Software tools for micro-analysis of programs

The paper proposes and describes several tools enabling their user to estimate the efficiency of Pascal or C-like programs. The approach consists of generating symbolic formulas expressing the efficiency of the programs being analyzed. The formulas are applicable to a variety of compiler-machine configurations. The actual numeric values of the variables in the symbolic formula are determined using linear programming techniques. The proposed approach reduces considerably the amount of benchmarking needed to analyze programs. Several examples are presented showing the applicability of the tools. The effort necessary to implement them is considerably reduced by the combined usage of Prolog and a symbolic formula manipulation package (Maple).     

Generalized topology design of structures with a buckling load criterion

Material based models for topology optimization of linear elastic solids with a low volume constraint generate very slender structures composed mainly of bars and beam elements. For this type of structure the value of the buckling critical load becomes one of the most important design criteria and so its control is very important for meaningful practical designs. This paper tries to address this problem, presenting an approach to introduce the possibility of critical load control into the topology optimization model.Using the material based formulation for topology design of structures, the problem of optimal structural reinforcement for a critical load criterion is formulated. The stability problem is conveniently reduced to a linearized eigenvalue problem assuming only material effective properties and macroscopic instability modes. The respective optimality criteria are presented by introducing the Lagrangian associated with the optimization problem. Based on this Lagrangian a first-order method is used as a basis for the numerical update scheme. Two numerical examples to validate the developments are presented and analysed.     

Incremental inconsistency detection with low memory overhead

Ensuring models’ consistency is a key concern when using a model‐based development approach. Therefore, model inconsistency detection has received significant attention over the last years. To be useful, inconsistency detection has to be sound, efficient, and scalable. Incremental detection is one way to achieve efficiency in the presence of large models. In most of the existing approaches, incrementalization is carried out at the expense of the memory consumption that becomes proportional to the model size and the number of consistency rules. In this paper, we propose a new incremental inconsistency detection approach that only consumes a small and model size‐independent amount of memory. It will therefore scale better to projects using large models and many consistency rules. Copyright © 2012 John Wiley & Sons, Ltd.     

A team algorithm for robust stability analysis and control design of uncertain time‐varying linear systems using piecewise quadratic Lyapunov functions

A team algorithm based on piecewise quadratic simultaneous Lyapunov functions for robust stability analysis and control design of uncertain time‐varying linear systems is introduced. The objective is to use robust stability criteria that are less conservative than the usual quadratic stability criterion. The use of piecewise quadratic Lyapunov functions leads to a non‐convex optimization problem, which is decomposed into a convex subproblem in a selected subset of decision variables, and a lower‐dimensional non‐convex subproblem in the remaining decision variables. A team algorithm that combines genetic algorithms (GA) for the non‐convex subproblem and interior‐point methods for the solution of linear matrix inequalities (LMI), which form the convex subproblem, is proposed. Numerical examples are given, showing the advantages of the proposed method. Copyright © 2001 John Wiley & Sons, Ltd.     

Effect of different surface processing protocols in three-dimensional images for rapid prototyping

The aim of the study was to evaluate the accuracy of virtual three-dimensional reconstructions of human dry mandibles, produced with different surface processing protocols. Three-dimensional images were built from computed tomography scans of 10 dry mandibles, and the surface was smoothed, refined, or both, generating 30 different images. Linear measurements from anatomical landmarks were calculated and compared with the corresponding measurements of the original dry mandible (gold standard). The results showed no differences between the models that were just refined or just smoothed (p > 0.05), when compared to the gold standard. When these two tools were applied together, there was a statistically significant difference (p < 0.01). In conclusion, the application of a single processing tool (smoothing or refinement) in the virtual models does not affect the anatomical measures. However, the simultaneous application of both tools increases the differences between the reconstructions and the original anatomical parts.     

The fully informed particle swarm: simpler, maybe better

The canonical particle swarm algorithm is a new approach to optimization, drawing inspiration from group behavior and the establishment of social norms. It is gaining popularity, especially because of the speed of convergence and the fact that it is easy to use. However, we feel that each individual is not simply influenced by the best performer among his neighbors. We, thus, decided to make the individuals "fully informed." The results are very promising, as informed individuals seem to find better solutions in all the benchmark functions.     

Artificial neural network model for ground vibration amplitudes prediction due to light railway traffic in urban areas

The growth of density and circulation speed of railway transportation systems in urban areas increases the importance of the research issues of the produced environmental impacts. This study presents a field data analysis, obtained during monitoring campaigns of ground vibration, due to light railway traffic in urban areas, based on the artificial neural network (ANN) approach, using quantitative and qualitative predictors. Different ANN-based models, using those predictors, were evaluated/trained and validated. Using several criteria, including those that measures the possibility of ANN overfitting (RR²) and complexity (AIC), the best ANN model was successfully obtained for Lisbon area. This model, with 16 input elements (quantitative and qualitative predictors), 2 neurons on the hidden layer with a hyperbolic tangent sigmoid transfer function, and 1 neuron on the output layer considering a linear transfer function, has 0.9720 for the coefficient of determination and 0.5293 for the sum squared error.

     

Is It Possible to Retain Customer Loyalty When a Service Has Failed?

This article aims to analyze the impact of recovery on loyalty in the context of a service chain characterized by the e‐quality–perceived value–loyalty relationship. A sample of 91 out of 1,201 respondents claimed to have had service problems with an online travel agency website. A causal model to test relationships was performed using structural equations modeling, and it was found that data fit with the proposed model. The really important point to retaining customers is quality. It is not so clear that the recovery effort might affect loyalty. Our findings underpin some previous stream of literature confirming that recovery does not always affect loyalty. Although the literature has not reached a consensus in this topic, we add new elements in this debate.     

Are electronic white canes better than traditional canes? A comparative study with blind and blindfolded participants

Visually impaired individuals often rely on assistive technologies such as white canes for independent navigation. Many electronic enhancements to the traditional white cane have been proposed. However, only a few of these proof-of-concept technologies have been tested with authentic users, as most studies rely on blindfolded non-visually impaired participants or no testing with participants at all. Experiments involving blind users are usually not contrasted with the traditional white cane. This study set out to compare an ultrasound-based electronic cane with a traditional white cane. Moreover, we also compared the performance of a group of visually impaired participants (N = 10) with a group of blindfolded participants without visual impairments (N = 31). The results show that walking speed with the electronic cane is significantly slower compared to the traditional white cane. Moreover, the results show that the performance of the participants without visual impairments is significantly slower than for the visually impaired participants. No significant differences in obstacle detection rates were observed across participant groups and device types for obstacles on the ground, while 79% of the hanging obstacles were detected by the electronic cane. The results of this study thus suggest that electronic canes present only one advantage over the traditional cane, namely in its ability to detect hanging obstacles, at least without prolonged practice. Next, blindfolded participants are insufficient substitutes for blind participants who are expert cane users. The implication of this study is that research into digital white cane enhancements should include blind participants. These participants should be followed over time in longitudinal experiments to document if practice will lead to improvements that surpass the performance achieved with traditional canes.