Sharp-SSL: Selective high-dimensional axis-aligned random projections for semi-supervised learning

We propose a new method for high-dimensional semi-supervised learning problems based on the careful aggregation of the results of a low-dimensional procedure applied to many axis-aligned random projections of the data. Our primary goal is to identify important variables for distinguishing between the classes; existing low-dimensional methods can then be applied for final class assignment. Motivated by a generalized Rayleigh quotient, we score projections according to the traces of the estimated whitened between-class covariance matrices on the projected data. This enables us to assign an importance weight to each variable for a given projection, and to select our signal variables by aggregating these weights over high-scoring projections. Our theory shows that the resulting Sharp-SSL algorithm is able to recover the signal coordinates with high probability when we aggregate over sufficiently many random projections and when the base procedure estimates the whitened between-class covariance matrix sufficiently well. The Gaussian EM algorithm is a natural choice as a base procedure, and we provide a new analysis of its performance in semi-supervised settings that controls the parameter estimation error in terms of the proportion of labeled data in the sample. Numerical results on both simulated data and a real colon tumor dataset support the excellent empirical performance of the method.Comment: 49 pages, 4 figure

Shear and Layer Breathing Modes in Multilayer MoS2

We study by Raman scattering the shear and layer breathing modes in multilayer MoS2. These are identified by polarization measurements and symmetry analysis. Their positions change with the number of layers, with different scaling for odd and even layers. A chain model explains the results, with general applicability to any layered material, and allows one to monitor their thickness

Fuel quality impact analysis for practical implementation of corn COB gasification gas in conventional gas turbine power plants

Practical implementation of alternative fuels in gas turbine facilities is a challenging step towards cleaner and more responsible energy production. Despite numerous technical, economical and legal obstacles, possibilities for partial or complete substitution of fossil fuels are still subject of profound research. From all possible solutions, one with high acceptance is the symbiosis of existing gas turbine technologies and new ways of waste biomass energy utilization through firing or co – firing of biomass gasification gas. Therefore, the practical implementation of corn cob gasification gas with CO2 recirculation in gas turbines is analyzed in this paper. The followed methodology approaches this solution through two different scenarios each with 5 different cases. In the first scenario fuel mass flows are kept constant regardless of the fuel quality change consequence of the corn cob gas share, while in the second scenario fuel volume flows are assumed constant. Fuel quality refers to fuel composition which affects heat capacity, as well as physical and chemical characteristics of fuel. Impact of fuel composition changes on combustion product characteristics was analyzed using CHEMKIN PRO with GRI–Mech 3.0. Finally, fuel quality impacts on a gas turbine power plant performance are analyzed using a numerical model of a physical cycle that enables the simulation of a 3.9 MW experimentally correlated gas turbine. The results show that utilization of corn cob gasification gas is possible through co-firing with natural gas with acceptable values without modification of the fuel system or gas turbine

Model Independent Extraction of ∣Vbc∣|V_{\rm bc}| Without Heavy Quark Symmetry

A new method to extract $|V_{\rm bc}|$ is proposed based on a sum--rule for semileptonic decays of the $B$ meson. The method relies on much weaker assumptions than previous approaches which are based on heavy--quark symmetry. This sum--rule only relies on the assumption that the virtual $c \overline{c}$ pair content of the $B$ meson can be neglected. The extraction of the CKM matrix element also requires that the sum--rule saturates in the kinematically accessible region.Comment: 10 pages revtex3 manuscript. No figures, U. of MD PP #94--086. With our apologies, some innocuous errors corrected and some references added that had been brought to our attentio

Development the conceptual design of knowledge based system for integrated maintenance strategy and operation

YesThe importance of maintenance has escalated significantly by the increasing of automation in manufacturing process. This condition switches traditional maintenance perspective of inevitable cost into the business competitive driver. Consequently, maintenance strategy and operation decision needs to be synchronized to business and manufacturing concerns. This paper shows the development of conceptual design of Knowledge Based System for Integrated Maintenance Strategy and Operation (KBIMSO). The framework of KBIMSO is elaborated to show the process of how the KBIMSO works to reach the maintenance decision. By considering the multi-criteria of maintenance decision making, the KB system embedded with GAP and AHP to support integrated maintenance strategy and operation which is novel in this area. The KBIMSO is useful to review the existing maintenance system and give reasonable recommendation of maintenance decisions in respect to business and manufacturing perspective