An approach to emulating separable graphs

A technique foremulating multicomputer interconnection networks that are based onseparable graphs (graphs having bounded degree and sublinear multicolor recursive bisectors) is presented. Efficient emulations among interconnection networks are necessary for porting programs designed for one network to another.Emulations are formalized asgraph embeddings, where the nodes (processors) of theguest graph (emulated network) are assigned to nodes of thehost graph (emulator), while the edges (communication links) of the guest are routed via paths in the host. The communication slowdown in an emulation depens on thedilation (length of the longest routing path) and thecongestion (number of paths that contend for a host edge) of the embedding. Theexpansion of the embedding (the ratio of the sizes of the host to guest) determines the inefficiency of processor utilization. Cell trees are introduced as interconnection networks whose special communication properties enable them to serve as intermediate devices in these emulations. Nodes in cell trees are organized into equinumerous parts calledcells; the cells are labeled by nodes of a complete binary tree. Communication in cell trees is restricted to two specific and distinct primitives:cell communication is confined within cells, whiletransfer communication occurs between adjacent cells. Rather than solved directly, the emulation problem for the original guest-host pair is decomposed into two independent parts: emulating the guest by the cell tree, and emulating the cell tree by the host.In emulations of separable graphs by cell trees, the node assignment that ensures small dilation is derived from the separator-based decomposition of guest graphs. The congestion-free edge routing is achieved by coordinatingglobal andlocal phases, which are based on two characteristic cell-tree communication primitives.The technique is instantiated by emulating cell trees on specific host graphs. Withshuffle-like hypercube-derivative networks as hosts new constant-expansion emulations are obtained that have both dilation and congestion logarithmic in the size of the multicolor bisector of guest graphs. These emulations are the first such to have optimal (up to constants)congestion; they provide the firstoptimal algorithm for emulating arbitrary separable graphs on shuffle-like networks. The application of the technique tohypercubes as hosts also produces optimal emulations that differ from those previously known by having smaller expansion constants.This research was supported in part by NSF Grants CCR-88-12567 and CCR-90-13184, and by the University of Massachusetts Graduate School Fellowship for the academic year 1991-92. A preliminary version of this paper was presented at the 3rd ACM Symposium on Parallel Algorithms and Architectures, July 22–24, 1991, in Hilton Head, South Carolina, USA.     

Relationship between the Undrained Shear Strength, Water Content, and Mineralogical Properties of Fine-Grained Soils

The relationship between the undrained shear strength of fine-grained soils and the water content can be described with a nonlinear function in which the type of soil is determined by two parameters. It is well known that these parameters depend mainly on the mineral compositions of soils; these relationships, however, have not yet been investigated. The findings described in this paper define those mineralogical properties of soils which determine the values of both parameters. Experimentally obtained results suggest that the parameters primarily depend on the size of the clay minerals, their quantity in soil composition, and the interlayer water quantity in the expanding clay minerals. As this dependence is well defined, the parameters, and thus the undrained shear strength at different water content, can be defined from knowledge of these mineralogical soil properties.     

A flexible graphical user interface for embedding heterogeneousneural network simulators

A graphical user interface (GUI) for heterogeneous neural network simulators proposed in this article is intended to be of use both for the novice and for the experienced neural network user. For the novice, it provides an easy-to-use neural network simulation package that insulates the user from the requirements of knowing the simulator implementation details or the configuration file syntax. For the experienced neural network professional it provides an interface that is easily extensible to include any additional neural network simulator in its binary form. To satisfy both academic and personal computer environments, the GUI has been developed by using the free TCL/TK software package, available on workstations running Unix and on PCs running the free Linux operating system. Although the GUI and the embedded simulators have been successfully tested both in neural network research and training programs, a more extensive testing in undergraduate and graduate level classes is in progress     

Information maximization and independent component analysis; is there a difference?

This article provides a detailed and rigorous analysis of the two commonly used methods for redundancy reduction: linear independent component analysis (ICA) posed as a direct minimization of a suitably chosen redundancy measure and information maximization (InfoMax) of a continuous stochastic signal transmitted through an appropriate nonlinear network. The article shows analytically that ICA based on the Kullback-Leibler information as a redundancy measure and InfoMax lead to the same solution if the parameterization of the output nonlinear functions in the latter method is sufficiently rich. Furthermore, this work discusses the alternative redundancy measures not based on the Kullback-Leibler information distance. The practical issues of applying ICA and InfoMax are also discussed and illustrated on the problem of extracting statistically independent factors from a linear, pixel-by-pixel mixture of images.     

Chromosomal location of the genetic determinants for bacteriocins produced by Lactobacillus gasseri K7

The production of similar or even identical bacteriocins by different lactic acid bacteria is not a rare event. To take advantage of this finding, genetic determinants of the Lactobacillus K7 bacteriocins were tested for putative homologies with previously described bacteriocins of the Lactobacillus acidophilus group through polymerase chain reaction (PCR). Among specific primer pairs of seven known bacteriocins, derived from their respective sequences, only acidocin LF221 A and B primers amplified fragments in chromosomal DNA of K7 strain that revealed strong similarity over small regions of LF221 bacteriocins. Treatment of Lactobacillus K7 with ethidium bromide and mitomycin C was ineffective in generating non-bacteriocinogenic derivatives and had no impact on plasmid loss either. Classification studies elucidated Lactobacillus K7 as a member of the Lactobacillus gasseri species.     

An adaptive partitioning approach for mining discriminant regions in 3D image data

Mining discriminative spatial patterns in image data is an emerging subject of interest in medical imaging, meteorology, engineering, biology, and other fields. In this paper, we propose a novel approach for detecting spatial regions that are highly discriminative among different classes of three dimensional (3D) image data. The main idea of our approach is to treat the initial 3D image as a hyper-rectangle and search for discriminative regions by adaptively partitioning the space into progressively smaller hyper-rectangles (sub-regions). We use statistical information about each hyper-rectangle to guide the selectivity of the partitioning. A hyper-rectangle is partitioned only if its attribute cannot adequately discriminate among the distinct labeled classes, and it is sufficiently large for further splitting. To evaluate the discriminative power of the attributes corresponding to the detected regions, we performed classification experiments on artificial and real datasets. Our results show that the proposed method outperforms major competitors, achieving 30% and 15% better classification accuracy on synthetic and real data respectively while reducing by two orders of magnitude the number of statistical tests required by voxel-based approaches.     

Gas–liquid mass transfer in periodically operated trickle-bed reactors: Influence of the liquid-phase physical properties and flow modulation

The influence of periodic operation on trickle-bed reactor (TBR) hydrodynamics and gas–liquid mass transfer was investigated. Two-phase pressure drop, dynamic liquid hold-up and gas–liquid mass transfer coefficient (k_La) were determined at various liquid flow rates and for different modes of liquid flow variation (increasing and decreasing liquid flow rate). The results reveal the considerable influence of type of liquid flow rate modulation on k_La values (deviations of up to 80% in k_La). Simulation studies on gas-limited reaction in a periodically operated TBR indicate that an enhancement in conversion of about 14% can be expected from an appropriate selection of the operating mode, thus clearly demonstrating the quantitative process intensification feasible through increased gas–liquid mass transfer.     

Modelling of unsteady-state hydrodynamics in periodically operated trickle-bed reactors:Influence of the liquid-phase physical properties

Process intensification using periodic operation of trickle bed reactors (TBRs) is still a long way from replacing conventional steady-state operation in industrial use, despite the numerous benefits described in the literature. Complex interactions between hydrodynamics, mass transfer and reaction phenomena make the design of periodically operated TBRs an almost insurmountable challenge. The development of hydrodynamic models able to provide reliable quantitative predictions of flow behaviour and possessing a sound physical basis, is an essential prerequisite for obtaining the necessary insights into this complexity. In this work, the two-phase pressure drop and dynamic liquid hold-up during max/min and on/off periodical operation were predicted using a model based on the relative permeability concept. In order to demonstrate the utility of this approach, a systematic investigation of the quantitative influence of the liquid-phase physical properties was carried out. The results obtained show that the modelling of the hydrodynamics in periodically operated TBRs using the relative permeability concept is feasible. By selecting suitable permeability parameters, unsteady-state hydrodynamics for different periodic operating modes can be predicted successfully.