Non-encapsulated thermo-liquid crystals for digital particle tracking thermography/velocimetry in microfluidics

The ever accelerating state of technology has powered an increasing interest in heat transfer solutions and process engineering innovations in the microfluidics domain. In order to carry out such developments, reliable heat transfer diagnostic techniques are necessary. Thermo-liquid crystal (TLC) thermography, in combination with particle image velocimetry, has been a widely accepted and commonly used technique for the simultaneous measurement and characterization of temperature and velocity fields in macroscopic fluid flows for several decades. However, low seeding density, volume illumination, and low TLC particle image quality at high magnifications present unsurpassed challenges to its application to three-dimensional flows with microscopic dimensions. In this work, a measurement technique to evaluate the color response of individual non-encapsulated TLC particles is presented. A Shirasu porous glass membrane emulsification approach was used to produce the non-encapsulated TLC particles with a narrow size distribution and a multi-variable calibration procedure, making use of all three RGB and HSI color components, as well as the proper orthogonally decomposed RGB components, was used to achieve unprecedented low uncertainty levels in the temperature estimation of individual particles, opening the door to simultaneous temperature and velocity tracking using 3D velocimetry techniques.     

Towards enhancing the security and accuracy of iris recognition systems

The intricate structure of the iris constitutes a powerful biometric characteristic utilized by iris recognition algorithms to extract discriminative biometric templates. Iris recognition is field-proven but consequential issues, e.g. privacy protection or recognition in unconstrained environments, still to be solved, raise the need for further investigations. In this paper different improvements focused on template protection and biometric comparators are presented. Experimental evaluations are performed on a public dataset confirming the soundness of proposed enhancements.     

Geometry based pre-processor for parallel fluid dynamic simulations using a hierarchical basis

The pre-processing stage of finite element analysis of the Navier–Stokes equations is becoming increasingly important as the desire for more general boundary conditions, as well as applications to parallel computers increases. The set up of general boundary conditions and communication structures for parallel computations should be accomplished during the pre-processing phase of the analysis, if possible, to ensure efficient computations for large scale problems in computational fluid dynamics. This paper introduces a general methodology for geometry based boundary condition application and pre-computing of parallel communication tasks. A. K. Karanam was supported by NSF Grant No. 9985340. C. H. Whiting was supported by a grant from NASA LaRC.     

An ant colony optimization algorithm for DNA sequencing by hybridization

The reconstruction of DNA sequences from DNA fragments is one of the most challenging problems in computational biology. In recent years the specific problem of DNA sequencing by hybridization has attracted quite a lot of interest in the optimization community. Several metaheuristics such as tabu search and evolutionary algorithms have been applied to this problem. However, the performance of existing metaheuristics is often inferior to the performance of recently proposed constructive heuristics. On the basis of these new heuristics we develop an ant colony optimization algorithm for DNA sequencing by hybridization. An important feature of this algorithm is the implementation in a so-called multi-level framework. The computational results show that our algorithm is currently a state-of-the-art method for the tackled problem.     

Rapid convergence to feature layer correspondences

We describe a neural network able to rapidly establish correspondence between neural feature layers. Each of the network's two layers consists of interconnected cortical columns, and each column consists of inhibitorily coupled subpopulations of excitatory neurons. The dynamics of the system builds on a dynamic model of a single column, which is consistent with recent experimental findings. The network realizes dynamic links between its layers with the help of specialized columns that evaluate similarities between the activity distributions of local feature cell populations, are subject to a topology constraint, and can gate the transfer of feature information between the neural layers. The system can robustly be applied to natural images, and correspondences are found in time intervals estimated to be smaller than 100 ms in physiological terms.     

Analysis of Two-Dimensional Non-Rigid Shapes

Analysis of deformable two-dimensional shapes is an important problem, encountered in numerous pattern recognition, computer vision and computer graphics applications. In this paper, we address three major problems in the analysis of non-rigid shapes: similarity, partial similarity, and correspondence. We present an axiomatic construction of similarity criteria for deformation-invariant shape comparison, based on intrinsic geometric properties of the shapes, and show that such criteria are related to the Gromov-Hausdorff distance. Next, we extend the problem of similarity computation to shapes which have similar parts but are dissimilar when considered as a whole, and present a construction of set-valued distances, based on the notion of Pareto optimality. Finally, we show that the correspondence between non-rigid shapes can be obtained as a byproduct of the non-rigid similarity problem. As a numerical framework, we use the generalized multidimensional scaling (GMDS) method, which is the numerical core of the three problems addressed in this paper.     

Over-Parameterized Variational Optical Flow

A novel optical flow estimation process based on a spatio-temporal model with varying coefficients multiplying a set of basis functions at each pixel is introduced. Previous optical flow estimation methodologies did not use such an over parameterized representation of the flow field as the problem is ill-posed even without introducing any additional parameters: Neighborhood based methods of the Lucas–Kanade type determine the flow at each pixel by constraining the flow to be described by a few parameters in small neighborhoods. Modern variational methods represent the optic flow directly via the flow field components at each pixel. The benefit of over-parametrization becomes evident in the smoothness term, which instead of directly penalizing for changes in the optic flow, accumulates a cost of deviating from the assumed optic flow model. Our proposed method is very general and the classical variational optical flow techniques are special cases of it, when used in conjunction with constant basis functions. Experimental results with the novel flow estimation process yield significant improvements with respect to the best results published so far.     

Partial Partitions,Partial Connections and Connective Segmentation

In connective segmentation (Serra in J. Math. Imaging Vis. 24(1):83–130, [2006]), each image determines subsets of the space on which it is “homogeneous”, in such a way that this family of subsets always constitutes a connection (connectivity class); then the segmentation of the image is the partition of space into its connected components according to that connection. Several concrete examples of connective segmentations or of connections on sets, indicate that the space covering requirement of the partition should be relaxed. Furthermore, morphological operations on partitions require the consideration of wider framework. We study thus partial partitions (families of mutually disjoint non-void subsets of the space) and partial connections (where connected components of a set are mutually disjoint but do not necessarily cover the set). We describe some methods for generating partial connections. We investigate the links between the two lattices of partial connections and of partial partitions. We generalize Serra’s characterization of connective segmentation and discuss its relevance. Finally we give some ideas on how the theory of partial connections could lead to improved segmentation algorithms.

Production of two-material micro-assemblies by two-component powder injection molding and sinter-joining

In the field of micro-technology the production of metallic and ceramic micro-components by powder injection molding (PIM) has become a more and more established fabrication method. But in order to fulfill the demand for more complex-shaped high-precision micro-components further development work has to be performed. This is especially true if more efficient production routes for multi-component-micro-assemblies consisting of different materials or sub-components are envisaged. To meet these challenges, investigations are performed to realize and to establish two primary shape micro-processes. These are two-component micro-injection molding (2C-MicroPIM) and sinter-joining. The realization of these technologies will lead to a markedly reduction of the efforts for handling, adjustment, and assembling of metallic and ceramic micro-assemblies. Furthermore, an increased integration level and functionality can be yielded. For an effective transfer of scientific results to industrial applications the whole process chain must be considered, from development and construction of the tooling as well as of the components to the quality assurance and determination of the properties of the assemblies after sintering. These primary shape processes shall enable the mutual processing of different materials within the fabrication process, so avoiding separate mounting or assembling steps. Additionally fixed and loose junctions between at least two components shall be realized. The progress in research and development will be demonstrated especially by the implementation of shaft-to-collar connections between micro-gearwheels and corresponding shafts. Regarding two-component micro-injection molding, the tool construction for shaft-to-collar connections will be presented as well as first experimental results on the properties of selected ceramic powders and feedstocks for the special requirements of the 2C-MicroPIM process. With the assembly step being performed outside the injection molding tool before sinter-joining different parts and geometries can be combined quite easily. The presented article gives an overview on the concept and on preliminary testing results for the fabrication of a shaft-to-collar-connection. Additionally, a solution for an automated assembly of a shaft and a toothed wheel outside the injection molding tool is presented.