distances. The general idea is to use a (reformulated) classical CG model in which a feasible dual solution is expressed as a linear combination of both DFF and non-DFF terms. In fact, one of the proposed approaches (the mixed CG-DFF bound for Capacitated p - Median in Section 2.2 ) still requires optimizing a restricted CG program , but with fewer variables and easier pricing sub-problems. The most refined bound version is the “ DFF warm-started CG ” from Section 2.2.2 : it takes dual constraints generated while solving the above restricted CG program are re-uses them to warm-start a full CG phase. In the best cases, this can yield a speed-up between 2 and 3 relative to the pure CG. We present numerical experiments on Capacitated p - Median , Capacitated Arc-Routing (with fixed costs) and Distance Constrained Arc Routing ; the comparisons with the CG bound concern both the quality and the running time. [ABSTRACT FROM AUTHOR]

The approach presented in this paper applies fuzzy set theory to the evaluation of audio signals segmentation with high resolution and accuracy. The method is based on comparing automatically found boundaries with ground truth . Hence, the method is more accurate and able to grasp the evaluation problem in a way more similar to the evaluation conducted by a human being. Traditional methods often fail on grading segmentation algorithms, particularly those of relatively similar qualities. We define a fuzzy membership function that measures the degree to which the segments obtained by an automatic procedure are similar to the results of a correct segmentation. To identify a pair of equivalent segments, we set a fuzzy alignment function that points the pairs of segments obtained by an automatic segmentation with the corresponding segments from a correct segmentation. Speech segmentation is an example where the presented approach was applied. [ABSTRACT FROM AUTHOR]

We present a declarative debugger for sequential Erlang programs. The tool is started when a program produces some unexpected result, and proceeds asking questions to the user about the correctness of some subcomputations until an erroneous program function is found. Then, the user can refine the granularity by zooming in the function, checking the values bound to variables and the if/case/try-catch branches taken during the execution. We show by means of an extensive benchmark that the result is a usable, scalable tool that complements already existing debugging tools such as the Erlang tracer and Dialyzer. Since the technique is based on a formal calculus, we are able to prove the soundness and completeness of the approach. [ABSTRACT FROM AUTHOR]

Given a function from Z n to itself one can determine its polynomial representability by using Kempner function. In this paper we present an alternative characterization of polynomial functions over Z n by constructing a generating set for the Z n -module of polynomial functions. This characterization results in an algorithm that is faster on average in deciding polynomial representability. We also extend the characterization to functions in several variables. [ABSTRACT FROM AUTHOR]

We study the problem of trimming visibly pushdown automata ( VPA ). We first describe a polynomial time procedure which, given a visibly pushdown automaton that accepts only well-nested words, returns an equivalent visibly pushdown automaton that is trimmed. We then show how this procedure can be lifted to the setting of arbitrary VPA . Furthermore, we present a way of building, given a VPA , an equivalent VPA which is both deterministic and trimmed. Last, our trimming procedures can be applied to weighted VPA . [ABSTRACT FROM AUTHOR]

Multi-methods are functions whose calls at runtime are resolved depending on the dynamic types of more than one argument. They are useful for common programming problems. However, while many languages provide different mechanisms to implement them in one way or another, there is still, to the best of our knowledge, no library or language feature that handles them in a general and flexible way. In this paper, we present the EVL (Extended Virtual function Library) framework which provides a set of classes in C++ aiming at solving this problem. The EVL framework provides a generalization of virtual function dispatch through the number of dimensions and the selection of the function to invoke using a so-called Function Comparison Operator . Our library provides both symmetric and asymmetric dispatch algorithms that can be refined by the programmer to include criteria other than class inheritance. For instance, the EVL framework provides multi-methods with predicate dispatch by defining a dedicated FCO based not only on the dynamic types of the arguments but also on their values. This flexibility greatly helps to resolve ambiguities without having to define new functions. Our multi-methods also unify dispatch tables and caching by introducing cache strategies for which the implementation is a balance between memory and speed. To define multi-methods in C++, we implement a non-intrusive reflection library providing fast dynamic casting and supporting dynamic class loading. Our multi-methods are policy-based class templates that support virtual but not repeated inheritance. They check the type compatibility of functions at compile-time, preserve type-safety and resolve function calls at runtime by invoking the cache or updating it by computing the selected function for the requested tuple of types. By default, our multi-methods handle dispatch errors at runtime by throwing exceptions but an error-code strategy can be set up by defining a dedicated policy class. Performance of our multi-methods is comparable with that of standard virtual functions when configured with fast cache. [ABSTRACT FROM AUTHOR]

A simplified method for generating slope deformation hazard curve that takes into account the variations of input parameters is presented in this paper. The main assumption in the new approach is that the occurrence of peak slope deformation is Poisson׳s process. The procedure is based on logic tree analysis, commercial software and routines programmed by the authors for generating sets of input files, and forming slope performance curve. The methodology was applied to a real landslide in order to demonstrate the advantages and limitations of the proposed approach. The results of the analysis showed the influence of the certain input factors on sliding displacement as well as the advantages of employing continuum mechanics approach. [ABSTRACT FROM AUTHOR]

In this paper, progressive debonding of the blade root joint of a 660 kW wind turbine under cyclic loading is studied. Progressive fatigue debonding of this adhesive joint is analyzed using cohesive zone interface modeling. The blade is subjected to various loadings such as aerodynamic forces, centrifugal force, weight, and force due to the change in wind direction. A user defined material subroutine is used in the ANSYS finite element code to predict both the crack (debonding) initiation and propagation in the adhesive joint under variable amplitude fatigue loading. The required material properties such as the critical strain energy release rate and the Paris law constants are characterized experimentally through the well-known tests for different fracture modes: double cantilever beam (DCB) for mode-I (opening mode), end notch flexure (ENF) for mode-II (shearing mode) and mixed mode bending (MMB) for mixed mode conditions. These tests are performed for composite to aluminum interfaces, which are representative of the actual material used in the manufacturing of the wind turbines blades. The experiments are performed under both static and fatigue loading. The predicted initiation and progressive damage results from numerical analyses are verified by experimental results for simple joints. It is illustrate that the maximum length of the deboned area after a typical overloading is about 8% of the total height of the root joint and during the fatigue loadings it would increase to about 40% of the total height after 1 month normal operation. The developed numerical analysis tool can then be used to predict the debonding initiation and propagation in the root joint of the wind turbine blades. [ABSTRACT FROM AUTHOR]

This paper introduces a novel technique to decide the satisfiability of formulae written in the language of Linear Temporal Logic with both future and past operators and atomic formulae belonging to constraint system D (CLTLB( D ) for short). The technique is based on the concept of bounded satisfiability , and hinges on an encoding of CLTLB( D ) formulae into QF-EU D , the theory of quantifier-free equality and uninterpreted functions combined with D . Similarly to standard LTL, where bounded model-checking and SAT-solvers can be used as an alternative to automata-theoretic approaches to model-checking, our approach allows users to solve the satisfiability problem for CLTLB( D ) formulae through SMT-solving techniques, rather than by checking the emptiness of the language of a suitable automaton. The technique is effective, and it has been implemented in our Z ot formal verification tool. [ABSTRACT FROM AUTHOR]

We present a novel hybrid algorithm for Bayesian network structure learning, called H2PC. It first reconstructs the skeleton of a Bayesian network and then performs a Bayesian-scoring greedy hill-climbing search to orient the edges. The algorithm is based on divide-and-conquer constraint-based subroutines to learn the local structure around a target variable. We conduct two series of experimental comparisons of H2PC against Max-Min Hill-Climbing (MMHC), which is currently the most powerful state-of-the-art algorithm for Bayesian network structure learning. First, we use eight well-known Bayesian network benchmarks with various data sizes to assess the quality of the learned structure returned by the algorithms. Our extensive experiments show that H2PC outperforms MMHC in terms of goodness of fit to new data and quality of the network structure with respect to the true dependence structure of the data. Second, we investigate H2PC's ability to solve the multi-label learning problem. We provide theoretical results to characterize and identify graphically the so-called minimal label powersets that appear as irreducible factors in the joint distribution under the faithfulness condition. The multi-label learning problem is then decomposed into a series of multi-class classification problems, where each multi-class variable encodes a label powerset. H2PC is shown to compare favorably to MMHC in terms of global classification accuracy over ten multi-label data sets covering different application domains. Overall, our experiments support the conclusions that local structural learning with H2PC in the form of local neighborhood induction is a theoretically well-motivated and empirically effective learning framework that is well suited to multi-label learning. The source code (in R) of H2PC as well as all data sets used for the empirical tests are publicly available. [ABSTRACT FROM AUTHOR]

In this paper the complex thermomechanical behaviour at the tool – workmaterial interface in machining has been analysed. The contact behaviour is formulated in the frame of a Lagrangian Finite Element approach. The thermomechanical laws governing the tool – workmaterial interface in machining have been implemented via the VUINTER subroutine of ABAQUS/Explicit FE code. Using this interface, velocity dependent heat partition coefficient of the frictional heat has been implemented. Numerical results (calculated heat flux transmitted into the tool and cutting force) have been compared to experimental ones for different cutting conditions, which are in good agreement. It is shown that different couples of the heat partition and heat transfer coefficients can give the same heat flux transmitted in the tool. In addition, with the new developed VUINTER subroutine, it is possible to implement any mathematical model governing the friction and heat exchange for simulations of complex contact behaviours. [ABSTRACT FROM AUTHOR]

Abstract: This paper studies the fault detection process (FDP) and fault correction process (FCP) with the incorporation of testing effort function and imperfect debugging. In order to ensure high reliability, it is essential for software to undergo a testing phase, during which faults can be detected and corrected by debuggers. The testing resource allocation during this phase, which is usually depicted by the testing effort function, considerably influences not only the fault detection rate but also the time to correct a detected fault. In addition, testing is usually far from perfect such that new faults may be introduced. In this paper, we first show how to incorporate testing effort function and fault introduction into FDP and then develop FCP as delayed FDP with a correction effort. Various specific paired FDP and FCP models are obtained based on different assumptions of fault introduction and correction effort. An illustrative example is presented. The optimal release policy under different criteria is also discussed. [Copyright &y& Elsevier]

Abstract: Classical ballet requires dancers to exercise significant muscle control and strength both while stationary and when moving. Following the Royal Academy of Dance (RAD) syllabus, 8 male and 27 female dancers (aged 20.2 + 1.9 yr) in a full-time university undergraduate dance training program were asked to stand in first position for 10seconds and then perform 10 repeats of a demi-plié exercise to a counted rhythm. Accelerometer records from the wrist, sacrum, knee and ankle were compared with the numerical scores from a professional dance instructor. The sacrum mounted sensor detected lateral tilts of the torso in dances with lower scores (Spearman's rank correlation coefficient r = -0.64, p < 0.005). The RMS acceleration amplitude of wrist mounted sensor was linearly correlated to the movement scores (Spearman's rank correlation coefficient r = 0.63, p < 0.005). The application of sacrum and wrist mounted sensors for biofeedback during dance training is a realistic, low cost option. [Copyright &y& Elsevier]

Abstract: Fibre-reinforced polymer-based composite materials fail due to a wide variety of interacting damage mechanisms, which require complex constitutive models in order to develop Finite Element (FE) predictive analysis. In this paper, a constitutive behaviour model based on Continuum Damage Mechanics (CDM) is proposed for the simulation of fabric-reinforced composites. The model uses simplified loading functions in order to minimise the computational time required to obtain the numerical solution. To reduce the influence of mesh refinement on the numerical solutions, the Crack Band Model (CBM) algorithm is implemented. In this way, the energy dissipated at each point in the material is regularized for the different damage mechanisms. This newly-formulated constitutive model is implemented by means of a user-defined material subroutine in Abaqus/Explicit FE code. The model is validated by comparing the results of FE predictions with experimental data from open hole specimens, under quasi-static tensile loading conditions. A good correlation between the numerical and experimental results is achieved when using a bilinear cohesive law, for different combinations of hole diameter and specimen width. [Copyright &y& Elsevier]

Abstract: Hesitant fuzzy set (HFS) is used to deal with the situations in which the decision makers hesitate among several values to assess an indicator, alternative, variable, etc. Recently, the multi-criteria decision making (MCDM) problems with hesitant fuzzy information have received increasing attentions and many corresponding MCDM methods have also been developed, but none of them can be used to solve the MCDM problems in case of considering the decision maker’s psychological behavior. In this study, we extend the TODIM (an acronym in Portuguese of interactive and multi-criteria decision making) method, which is based on prospect theory and can effectively capture the decision maker’s psychological behavior, to solve this type of problems under hesitant fuzzy environment. Firstly, we develop two novel measured functions for comparing the magnitude of hesitant fuzzy elements and interval-valued hesitant fuzzy elements, which are more reasonable and effective compared with the existing measured functions. Then, we calculate the dominance degree of each alternative related to the others based on novel measured functions and distance measures. By aggregating these dominance degrees, we can further obtain the overall value of each alternative and whereby rank the alternatives. Finally, a decision making problem that concerns the evaluation and ranking of the service quality among domestic airlines is used to illustrate the validity and applicability of the proposed method. [Copyright &y& Elsevier]

Abstract: Multi-tenant database is a new database solution which is significant for Software as a service (SaaS) and Big Data applications in the context of cloud computing paradigm. This multi-tenant database has significant design challenges to develop a solution that ensures a high level of data quality, accessibility, and manageability for the tenants using this database. In this paper, we propose a multi-tenant data management service called Elastic Extension Tables Schema Handler Service (EETSHS), which is based on a multi-tenant database schema called Elastic Extension Tables (EET). This data management service satisfies tenants’ different business requirements, by creating, managing, organizing, and administratinglarge volumes of structured, semi-structured, and unstructured data. Furthermore, it combines traditional relational data with virtual relational data in a single database schema and allows tenants to manage this data by calling functions from this service. We present algorithms for frequently used functions of this service, and perform several experiments to measure the feasibility and effectiveness of managing multi-tenant data using these functions. We report experimental results of query execution timesfor managing tenants’ virtual and traditional relational data showing that EET schema is a good candidate for the management of multi-tenant data for SaaS and Big Data applications. [Copyright &y& Elsevier]

Abstract: The introduction of auto-tuning techniques in linear algebra routines using hybrid combinations of multiple CPU and GPU computing resources is analyzed. Basic models of the execution time and information obtained during the installation of the routines are used to optimize the execution time with a balanced assignation of the work to the computing components in the system. The study is carried out with a basic kernel (matrix-matrix multiplication) and a higher level routine (LU factorization) using GPUs and the host multicore processor. Satisfactory results are obtained, with experimental execution times close to the lowest experimentally achievable. [Copyright &y& Elsevier]

In this paper we show that a p ( ⩾ 2 ) -center location problem in general networks can be transformed to the well-known Kleeʼs measure problem (Overmars and Yap, 1991) [15] . This results in a significantly improved algorithm for the continuous case with running time O ( m p n p / 2 2 log ⁎ n log n ) for p ⩾ 3 , where n is the number of vertices, m is the number of edges, and log ⁎ n denotes the iterated logarithm of n (Cormen et al., 2001) [10] . For p = 2 , the running time of the improved algorithm is O ( m 2 n log 2 n ) . The previous best result for the problem is O ( m p n p α ( n ) log n ) where α ( n ) is the inverse Ackermann function (Tamir, 1988) [17] . When the underlying network is a partial k -tree ( k fixed), we exploit the geometry inherent in the problem and propose a two-level tree decomposition data structure which can be used to efficiently solve discrete p -center problems for small values of p . [ABSTRACT FROM AUTHOR]

A fundamental and well-studied problem in computational geometry is range searching , where the goal is to preprocess a set, S , of geometric objects (e.g., points in the plane) so that the subset S ′ ⊆ S that is contained in a query range (e.g., an axes-parallel rectangle) can be reported efficiently. However, in many situations, what is of interest is to generate a more informative “summary” of the output, obtained by applying a suitable aggregation function on S ′ . Examples of such aggregation functions include count , sum , min , max , mean , median , mode , and top-k that are usually computed on a set of weights defined suitably on the objects. Such range-aggregate query problems have been the subject of much recent research in both the database and the computational geometry communities. In this paper, we further generalize this line of work by considering aggregation functions on point-sets that measure the extent or “spread” of the objects in the retrieved set S ′ . The functions considered here include closest pair , diameter , and width . The challenge here is that these aggregation functions (unlike, say, count ) are not efficiently decomposable in the sense that the answer to S ′ cannot be inferred easily from answers to subsets that induce a partition of S ′ . Nevertheless, we have been able to obtain space- and query-time-efficient solutions to several such problems including: closest pair queries with axes-parallel rectangles on point sets in the plane and on random point-sets in R d ( d ⩾ 2 ), closest pair queries with disks on random point-sets in the plane, diameter queries on point-sets in the plane, and guaranteed-quality approximations for diameter and width queries in the plane. Our results are based on a combination of geometric techniques, including multilevel range trees, Voronoi Diagrams, Euclidean Minimum Spanning Trees, sparse representations of candidate outputs, and proofs of (expected) upper bounds on the sizes of such representations. [ABSTRACT FROM AUTHOR]

Abstract: The paper aims to investigate plastic limit pressure of spherical vessels of nonlinear combined isotropic/kinematic hardening materials. The Armstrong-Frederick kinematic hardening model is adopted and the Voce hardening law is incorporated for isotropic hardening behavior. Analytically, we extend sequential limit analysis to deal with combined isotropic/kinematic hardening materials. Further, exact solutions of plastic limit pressure were developed analytically by conducting both static and kinematic limit analysis. The onset of instability was also derived and solved iteratively by Newton's method. Numerically, elastic–plastic analysis is also performed by the commercial finite-element code ABAQUS incorporated with the user subroutine UMAT implemented with user materials of combined hardening. Finally, the problem formulation and the solution derivations presented here are validated by a very good agreement between the numerical results of exact solutions and the results of elastic–plastic finite-element analysis by ABAQUS. [Copyright &y& Elsevier]

Abstract: In this paper, feature combinations associated with the most commonly used time functions related to the signing process are analyzed, in order to provide some insight on their actual discriminative power for online signature verification. A consistency factor is defined to quantify the discriminative power of these different feature combinations. A fixed-length representation of the time functions associated with the signatures, based on Legendre polynomials series expansions, is proposed. The expansion coefficients in these series are used as features to model the signatures. Two different signature styles, namely, Western and Chinese, from a publicly available Signature Database are considered to evaluate the performance of the verification system. Two state-of-the-art classifiers, namely, Support Vector Machines and Random Forests are used in the verification experiments. Error rates comparable to the ones reported over the same signature datasets in a recent Signature Verification Competition, show the potential of the proposed approach. The experimental results, also show that there is a good correlation between the consistency factor and the verification errors, suggesting that consistency values could be used to select the optimal feature combination. [Copyright &y& Elsevier]