Improving Neural Networks for Mechanism Kinematic Chain Isomorphism Identification

Detection of isomorphism among kinematic chains is essential in mechanical design, but difficult and computationally expensive. It has been shown that both traditional methods and previously presented neural networks still have a lot to be desired in aspects such as simplifying procedure of identification and adapting automatic computation. Therefore, a new algorithm based on a competitive Hopfield network is developed for automatic computation in the kinematic chain isomorphism problem. The neural approach provides directly interpretable solutions and does not demand tuning of parameters. We have tested the algorithm by solving problems reported in the recent mechanical literature. Simulation results show the effectiveness of the network that rapidly identifies isomorphic kinematic chains.     

Carbonitriding of Clay: Relation between the Weight Loss and Crystalline Phases during Reaction

β'-Sialons are phases of the Si-Al-O-N system. The carbonitriding of clays and kaolins is a preparation method. The reaction mechanism of clay carbonitriding is verified by means of the relation among crystalline phases formed and the weight loss produced in the samples during the reaction. Two clays were previously mixed with carbon black and pressed into pellets, flowing through N₂ atmosphere, at five temperatures within the range 1335–1427°C. The phases formed (XRD)—mullite, SiC, β'A-sialon, and oxynitrides—were related to the weight loss measured in the pellet independently of reaction temperature and time. The β'A-sialon and the nitrogenous phases were formed from SiC and mullite. A z value decrease for β'A-sialon was observed during reaction progression.     

Comparisons of Urban Travel Forecasts Prepared with the Sequential Procedure and a Combined Model

Detailed analyses and comparisons of urban travel forecasts prepared by applying the state-of-practice sequential procedure and the solution of a combined network equilibrium model are presented. The sequential procedure for solving the trip distribution, mode choice and assignment problems with feedback is the current practice in most transportation planning agencies, although its important limitations are well known. The solution of a combined model, in contrast, results from a single mathematical formulation, which ensures a well-converged and consistent result. Using a real network, several methods for solving the sequential procedure with feedback are compared to the solution of the combined model ESTRAUS. The results of these methods are shown to have various levels of instability. The paper concludes with a call for a new paradigm of travel forecasting practice based on an internally consistent model formulation that can be solved to a level of precision suitable for comparing alternative scenarios.     

A Tale of Two Dams: The Impact of Reservoir Management on Rural Depopulation in Central Spain

In rural areas, depopulation is mainly due to a lack of economic and employment opportunities. In this context, the reservoirs already built can be a source of socioeconomic development based on tourism and outdoor leisure activities. The condition for this development to materialize is that reservoir management considers these activities. In Central Spain, a process of rural depopulation has been generated in the municipalities around the reservoirs at the Upper Tagus River, as water management allows water transfers from the Tagus to the Segura River without taking into account regulations that prioritize and protect donor basin users. Through the comparison of reservoir water management and demographic data of two rural areas close to the reservoirs, this article reveals the direct relationship between reservoir management that enables recreational uses with its consequent socioeconomic development and the maintenance of the population in the territory. Consequently, reservoir water management based on the socioeconomic development of reservoir banks is necessary and a priority over transfers to another basin.

     

Retraction of “Using ergonomic digital human modeling in evaluation of workplace design and prevention of workrelated musculoskeletal disorders onboard small fishing vessel”

The following article from Human Factors and Ergonomics in Manufacturing & Service Industries, “Using ergonomic digital human modeling in evaluation of workplace design and prevention of workrelated musculoskeletal disorders onboard small fishing vessel,” by Enrique Álvarez‐Casado, Bing Zhang, Sonia Tello Sandoval and Mondelo Pedro, published online on October 11, 2011 in Wiley Online Library ( www.onlinelibrary.wiley.com ), has been retracted by agreement between the authors, the journal Editors‐in‐Chief, Waldemar Karwowski and Gavriel Salvendy, and Publisher Wiley Periodicals, Inc. The retraction has been agreed as these articles were mistakenly published after being rejected.     

A comparative study between dynamic adapted PSO and VNS for the vehicle routing problem with dynamic requests

Combinatorial optimization problems are usually modeled in a static fashion. In this kind of problems, all data are known in advance, i.e. before the optimization process has started. However, in practice, many problems are dynamic, and change while the optimization is in progress. For example, in the dynamic vehicle routing problem (DVRP), new orders arrive when the working day plan is in progress. In this case, routes must be reconfigured dynamically while executing the current simulation. The DVRP is an extension of a conventional routing problem, its main interest being the connection to many real word applications (repair services, courier mail services, dial-a-ride services, etc.). In this article, a DVRP is examined, and solving methods based on particle swarm optimization and variable neighborhood search paradigms are proposed. The performance of both approaches is evaluated using a new set of benchmarks that we introduce here as well as existing benchmarks in the literature. Finally, we measure the behavior of both methods in terms of dynamic adaptation.     

Solving differential equations with Fourier series and Evolution Strategies

A novel mesh-free approach for solving differential equations based on Evolution Strategies (ESs) is presented. Any structure is assumed in the equations making the process general and suitable for linear and nonlinear ordinary and partial differential equations (ODEs and PDEs), as well as systems of ordinary differential equations (SODEs). Candidate solutions are expressed as partial sums of Fourier series. Taking advantage of the decreasing absolute value of the harmonic coefficients with the harmonic order, several ES steps are performed. Harmonic coefficients are taken into account one by one starting with the lower order ones. Experimental results are reported on several problems extracted from the literature to illustrate the potential of the proposed approach. Two cases (an initial value problem and a boundary condition problem) have been solved using numerical methods and a quantitative comparative is performed. In terms of accuracy and storing requirements the proposed approach outperforms the numerical algorithm.     

Participatory Modeling Workshops in a Water-Stressed Basin Result in Gains in Modeling Capacity but Reveal Disparity in Water Resources Management Priorities

Participatory modeling workshops were held in Sonora, México, with the goal of developing water resources management strategies in a water-stressed basin. A model of the water resources system, consisting of watershed hydrology, water resources infrastructure, and groundwater models, was developed deliberatively in the workshops, along with scenarios of future climate and development. Participants used the final version of the water resources systems model to select management strategies. The performance of the strategies was based on the reliability of meeting current and future demands at a daily time scale over a year’s period. Pre- and post-workshop surveys were developed and administered. The survey questions focused on evaluation of participants’ modeling capacity and the utility and accuracy of the models. The selected water resources strategies and the associated, expected reliability varied widely among participants. Most participants could be clustered into three groups with roughly equal numbers of participants that varied in terms of reliance on expanding infrastructure vs. demand modification; expectations of reliability; and perceptions of social, environmental, and economic impacts. The wide range of strategies chosen and associated reliabilities indicate that there is a substantial degree of uncertainty in how future water resources decisions could be made in the region. The pre- and post-survey results indicate that participants believed their modeling abilities increased and beliefs in the utility of models increased as a result of the workshops.     

Effects of physical refining on contents of waxes and fatty alcohols of refined olive oil

Changes in the contents of waxes and fatty alcohols during deodorization/physical refining of bleached olive oil were studied. Experiments were carried out with 1.85% acidity oil, which was physically refined in a discontinuous deodorizer of 250-kg maximum capacity using nitrogen as stripping gas instead of steam. The variables studied were load and temperature of oil in the deodorizer as well as N₂ flow. Analyses of waxes and alcohols were carried out at different operation times. The maximum content of wax was always observed when the oil reached the deodorization temperature. The variation in the wax content depended on temperature and N₂ flow. Wax decomposition started and continued during the operating time, and a progressive decrease, which was pronounced between 3 and 4 h, was observed. Small changes in waxes were observed between 4 and 5 h. Total content of fatty alcohols diminished throughout the operating time, and changes did not depend on the variables studied.     

A complete and efficient CUDA-sharing solution for HPC clusters

In this paper we detail the key features, architectural design, and implementation of rCUDA, an advanced framework to enable remote and transparent GPGPU acceleration in HPC clusters. rCUDA allows decoupling GPUs from nodes, forming pools of shared accelerators, which brings enhanced flexibility to cluster configurations. This opens the door to configurations with fewer accelerators than nodes, as well as permits a single node to exploit the whole set of GPUs installed in the cluster. In our proposal, CUDA applications can seamlessly interact with any GPU in the cluster, independently of its physical location. Thus, GPUs can be either distributed among compute nodes or concentrated in dedicated GPGPU servers, depending on the cluster administrator’s policy. This proposal leads to savings not only in space but also in energy, acquisition, and maintenance costs. The performance evaluation in this paper with a series of benchmarks and a production application clearly demonstrates the viability of this proposal. Concretely, experiments with the matrix–matrix product reveal excellent performance compared with regular executions on the local GPU; on a much more complex application, the GPU-accelerated LAMMPS, we attain up to 11x speedup employing 8 remote accelerators from a single node with respect to a 12-core CPU-only execution. GPGPU service interaction in compute nodes, remote acceleration in dedicated GPGPU servers, and data transfer performance of similar GPU virtualization frameworks are also evaluated.