SACOC: A spectral-based ACO clustering algorithm

The application of ACO-based algorithms in data mining is growing over the last few years and several supervised and unsupervised learning algorithms have been developed using this bio-inspired approach. Most recent works concerning unsupervised learning have been focused on clustering, where ACO-based techniques have showed a great potential. At the same time, new clustering techniques that seek the continuity of data, specially focused on spectral-based approaches in opposition to classical centroid-based approaches, have attracted an increasing research interest–an area still under study by ACO clustering techniques. This work presents a hybrid spectral-based ACO clustering algorithm inspired by the ACO Clustering (ACOC) algorithm. The proposed approach combines ACOC with the spectral Laplacian to generate a new search space for the algorithm in order to obtain more promising solutions. The new algorithm, called SACOC, has been compared against well-known algorithms (K-means and Spectral Clustering) and with ACOC. The experiments measure the accuracy of the algorithm for both synthetic datasets and real-world datasets extracted from the UCI Machine Learning Repository

NASA technology utilization program: The small business market

Technology transfer programs were studied to determine how they might be more useful to the small business community. The status, needs, and technology use patterns of small firms are reported. Small business problems and failures are considered. Innovation, capitalization, R and D, and market share problems are discussed. Pocket, captive, and new markets are summarized. Small manufacturers and technology acquisition are discussed, covering external and internal sources, and NASA technology. Small business and the technology utilization program are discussed, covering publications and industrial applications centers. Observations and recommendations include small business market development and contracting, and NASA management technology

MACOC: a medoid-based ACO clustering algorithm

The application of ACO-based algorithms in data mining is growing over the last few years and several supervised and unsupervised learning algorithms have been developed using this bio-inspired approach. Most recent works concerning unsupervised learning have been focused on clustering, showing great potential of ACO-based techniques. This work presents an ACO-based clustering algorithm inspired by the ACO Clustering (ACOC) algorithm. The proposed approach restructures ACOC from a centroid-based technique to a medoid-based technique, where the properties of the search space are not necessarily known. Instead, it only relies on the information about the distances amongst data. The new algorithm, called MACOC, has been compared against well-known algorithms (K-means and Partition Around Medoids) and with ACOC. The experiments measure the accuracy of the algorithm for both synthetic datasets and real-world datasets extracted from the UCI Machine Learning Repository

Exponentially growing solutions in homogeneous Rayleigh-Benard convection

It is shown that homogeneous Rayleigh-Benard flow, i.e., Rayleigh-Benard turbulence with periodic boundary conditions in all directions and a volume forcing of the temperature field by a mean gradient, has a family of exact, exponentially growing, separable solutions of the full non-linear system of equations. These solutions are clearly manifest in numerical simulations above a computable critical value of the Rayleigh number. In our numerical simulations they are subject to secondary numerical noise and resolution dependent instabilities that limit their growth to produce statistically steady turbulent transport.Comment: 4 pages, 3 figures, to be published in Phys. Rev. E - rapid communication

Office paper recyclability: first recycling

Paper recyclability implies in the paper capacity to be recycled maintaining its properties to the maximum. Four commercial papers from Argentina and Brazil were studied, including three eucalyptus kraft (A, B, C) and one sugar cane bagasse soda-AQ (D), all with different bleaching processes. Their physical and chemical properties and a first laboratory recycling were evaluated. A refining of the pulp with a PFI mill, applying two energy levels at two different intensities - measured by number of revolutions and load - was accomplished to reach the same °SR (between 30 and 40, approximately). The refining energy and the yield were registered in each case. The properties of laboratory handsheets, and the aging to 24, 48, 72 and 144 hours were evaluated. The statistical analysis of the results indicates that the properties of the initial eucalyptus papers were similar, whereas they were generally inferior in the case of the bagasse paper. The bagasse and eucalyptus papers presented similar initial whiteness, but the first one had a higher reversion than the others. Once repulped, the eucalyptus papers A, B and C required, respectively, 4, 7 and 10 times greater energy than D, to obtain the same °SR. In all cases, the required energy to achieve the same °SR is slightly greater with the smaller refining intensity. The physical properties of the handsheets from the first recycle of paper D were, in general, lower. Among eucalyptus papers, B showed a slightly higher resistance and C, a slightly lower one. The mechanical properties of pulp sheets A, and D to a lesser extension, were more affected by the refining intensity than the rest, indicating a higher sensitivity of the fibers. The whiteness of the sheets of pulp B is lower than the rest. Opacity and light scattering coefficient of the sheets of pulp C were much higher than those of the other pulps.Fil: Benitez, Julieta Beatriz. Universidad Nacional de Misiones; ArgentinaFil: Koga, Mariza E. T.. Instituto de Pesquisas Tecnológicas de São Paulo (ipt); BrasilFil: Otero D'Almeida, Maria L.. Instituto de Pesquisas Tecnológicas de São Paulo (ipt); BrasilFil: Felissia, Fernando Esteban. Universidad Nacional de Misiones; ArgentinaFil: Park, Song W.. Escola Politecnica, Universidad de Sao Paulo (usp); BrasilFil: Area, Maria Cristina. Universidad Nacional de Misiones; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentin

Quantum size effects in Pb islands on Cu(111): Electronic-structure calculations

The appearance of "magic" heights of Pb islands grown on Cu(111) is studied by self-consistent electronic structure calculations. The Cu(111) substrate is modeled with a one-dimensional pseudopotential reproducing the essential features, i.e. the band gap and the work function, of the Cu band structure in the [111] direction. Pb islands are presented as stabilized jellium overlayers. The experimental eigenenergies of the quantum well states confined in the Pb overlayer are well reproduced. The total energy oscillates as a continuous function of the overlayer thickness reflecting the electronic shell structure. The energies for completed Pb monolayers show a modulated oscillatory pattern reminiscent of the super-shell structure of clusters and nanowires. The energy minima correlate remarkably well with the measured most probable heights of Pb islands. The proper modeling of the substrate is crucial to set the quantitative agreement.Comment: 4 pages, 4 figures. Submitte