A novel methodology to predict urban traffic congestion with ensemble learning

Urban traffic congestion prediction is a very hot topic due to the environmental and economical impacts that currently implies. In this sense, to be able to predict bottlenecks and to provide alternatives to the circulation of vehicles becomes an essential task for traffic management. A novel methodology, based on ensembles of machine learning algorithms, is proposed to predict traffic congestion in this paper. In particular, a set of seven algorithms of machine learning has been selected to prove their effectiveness in the traffic congestion prediction. Since all the seven algorithms are able to address supervised classification, the methodology has been developed to be used as a binary classification problem. Thus, collected data from sensors located at the Spanish city of Seville are analyzed and models reaching up to 83 % are generated.     

Image blur and energy broadening effects in XPEEM

We report image blurring and energy broadening effects in energy-filtered XPEEM when illuminating the specimen with soft X-rays at high flux densities. With a flux of 2×10¹³ photons/s, the lateral resolution in XPEEM imaging with either core level or secondary electrons is degraded to more than 50 nm. Fermi level broadening up to several hundred meV and spectral shift to higher kinetic energies are also systematically observed. Simple considerations suggest that these artifacts result from Boersch and Loeffler effects, and that the electron-electron interactions are strongest in the initial part of the microscope optical path. Implications for aberration corrected instruments are discussed.     

Managing Citizen Profiles in the Domain of e-Government: The cPortfolio Project

The provision of support for holistic operations in the scope of a horizontal digital administration requires the fulfillment of a number of previous steps that guarantee the viability of services in the domain. One of these tasks is the proper management of documents. Documents are a key element of any democratic administration and their digital management is a clear pre-requisite for the arrival of digital government. This article tackles how this service can be provided using the support of semantics as a technological cornerstone. The implementation of such a tool is made through the so-called cPortfolio. This platform is deeply discussed and details about its design and implementation are provided. This system is designed to manage both the personal information from the citizen and the documents they possess. Tests on the prototype showed interesting features regarding the simplicity of use and the interoperability support provided to third party agents.     

A multi-start tabu search method for a single-machine scheduling problem with periodic maintenance and sequence-dependent set-up times

In this paper we study a problem of sequencing jobs in a machine with programmed preventive maintenance and sequence-dependent set-up times. The problem combines two NP-hard problems, so we propose a heuristic method for solving it, which hybridizes multi-start strategies with Tabu Search. We compare our method with the only published metaheuristic algorithm for this problem on a set of 420 instances. The comparison favors the method developed in this work, showing that is able to find high quality solutions in very short computational times.     

A multiobjective approach based on artificial bee colony for the static routing and wavelength assignment problem

Nowadays, the most promising technology for designing optical networks is the wavelength division multiplexing. This technique divides the huge bandwidth of an optical fiber link into different wavelengths, providing different available channels per link. However, a problem comes up when it is necessary to interconnect a set of traffic demands. This problem is known as routing and wavelength assignment problem, and due to its complexity (NP-hard problem) it is very suitable for being solved using evolutionary computation. The selected heuristics is the artificial bee colony algorithm, an heuristics based on the behavior of honeybee foraging for nectar. Therefore, we have applied multiobjective optimization to solve the static routing and wavelength assignment problem, and adapted this algorithm to the multiobjective context. New results have been obtained that significantly improve those published in previous researches.     

Use of Ontologies as Representation Support of Workflows Oriented to Administrative Management

One of the applications of workflow systems is the management of administrative processes characterized by the transmission of information elements among users of an organization. Tasks contained in these processes are carried out by users responsible for confirming, modifying or adding information throughout. These processes need to be defined in workflow management systems in which all the elements are perfectly identified and are easily adaptable to changes that may arise in the sequences of tasks, in the users involved or in the data transmitted from one task to another. For this kind of processes is easier to reuse those represented in ontologies. On one hand, existing ontologies for representing some domain elements can be reused. At the same time, ontologies have an excellent expressive capacity to define tasks, their relationships and the flow control among them with precision. This paper proposes a complete model, together with the necessary software tools, for tackling this issue.

Empirical Comparisons of X‐bar Charts when Control Limits are Estimated

A control chart is a very common tool used to monitor the quality of business processes. An estimator of the process variability is generally considered to obtain the control limits of a chart when parameters of the process are unknown. Assuming Monte Carlo simulations, this paper first compares the efficiency of the various estimators of the process variability. Two empirical measures used to analyze the performance of control charts are defined. Results derived from various empirical studies reveal the existence of a linear relationship between the performance of the various estimators of the process variability and the performance of charts. The various Monte Carlo simulations are conducted under the assumption that the process is in both situations of in‐control and out‐of‐control. Copyright © 2015 John Wiley & Sons, Ltd.