Fast calculation of α-stable density functions based on off-line precomputations. Application to ML parameter estimation

This paper proposes a fast algorithm to compute arbitrary α-stable PDFs and CDFs. The procedure is based on off-line precomputations of α-stable values on a grid of points in the α–β parameter space, as well as in a set of abscissa points. The grid is built by defining two quality measures and assuring that minimum values for these measures are reached on those points. Results indicate that the method here proposed is substantially faster than directly evaluating the standard expressions proposed by Nolan [1]. The proposed algorithm makes it possible to efficiently use estimation methods based on the evaluation of the PDF, such as the Maximum Likelihood (ML) principle, which gives asymptotically unbiased and efficient estimates. To this end, an ML-based estimation algorithm is provided as well.     

XDist： an effective XML keyword search system with re-ranking model based on keyword distribution

Keyword search enables web users to easily access XML data without understanding the complex data schemas. However, the native ambiguity of keyword search makes it arduous to select qualified relevant results matching keywords. To solve this problem, researchers have made much effort on establishing ranking models distinguishing relevant and irrelevant passages, such as the highly cited TF＊IDF and BM25. However, these statistic based ranking methods mostly consider term frequency, inverse document frequency and length as ranking factors, ignoring the distribution and connection information between different keywords. Hence, these widely used ranking methods are powerless on recognizing irrelevant results when they are with high term frequency, indicating a performance limitation. In this paper, a new searching system XDist is accordingly proposed to attack the problems aforementioned. In XDist, we firstly use the semantic query model maximal lowest common ancestor （MAXLCA） to recognize the returned results of a given query, and then these candidate results are ranked by BM25. Especially, XDist re-ranks the top several results by a combined distribution measurement （CDM） which considers four measure criterions： term proximity, intersection of keyword classes, degree of integration among keywords and quantity variance of keywords. The weights of the four measures in CDM are trained by a listwise learning to optimize method. The experimental results on the evaluation platform of INEX show that the re-ranking method CDM can effectively improve the performance of the baseline BM25 by 22% under iP[0.01] and 18% under MAiP. Also the semantic model MAXLCA and the search engine XDist perform the best in their respective related fields.     

Stress distributions in an elastic body due to molecular interactions considering one-dimensional periodic material distribution based on Mindlin’s solution

A method to calculate the stress distributions in a semi-infinite elastic body caused by molecular interactions has been established based on Mindlin’s solution. A molecular interaction force derived from the Lennard-Jones potential considering a one-dimensional periodic material distribution in the in-plane direction, i.e., x-direction, was used as a concentrated force in Mindlin’s solution. The stresses acting on the (100) and (001) surfaces (σ_x, σ_z, and τ_zx) for the distribution of two materials were calculated as a typical example of a periodic material distribution. The stress distributions were shown by color maps and the basic characteristics of the stress distribution, especially the effects of the surface distance, were quantitatively clarified. The asymptotic values of σ_x, σ_z, and τ_zx at the position far from the surface were analytically derived. Those of σ_x and σ_z had the same value, depending on the surface distance, while that of τ_zx was always zero. This difference comes from the existence of a non-fluctuation contribution.

     

Multi-sensor fusion approach with fault detection and exclusion based on the Kullback–Leibler Divergence: Application on collaborative multi-robot system

This paper presents a multi-sensor fusion strategy able to detect the spurious sensors data that must be eliminated from the fusion procedure. The used estimator is the informational form of the Kalman Filter (KF) namely Information Filter (IF). In order to detect the erroneous sensors measurements, the Kullback–Leibler Divergence (KLD) between the a priori and a posteriori distributions of the IF is computed. It is generated from two tests: One acts on the means and the other deals with the covariance matrices. Optimal thresholding method based on a Kullback–Leibler Criterion (KLC) is developed and discussed in order to replace classical approaches that fix heuristically the false alarm probability.Multi-robot systems became one of the major fields of study in the indoor environment where the environmental monitoring and the response to crisis must be ensured. Consequently, the robots required to know precisely their positions and orientations in order to successfully perform their mission. Fault detection and exclusion (FDE) play a crucial role in enhancing the integrity of localization of the multi-robot team. The main contributions of this paper are: - developing a new method of sensors data fusion that tackle the erroneous data issues, - developing a Kullback–Leibler based criterion for the threshold optimization, - Validation with real experimental data from a group of robots.     

SFP—a new parameterization based on shape functions for optimal material selection: application to conventional composite plies

In this paper, a new parameterization of the mechanical properties is proposed for the optimal selection of materials. Recent parameterization schemes from multi-phase topology optimization (i.e. Discrete Material Optimization—DMO) are compared to this novel approach in the selection of conventional laminates including only 0°, − 45°, 45° and 90° plies. In the new parameterization the material stiffness is computed as a weighted sum of the candidate material properties, and the weights are based on the shape functions of a quadrangular first order finite element. Each vertex of the reference quadrangle then represents a candidate ply. Compared to DMO, this method requires fewer design variables, since the four pseudo-densities representing the presence or the absence of a given candidate ply in DMO are now replaced, in the weights, by two design variables, which are the two natural coordinates of the reference quadrangular element sufficient to identify each of the four vertices. Another advantage of the new parameterization scheme is to penalize, in a more convenient way, the intermediate values of the design variables, possibly avoiding any blending of materials at the solution. Three simple numerical applications with in-plane loadings are proposed and solved in order to demonstrate that the new approach is an interesting alternative to DMO, able to select the optimal orientations and to combine the material distribution with optimal orientation problems.     

Constructing exponential estimates in compartmental systems with distributed delays: an approach based on the hale–lunel inequality

This paper presents a method for constructing exponential estimates in a compartmental system with distributed delays on the basis of the Hale–Lunel inequality and its application. The practical importance of this study is illustrated by a pharmacokinetic model from anesthesiology.     

Design of reduced search space strategy based on integration of Nelder–Mead method and pattern search algorithm with application to economic load dispatch problem

This paper presents a novel hybrid technique for the solution of economic load dispatch problem with valve point loading effect using Nelder–Mead (NM) simplex method and pattern search (PS) algorithm. Strength of globalized NM optimization algorithm has been employed to explore the search space for near optimal solution, and PS algorithm is used in combination with a search space reduction strategy, incorporating the principles of selection and stochastic reproduction, to fine-tune the result. The proposed technique has been applied to three different systems having 3, 13 and 40 generating units to demonstrate the application for small to large load dispatch set-up. The efficacy of the design scheme is established from comparison of the results with the state-of-the-art solvers, and it is found that the proposed scheme gives the best result in terms of mean cost while the average computational time is less than most of the reported methods.

     

On the belief in avatars: what on earth have the aesthetics of the Byzantine icons to do with the avatar in social technologies?

This article looks at the digital portrait used in the form of avatars in various online worlds and communication networks. It describes an ongoing modal shift from an ontological understanding of the portrait towards the portrait as performative acting.

In accordance with the Western semiotic divide between representational fiction and material reality proper, the avatar-portrait is often still described as a representation that depicts the subject on the basis of a conceptual segregation between the living subject and the portrait. But the avatar-portrait functions as embodiment, thereby fulfilling a mainly performative purpose that triggers the participant's belief in the other's avatar.

The paper looks at Eastern iconology, where the iconic portrait is an energetic transmitter in which the depiction and the depicted converge in the belief in the realness of the picture. Key concepts such as prototype, archetype and inverse perspective are discussed and applied to the art piece Can You See Me Now? by Blast Theory.     

A majority-density approach to developing testing and diagnostic systems with the cooperation of multiple experts based on an enhanced concept–effect relationship model

In the recent years, diagnosing students’ learning problems after testing and providing learning suggestions for them are an important research issue. Many studies have been conducted to develop a method for analyzing learning barriers of students such that helpful learning suggestions or guidance can be provided based on the analysis results. In this paper, we present a new procedure for integrating test item–concept relationship opinions based on majority density of multiple experts in order to enhance a concept–effect relationship model used for generating personalized feedback. It provides a useful and practical way to decrease inconsistencies in the weighting criteria of multiple experts and to enhance the entire learning-diagnosis procedure for developing testing and diagnostic systems.     

A decision support system based on fuzzy reasoning and AHP–FPP for the ecodesign of products: Application to footwear as case study

The design stage represents one of the most critic steps for product development. Here, a great number of considerations have to be borne in mind, e.g., technical, functional, aesthetic or economic criteria. More recently, the increasing concerns on environmental aspects have added complexity to the process, known as ecodesign. In this respect, a framework to integrate the criteria provided by quantitative environmental indicators has been proposed on the basis of Fuzzy Preference Programming method features and fuzzy logic reasoning. As a result, an integrated Ecodesign Index (EcoInd) is obtained. This idea enables the decision making at process and product level taking into account different indicators at a time. The ecodesign of children's footwear was taken as case study and an ecodesign tool (decision support system) that included the estimation of environmental indicators and their integration was developed. Different models of shoes were analyzed to identify the most environmentally friendly design and to test the tool. In this case, the Ecological Footprint and two Environmental Risk Assessment indicators, namely Hazard Quotient and Cancer Risk, were selected as relevant environmental indicators and they were computed from data provided by a shoes manufacturer. Then, these indicators were integrated in the ecodesign tool and the EcoInd values were appraised for the children's footwear models analyzed. According to these figures, they were ranked as Red Leather > White Leather > White Synthetic > Pink Synthetic, from best to worst.