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Dynamic rating monitoring is a solution to face challenges in both the operation and the planning of power systems. With thermal monitoring, dynamic overloads of transformers are allowed; however, the thermal model used to predict hot-spot must be capable of ensuring the assessment of insulation life expectancy. Hence, this paper presents an online algorithm to estimate and predict transformers’ rating in order to assess the overload capability during short and long times. The overload factors are computed using estimations of top-oil temperature. The main characteristic of this proposal is that the environmental cooling conditions are considered by the fitting of the parameters of a simple equivalent thermal circuit using an extended Kalman filter during the transformer operation. To validate the implementation of the algorithm, the information provided by typical transformer rating monitoring systems is used. Thus, the performance and effectiveness of the algorithm are verified using field measurement data during the normal operation of two power transformers. [ABSTRACT FROM AUTHOR]

This paper presents the application of the Anisotropic Fast Marching Method to the path planning problem of mobile robots moving in outdoors environments, such as Mars. Considering that at any point on a 3D surface there are two main slopes: the maximum, which is the slope of the gradient, and the minimum, the height map of a terrain can be considered as a tensor filed. Using the Anisotropic Fast Marching Method, the resulting trajectory of the path planning takes the tensor field into account so that the slopes in the trajectory are minimized. Numerical simulations are presented to show the advantage of this method over its isotropic version. Besides, the influence of the anisotropic index and the traversability of the resultant paths are analyzed. [ABSTRACT FROM AUTHOR]

The traditional methodology for defining the ampacity of overhead lines is based on conservative criteria regarding the operating conditions of the line, leading to the so-called static line rating. Although this procedure has been considered satisfactory for decades, it is nowadays sensible to account for more realistic line operating conditions when calculating its dynamic ampacity. Dynamic line rating is a technology used to improve the ampacity of overhead transmission lines based on the assumption that ampacity is not a static value but a function of weather and line's operating conditions. In order to apply this technology, it is necessary to monitor and predict the temperature of the conductor over time by direct or indirect measurements. This paper presents an algorithm to estimate and predict the temperature in overhead line conductors using an Extended Kalman Filter, with the aim of minimizing the mean square error in the current and subsequent states (temperature) of the conductor. The proposed algorithm assumes both actual weather and current intensity flowing along the conductor as control variables. The temperature of the conductor, mechanical tension and sag of the catenary are used as measurements because the common practice is to measure these values with dynamic line rating hardware. The algorithm has been validated by both simulations and measurements. The results of this study conclude that it is possible to implement the algorithm into Dynamic Line Rating systems, leading to a more accurate estimation and prediction of temperature. [ABSTRACT FROM AUTHOR]

This article presents a heuristic to solve instances of the MBSBPP - Multiple Bin-Size Bin Packing Problem. The heuristic is validated by comparison with a commercial tool of high acceptance. A four-step methodology is used: (A) design of the optimization algorithm, (B) selection of test data, (C) calculation of the solution using the Cape Pack? and GrasPacking v1.0 optimization tools, (D) performance validation by comparison, with emphasis in the percentage of use and computational time. The performance of the proposed algorithm is evaluated in experimental cases and in instances associated with delivery orders of a logistic company. The results allow us to conclude that the proposed heuristic has a good performance and can overcome the commercial tool. [ABSTRACT FROM PUBLISHER]

Over the last 25 years, the multiple sequence alignment (MSA) problem has attracted the attention of biologists because it is one of the major techniques used in several areas of computational biology, such as homology searches, genomic annotation, protein structure prediction, gene regulation networks, or functional genomics. This problem implicates the alignment of more than two biological sequences, and is considered as a nondeterministic polynomial time optimization problem. In this paper, we find a number of different approaches for dealing with this biological sequence alignment problem. Basically, we distinguish six main groups: 1) exact methods; 2) progressive methods; 3) consistency-based methods; 4) iterative methods; 5) evolutionary algorithms; and 6) structure-based methods. In this paper, we propose the use of evolutionary computation and multiobjective optimization for solving this bioinformatics problem. A multiobjective version of a memetic metaheuristic is presented: hybrid multiobjective metaheuristics for MSA. In order to prove the effectiveness of the new proposal, we use three structure-based benchmarks created by using empirical data as input. The results obtained by our method are compared with well-known methods published in this paper, concluding that the new approach presents remarkable accuracy when dealing with sets of sequences with a low sequence similarity, the most frequent ones in real world. [ABSTRACT FROM AUTHOR]

Proteins are molecules that form the mass of living beings. These proteins exist in dissociated forms like amino-acids and carry out various biological functions, in fact, almost all body reactions occur with the participation of proteins. This is one of the reasons why the analysis of proteins has become a major issue in biology. In a more concrete way, the identification of conserved patterns in a set of related protein sequences can provide relevant biological information about these protein functions. In this paper, we present a novel algorithm based on teaching learning based optimization (TLBO) combined with a local search function specialized to predict common patterns in sets of protein sequences. This population-based evolutionary algorithm defines a group of individuals (solutions) that enhance their knowledge (quality) by means of different learning stages. Thus, if we correctly adapt it to the biological context of the mentioned problem, we can get an acceptable set of quality solutions. To evaluate the performance of the proposed technique, we have used six instances composed of different related protein sequences obtained from the PROSITE database. As we will see, the designed approach makes good predictions and improves the quality of the solutions found by other well-known biological tools. [ABSTRACT FROM PUBLISHER]

The ISO 50001 is an international standard oriented to the energy management. In the transport sector and in companies where the equipment is mainly combustion engine means, this energy management process is principally oriented to control the vehicle fuel consumption. In this paper, we present a service capable of monitoring how and when the fuel is consumed and offering tools to the fleet responsible to analyze and manage it. The service produces the required information and tools to support the ISO 50001 certification. To evaluate its performance, the service has been deployed in several vehicles of a garbage collector company making possible a reduction in the fuel consumption by approximately 20%. [ABSTRACT FROM PUBLISHER]

The IEEE Communications Society (Com-Soc), as a global organization of Communications professionals, relies heavily on state of the art Information and Communication Technology (ICT). ICT is essential for ComSoc governance and operations, and to host its community and group activities. All ComSoc activities involve participation from volunteers who live on various continents and in different time zones. Therefore, the ICT infrastructure is essential in keeping such a global Society operational. The Communications Society's ICT infrastructure and services are the technological foundation for "ComSoc On-Line." [ABSTRACT FROM PUBLISHER]

he IEEE Communications Society (ComSoc), being geographically diverse, relies heavily on state of the art Information and Communication Technology (ICT) infrastructure and services for its governance, operations, and to host its community and group activities. All ComSoc activities involve participation from volunteers who live on various continents and in different time zones. So ICT infrastructure is essential in keeping such a global Society operational. The Communications Society's ICT infrastructure and services are the technological foundation for our "Communications Society On-Line." [ABSTRACT FROM PUBLISHER]