Pattern-growth based frequent serial episode discovery

Frequent episode discovery is a popular framework for pattern discovery from sequential data. It has found many applications in domains like alarm management in telecommunication networks, fault analysis in the manufacturing plants, predicting user behavior in web click streams and so on. In this paper, we address the discovery of serial episodes. In the episodes context, there have been multiple ways to quantify the frequency of an episode. Most of the current algorithms for episode discovery under various frequencies are apriori-based level-wise methods. These methods essentially perform a breadth-first search of the pattern space. However currently there are no depth-first based methods of pattern discovery in the frequent episode framework under many of the frequency definitions. In this paper, we try to bridge this gap. We provide new depth-first based algorithms for serial episode discovery under non-overlapped and total frequencies. Under non-overlapped frequency, we present algorithms that can take care of span constraint and gap constraint on episode occurrences. Under total frequency we present an algorithm that can handle span constraint. We provide proofs of correctness for the proposed algorithms. We demonstrate the effectiveness of the proposed algorithms by extensive simulations. We also give detailed run-time comparisons with the existing apriori-based methods and illustrate scenarios under which the proposed pattern-growth algorithms perform better than their apriori counterparts. (C) 2013 Elsevier B.V. All rights reserved.

A Phase Transition for the Uniform Distribution in the Pattern Maximum Likelihood Problem

In this paper, we consider the setting of the pattern maximum likelihood (PML) problem studied by Orlitsky et al. We present a well-motivated heuristic algorithm for deciding the question of when the PML distribution of a given pattern is uniform. The algorithm is based on the concept of a ``uniform threshold''. This is a threshold at which the uniform distribution exhibits an interesting phase transition in the PML problem, going from being a local maximum to being a local minimum.

Diffusion pattern in MSi2 and M5Si3 silicides in group VB (M = V, Nb, Ta) and VIB (M = Mo, W) refractory metal-silicon systems

Group VB and VIB M-Si systems are considered to show an interesting pattern in the diffusion of components with the change in atomic number in a particular group (M = V, Nb, Ta or M = Mo, W, respectively). Mainly two phases, MSi2 and M5Si3 are considered for this discussion. Except for Ta-silicides, the activation energy for the integrated diffusion of MSi2 is always lower than M5Si3. In both phases, the relative mobilities measured by the ratio of the tracer diffusion coefficients, , decrease with an increasing atomic number in the given group. If determined at the same homologous temperature, the interdiffusion coefficients increase with the atomic number of the refractory metal in the MSi2 phases and decrease in the M5Si3 ones. This behaviour features the basic changes in the defect concentrations on different sublattices with a change in the atomic number of the refractory components.

Biomimetic molecular organization of naphthalene diimide in the solid state: tunable (chiro-) optical, viscoelastic and nanoscale properties

The interfacing of aromatic molecules with biomolecules to design functional molecular materials is a promising area of research. Intermolecular interactions determine the performance of these materials and therefore, precise control over the molecular organization is necessary to improve functional properties. Herein we describe the tunable biomimetic molecular engineering of a promising n-type organic semiconductor, naphthalene diimide (NDI), in the solid state by introducing minute structural mutations in the form of amino acids with variable Ca-functionality. For the first time we could achieve all four possible crystal packing modes, namely cofacial, brickwork, herringbone and slipped stacks of the NDI system. Furthermore, amino acid conjugated NDIs exhibit ultrasonication induced organogels with tunable visco-elastic and temperature responsive emission properties. The amino acid-NDI conjugates self-assemble into 0D nanospheres and 1D nanofibers in their gel state while the ethylamine-NDI conjugate forms 2D sheets from its solution. Photophysical studies indicated the remarkable influence of molecular ordering on the absorption and fluorescence properties of NDIs. Interestingly, the circular dichroism (CD) and X-ray diffraction (XRD) studies revealed the existence of helical ordering of NDIs in both solution and solid state. The chiral amino acids and their conformations with respect to the central NDI core are found to influence the nature of the helical organization of NDIs. Consequently, the origin of the preferential handedness in the helical organization is attributed to transcription of chiral information from the amino acid to the NDI core. On account of these unique properties, the materials derived from NDI-conjugates might find a wide range of future interdisciplinary applications from materials to biomedicine.

Efficient generation of diffraction-limited multi-sheet pattern for biological imaging

We demonstrate a new technique to generate multiple light-sheets for fluorescence microscopy. This is possible by illuminating the cylindrical lens using multiple copies of Gaussian beams. A diffraction grating placed just before the cylindrical lens splits the incident Gaussian beam into multiple beams traveling at different angles. Subsequently, this gives rise to diffraction-limited light-sheets after the Gaussian beams pass through the combined cylindrical lens-objective sub-system. Direct measurement of field at and around the focus of objective lens shows multi-sheet pattern with an average thickness of 7.5 mu m and inter-sheet separation of 380 mu m. Employing an independent orthogonal detection sub-system, we successfully imaged fluorescently-coated yeast cells (approximate to 4 mu m) encaged in agarose gel-matrix. Such a diffraction-limited sheet-pattern equipped with dedicated detection system may find immediate applications in the field of optical microscopy and fluorescence imaging. (C) 2015 Optical Society of America

Fish Inspired Biomimetic Ionic Polymer-Metal Composite Pectoral Fins Using Labriform Propulsion

In this article, we analyze and design ionic polymer metal composite (IPMC) underwater propulsors inspired from swimming of labriform fishes. The structural model of the IPMC fin accounts for the electromechanical dynamics of the bean in water. A quasi steady blade element model that accounts for unsteady phenomena, such as added mass effects, dynamic stall, and cumulativeWagner effect is used to estimate the hydrodynamic performance. Dynamic characteristics of IPMC actuated flapping fins having the same size as the actual fins of three different fish species, Gomphosus varius, Scarus frenatus, and Sthethojulis trilineata, are analyzed using numerical simulations.

Digital image analysis around isotropic points for photoelastic pattern recognition

Fringe tracking and fringe order assignment have become the central topics of current research in digital photoelasticity. Isotropic points (IPs) appearing in low fringe order zones are often either overlooked or entirely missed in conventional as well as digital photoelasticity. We aim to highlight image processing for characterizing IPs in an isochromatic fringe field. By resorting to a global analytical solution of a circular disk, sensitivity of IPs to small changes in far-field loading on the disk is highlighted. A local theory supplements the global closed-form solutions of three-, four-, and six-point loading configurations of circular disk. The local theoretical concepts developed in this paper are demonstrated through digital image analysis of isochromatics in circular disks subjected to three-and four-point loads. (C) 2015 Society of Photo-Optical Instrumentation Engineers (SPIE)

Pattern-Formation During Self-organization in Three-Phase Eutectic Solidification

Eutectic growth is an interesting example for exploring the topic of pattern-formation in multi-phase systems, where the growth of the phases is coupled with the diffusive transport of one or more components in the melt. While in the case of binary alloys, the number of possibilities are limited (lamellae, rods, labyrinth etc.), their number rapidly increases with the number of components and phases. In this paper, we will investigate pattern formation during three-phase eutectic solidification using a state-of-the art phase-field method based on the grand-canonical density formulation. The major aim of the study is to highlight the role of two properties, which are the volume fraction of the solid phases and the solid-liquid interfacial energies, in the self-organization of the solid phases during directional growth. Thereafter, we will show representative phase-field simulations of a micro-structure in a real alloy (Ag-Al-Cu) using an asymmetric phase diagram as well as interfacial properties.

Pattern formation in thin films of polymer solutions: Theory and simulations

Self-assembly has been recognized as an efficient tool for generating a wide range of functional, chemically, or physically textured surfaces for applications in small scale devices. In this work, we investigate the stability of thin films of polymer solutions. For low concentrations of polymer in the solution, long length scale dewetting patterns are obtained with wavelength approximately few microns. Whereas, for concentrations above a critical value, bimodal dispersion curves are obtained with the dominant wavelength being up to two orders smaller than the usual dewetting length scale. We further show that the short wavelength corresponds to the phase separation in the film resulting in uniformly distributed high and low concentration regions. Interestingly, due to the solvent entropy, at very high concentration values of polymer, a re-entrant behaviour is observed with the dominant length scale now again corresponding to the dewetting wavelength. Thus, we show that the binary films of polymer solutions provide additional control parameters that can be utilized for generating functional textured surfaces for various applications. (C) 2016 AIP Publishing LLC.

Increasing Critical Sensitivity of the Load/Unload Response Ratio before Large Earthquakes with Identified Stress Acclumulation Pattern

The Load/Unload Response Ratio (LURR) method is proposed for short-to-intermediate-term earthquake prediction [Yin, X.C., Chen, X.Z., Song, Z.P., Yin, C., 1995. A New Approach to Earthquake Prediction — The Load/Unload Response Ratio (LURR) Theory, Pure Appl. Geophys., 145, 701–715]. This method is based on measuring the ratio between Benioff strains released during the time periods of loading and unloading, corresponding to the Coulomb Failure Stress change induced by Earth tides on optimally oriented faults. According to the method, the LURR time series usually climb to an anomalously high peak prior to occurrence of a large earthquake. Previous studies have indicated that the size of critical seismogenic region selected for LURR measurements has great influence on the evaluation of LURR. In this study, we replace the circular region usually adopted in LURR practice with an area within which the tectonic stress change would mostly affect the Coulomb stress on a potential seismogenic fault of a future event. The Coulomb stress change before a hypothetical earthquake is calculated based on a simple back-slip dislocation model of the event. This new algorithm, by combining the LURR method with our choice of identified area with increased Coulomb stress, is devised to improve the sensitivity of LURR to measure criticality of stress accumulation before a large earthquake. Retrospective tests of this algorithm on four large earthquakes occurred in California over the last two decades show remarkable enhancement of the LURR precursory anomalies. For some strong events of lesser magnitudes occurred in the same neighborhoods and during the same time periods, significant anomalies are found if circular areas are used, and are not found if increased Coulomb stress areas are used for LURR data selection. The unique feature of this algorithm may provide stronger constraints on forecasts of the size and location of future large events.

Experimental Study of Surface Deformation and Flow Pattern on Buoyant-Thermocapillary Convection

Free surface deformation is one of the most important physical phenomena in fluids with free surface. In the present paper, convection and surface deformation caused by thermocapillary effect in a rectangular cavity were investigated. In ground experiments, the convection was also affected by gravity. The cavity has a horizontal cross section of 52mm×42mm and the thikkness of the liquid layer is 4mm. Temperature difference between two sides of the liquid layer was increased gradually, and the flow in liquid layer will develop from steady to unstable convection. An optical diagnostic system consisting of a revised Michelson interferometer with image processor was developed to study fluid surface deformation in convection, and the displacements of free surface oscillation were determined. PIV technique was adopted to observe the evolution of flow pattern, and the velocity fields were obtained quantitatively. The present experiments demonstrate that surface deformation is quite distinct in buoyant-thermocapillary convection. in order to understand the mechanism of buoyant-thermocapillary convection, not only the hydrothermal wave instability but also the surface wave instability should be discussed.

New tools for self-organised pattern formation

Position-dependent gene expression is a critical aspect of the development and behaviour of multicellular organisms. It requires a complex series of interactions to occur between different cell types in addition to intracellular signalling cascades. We used Escherichia coli to study the properties of an artificial signalling system at the interface between two expanding cell populations. We genetically engineered one population to produce a diffusible acyl-homoserine lactone (AHL) signal, and another population to respond to it. Our experiments demonstrate how such a signal can be used to reproducibly generate simple visible patterns with high accuracy in swimming agar. The producing and responding cassettes of two such signalling systems can be linked to produce a symmetric interface for bidirectional communication that can be used to visualise molecular logic. Intracellular feedback between these two cassettes would then create a framework for self-organised patterning of higher complexity. Adapting the experiments of Basu et al. (Basu et al., 2005) using cell motility, rather than a differential response to AHL concentrations as a way to define zones of response, we noted how the interaction of sender and receiver cell populations on a swimming plate could lead to complex pattern formation. Equipping highly motile strains such as E. coli MC1000 with AHL-mediated auto-inducing systems based on Vibrio fischeri luxI/luxR and Pseudomonas aeruginosa lasI/lasR cassettes would allow the amplification of a response to an AHL signal and its propagation. We designed and synthesised codon-optimised auto-inducing luxI/R and lasI/R cassettes as optimal gene expression is crucial for the generation of robust patterns. We still have to complete and test the entire genetic circuitry, although by modelling the system we were able to demonstrate its feasibility. © 2007 The Institution of Engineering and Technology.

Pattern formation and spatial solitons in bistable liquid-crystal microcavities

We report on spatial pattern formation, and appearances of 'optical bullet holes' in single-mode microcavities that are filled with liquid-crystals, when pumped above the cavity resonance frequency. These phenomena only occur beyond the bistability threshold. ©2002 Optical Society of America.

Pattern Recognition With Weighted Complex Networks

In this paper we introduce a weighted complex networks model to investigate and recognize structures of patterns. The regular treating in pattern recognition models is to describe each pattern as a high-dimensional vector which however is insufficient to express the structural information. Thus, a number of methods are developed to extract the structural information, such as different feature extraction algorithms used in pre-processing steps, or the local receptive fields in convolutional networks. In our model, each pattern is attributed to a weighted complex network, whose topology represents the structure of that pattern. Based upon the training samples, we get several prototypal complex networks which could stand for the general structural characteristics of patterns in different categories. We use these prototypal networks to recognize the unknown patterns. It is an attempt to use complex networks in pattern recognition, and our result shows the potential for real-world pattern recognition. A spatial parameter is introduced to get the optimal recognition accuracy, and it remains constant insensitive to the amount of training samples. We have discussed the interesting properties of the prototypal networks. An approximate linear relation is found between the strength and color of vertexes, in which we could compare the structural difference between each category. We have visualized these prototypal networks to show that their topology indeed represents the common characteristics of patterns. We have also shown that the asymmetric strength distribution in these prototypal networks brings high robustness for recognition. Our study may cast a light on understanding the mechanism of the biologic neuronal systems in object recognition as well.