Multiphase Machines and Drives-Revisited

Although the concept of a multiphase drive system dates back to the middle of the 20th century, the initial pace of development was rather slow, as witnessed by the first two surveys of the area published in the beginning of this century. However, considerably new developments have resulted in the last decade of the 20th century and the beginning of this century, leading to an authoritative survey of the asymmetrical six-phase drive control and subsequently of the review of the complete area. This also initiated the organization and subsequent publication of the first IEEE Transactions on Industrial Electronics "Special Section on Multiphase Machines and Drives" in May 2008, which commenced with another survey paper, and that contained 12 original research papers. Since the publication of this Special Section in May 2008, the level of interest and pace of developments in the area have further accelerated and substantial new knowledge has been generatedwith an ever-increasing number of published research papers and reported new industrial applications. Such a trend has been emphasized in a recent paper. It therefore seemed appropriate to revisit the area and organize this Special Section as a sequel to the first one. The call for the Special Section papers resulted in 51 submissions, almost twice as many as the total back in 2008, thus confirming a substantial growth of the area. Indeed, the amount of new knowledge acquired since the publication of the first Special Section in 2008 has meant that it was not possible to provide a complete and thorough survey of the field in a single review paper

A multi-objective genetic graph-based clustering algorithm with memory optimization

Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. H. D. Menéndez, D. F. Barrero, and D. Camacho, "A multi-objective genetic graph-based clustering algorithm with memory optimization", in 2013 IEEE Congress on Evolutionary Computation (CEC), 2013, pp. 3174 - 3181Clustering is one of the most versatile tools for data analysis. Over the last few years, clustering that seeks the continuity of data (in opposition to classical centroid-based approaches) has attracted an increasing research interest. It is a challenging problem with a remarkable practical interest. The most popular continuity clustering method is the Spectral Clustering algorithm, which is based on graph cut: it initially generates a Similarity Graph using a distance measure and then uses its Graph Spectrum to find the best cut. Memory consuption is a serious limitation in that algorithm: The Similarity Graph representation usually requires a very large matrix with a high memory cost. This work proposes a new algorithm, based on a previous implementation named Genetic Graph-based Clustering (GGC), that improves the memory usage while maintaining the quality of the solution. The new algorithm, called Multi-Objective Genetic Graph-based Clustering (MOGGC), uses an evolutionary approach introducing a Multi-Objective Genetic Algorithm to manage a reduced version of the Similarity Graph. The experimental validation shows that MOGGC increases the memory efficiency, maintaining and improving the GGC results in the synthetic and real datasets used in the experiments. An experimental comparison with several classical clustering methods (EM, SC and K-means) has been included to show the efficiency of the proposed algorithm.This work has been partly supported by: Spanish Ministry of Science and Education under project TIN2010-19872

Intercellular cancer collisions generate an ejected crystal comet tail effect with fractal interface embryoid body reassembly transformation

We have documented self-assembled geometric triangular chiral crystal complexes (GTCHC) and a framework of collagen vascular invariant geometric attractors in cancer tissues. This article shows how this system evolves in time. These structures are incorporated together and evolve in different ways. When the geometric core is stable, and the tissue architecture collapses, fragmented components emerge, which reveal a hidden interior identifying how each molecule is reassembled into the original mold, using one common connection, ie, a fractal self-similarity that guided the system from the beginning. GTCHC complexes generate ejected crystal comet tail effects and produce strange helicity states that arise in the form of spin domain interactions. As the crystal growth vibration stage progresses, biofractal echo images converge in a master-built construction of embryoid bodies with enolase-selective immunopositivity in relation to clusters of triangular chiral cell organization. In our electro-optic collision model, we were able to predict and replicate all the characteristics of this complex geometry that connects a physical phenomenon with the signal patterns that generate biologic chaos. Intrinsically, fractal geometry makes spatial correction errors embrace the chaotic system in a way that permits new structures to emerge, and as a result, an ordered self-assembly of embryoid bodies with neural differentiation at the final stage of cancer development is a predictable process. We hope that further investigation of these structures will lead not only to a new way of thinking about physics and biology, but also to a rewarding area in cancer research

Improved targeting through collaborative decision-making and brain computer interfaces

This paper reports a first step toward a brain-computer interface (BCI) for collaborative targeting. Specifically, we explore, from a broad perspective, how the collaboration of a group of people can increase the performance on a simple target identification task. To this end, we requested a group of people to identify the location and color of a sequence of targets appearing on the screen, and measured the time and the accuracy of the response. The individual results are compared to a collective identification result determined by simple majority voting, with random choice in case of drawn. The results are promising, as the identification becomes significantly more reliable even with this simple voting, and with a small number of people (either odd or even) involved in the decision. In addition, the paper briefly analyzes the role of brain-computer interfaces in collaborative targeting, extending the targeting task by using a BCI instead of a mechanical response

Confidence intervals of success rates in evolutionary computation

This is the author's version of the work. It is posted here for your personal use. Not for redistribution. The definitive Version of Record was published in Proceedings of the 12th annual conference on Genetic and evolutionary computation , http://dx.doi.org/10.1145/1830483.1830657Success Rate (SR) is a statistic straightforward to use and interpret, however a number of non-trivial statistical issues arises when it is examinated in detail. We address some of those issues, providing evidence that suggests that SR follows a binomial density function, therefore its statistical properties are independent of the flavour of the Evolutionary Algorithm (EA) and its domain. It is fully described by the SR and the number of runs. Moreover, the binomial distribution is a well known statistical distribution with a large corpus of tools available that can be used in the context of EC research. One of those tools, confidence intervals (CIs), is studie

Synthesis of racemic and chiral albicanol, albicanyl acetate and cyclozonarone: cytotoxic activity of ent-cyclozonarone

The total synthesis of racemic cyclozonarone ((±)-3) was achieved from E,E-farnesol (4) in an eight-step sequence in 6.6% overall yield. Albicanol ((±)-1) and its acetate ((±)-2) are intermediates. A similar sequence starting from natural (-)-drimenol (5) gave (+)-albicanol (1) and (+)-cyclozonarone (3) (42% and 11% yield, respectively). The cytotoxic activity of (+)-cyclozonarone was assayed and showed some selectivity towards MS-1 (mice endothelial cells).A síntese completa da mistura racêmica do cyclozonarone ((±)-3), foi obtida a partir do E,E-farnesol (4) em uma seqüência de oito passos com um rendimento geral de 6,6%. O albicanol ((±)-1) e seu acetato ((±)-2) são intermediários. Uma seqüência inicial, similar a partir do produto natural (-)-drimenol (5), produziu o(+)-albicanol (1) e o(+)-cyclozonarone (3) com 42% e 11%, respectivamente. A atividade citotóxica do composto(+)-cyclozonarone foi avaliada e mostrou alguma seletividade para MS-1 (células endoteliais de camundongos).Authors are grateful to Dirección de Investigación y Postgrado, Facultad de Química, Pontificia Universidad Católica de Chile, for financial support, to MECESUP grant UCH 0116 de la Red Nacional de Doctorado en Química for HRMS analyses and to Dr. Luis Espinoza for valuable help with spectroscopic assignments

Adapting Searchy to extract data using evolved wrappers

This is the author’s version of a work that was accepted for publication inExpert Systems with Applications: An International Journal. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. A definitive version was subsequently published in Expert Systems with Applications: An International Journal, 39, 3 (2012) DOI: 10.1016/j.eswa.2011.08.168Organizations need diverse information systems to deal with the increasing requirements in information storage and processing, yielding the creation of information islands and therefore an intrinsic difficulty to obtain a global view. Being able to provide such an unified view of the -likely heterogeneous-information available in an organization is a goal that provides added-value to the information systems and has been subject of intense research. In this paper we present an extension of a solution named Searchy, an agent-based mediator system specialized in data extraction and Integration. Through the use of a set of wrappers, it integrates information from arbitrary sources and semantically translates them according to a mediated scheme. Searchy is actually a domain-independent wrapper container that ease wrapper development, providing, for example, semantic mapping. The extension of Searchy proposed in this paper introduces an evolutionary wrapper that is able to evolve wrappers using regular expressions. To achieve this, a Genetic Algorithm (GA) is used to learn a regex able to extract a set of positive samples while rejects a set of negative samples.The authors gratefully acknowledge Mart´ın Knoblauch for his useful suggestions and valuable comments. This work has been partially supported by the Spanish Ministry of Science and Innovation under the projects ABANT (TIN 2010-19872), COMPUBIODIVE (TIN2007-65989) and by Castilla-La Mancha project PEII09-0266-6640

Hybrid Flooding Scheme for Mobile Wireless Networks

A hybrid broadcast scheme for mobile wireless networks is proposed in this letter. The main objective is to combine different flooding schemes in order to solve the broadcast storm issue encountered by the simple flooding scheme. For this purpose, the density of nodes is taken into account using a density metric called expansion metric. In addition, in order to reduce the broken links due to mobility of nodes and increasing dissimilarity among the intermediate nodes, a forwarding zone criterion is included in the proposed schemes. The proposed approaches have been implemented and compared with pure probabilistic flooding, and simple flooding schemes