Fast computation of computer-generated hologram using Xeon Phi coprocessor

We report fast computation of computer-generated holograms (CGHs) using Xeon Phi coprocessors, which have massively x86-based processors on one chip, recently released by Intel. CGHs can generate arbitrary light wavefronts, and therefore, are promising technology for many applications: for example, three-dimensional displays, diffractive optical elements, and the generation of arbitrary beams. CGHs incur enormous computational cost. In this paper, we describe the implementations of several CGH generating algorithms on the Xeon Phi, and the comparisons in terms of the performance and the ease of programming between the Xeon Phi, a CPU and graphics processing unit (GPU).     

Digit recognition in a natural scene with skew and slant normalization

This paper proposes a method to recognize digits in a natural scene, such as telephone numbers on a signboard. Candidate regions of digits are extracted from an image through contrast enhancement, edge extraction, and labeling. Since the target text patterns are in a 3D space, unlike traditional character recognition problems, we have to deal with the image transformation effect due to the orientation in the 3D space and projection. We have to cancel the effect as much as possible before digit recognition. In our method, the image transformation effect is modeled as skew and slant. In the proposed method, simplified Hough transform is used for the skew normalization. After the skew normalization, the remaining effect of image transformation is corrected by circumscribing digit patterns with tilted rectangles and affine transformation. In experiments, we tested a total of 1,332 images of signboards with 11,939 digits. We obtained a digit extraction rate of 99.2% and a correct digit recognition rate of 98.8%.Received: 15 December 2003, Accepted: 21 October 2004, Published online: 2 February 2005     

A hybrid model for a multiproduct pipeline planning and scheduling problem

Brazilian petrobras is one of the world largest oil companies. Recurrently, it faces a very difficult planning and scheduling problem: how to operate a large pipeline network in order to adequately transport oil derivatives and biofuels from refineries to local markets. In spite of being more economical and environmentally safer, the use of a complex pipeline network poses serious operational difficulties related to resource allocation and temporal constraints. The current approaches known from the literature only consider a few types of constraints and restricted topologies, hence they are far from being applicable to real instances from petrobras. We propose a hybrid framework based on a two-phase problem decomposition strategy. A novel Constraint Programming (CP) model plays a key role in modelling operational constraints that are usually overlooked in literature, but that are essential in order to guarantee viable solutions. The full strategy was implemented and produced very adequate results when tested over large real instances.     

Reversible data hiding based compressible privacy preserving system for color image

In digital era, privacy preservation and data size reduction are important issues and many applications handle them simultaneously. In this paper, authors introduce a novel application of reversible data hiding to protect privacy sensitive region in a color image while reducing its file size. The proposed work introduces entropy as a new performance criterion along with distortion, capacity for reversible data hiding. Evaluation metric of the proposed method is a file size of watermarked and losslessly compressed image. The proposed method preserves privacy and controls rise in image entropy by reversible data hiding.

     

Existential rigidity and many modalities in order-sorted logic

Order-sorted logic is a useful tool for knowledge representation and reasoning because it enables representation of sorted terms and formulas along with partially ordered sorts (called sort-hierarchy). However, this logic cannot represent more complex sorted expressions when they are true in any possible world (as rigid) or some possible worlds (as modality) such as time, space, belief, or situation. In this study, we extend order-sorted logic by introducing existential rigidity and many modalities. In the extended logic, sorted modal formulas are interpreted over the Cartesian product of sets of possible worlds. We present a new labeled tableau calculus to check the (un)satisfiability and validity of sorted modal formulas.     

On-chip fabrication of magnetic alginate hydrogel microfibers by multilayered pneumatic microvalves

Alginate hydrogel has widespread applications in tissue engineering, cancer therapy, wound management and drug/cell/growth factor delivery due to its biocompatibility, hydrated environment and desirable viscoelastic properties. However, the lack of controllability is still an obstacle for utilizing it in the fabrication of 3D tissue constructs and accurate targeting in mass delivery. Here, we proposed a new method for achieving magnetic alginate hydrogel microfibers by dispersing magnetic nanoparticles in alginate solution and solidifying the magnetic alginate into hydrogel fiber inside microfluidic devices. The microfluidic devices have multilayered pneumatic microvalves with hemicylindrical channels to fully stop the fluids. In the experiments, the magnetic nanoparticles and the alginate solution were mixed and formed a uniform suspension. No aggregation of magnetic nanoparticles was found, which is crucial for flow control inside microfluidic devices. By regulating the flow rates of different solutions with the microvalves inside the microfluidic device, magnetic hydrogel fibers and nonmagnetic hydrogel fibers were fabricated with controlled sizes. The proposed method for fabricating magnetic hydrogel fiber holds great potential for engineering 3D tissue constructs with complex architectures and active drug release.     

Algorithms for Extracting Correct Critical Points and Constructing Topological Graphs from Discrete Geographical Elevation Data

Researchers in the fields of computer graphics and geographical information systems (GISs) have extensively studied the methods of extracting terrain features such as peaks, pits, passes, ridges, and ravines from discrete elevation data. The existing techniques, however, do not guarantee the topological integrity of the extracted features because of their heuristic operations, which results in spurious features. Furthermore, there have been no algorithms for constructing topological graphs such as the surface network and the Reeb graph from the extracted peaks, pits, and passes. This paper presents new algorithms for extracting features and constructing the topological graphs using the features. Our algorithms enable us to extract correct terrain features; i.e., our method extracts the critical points that satisfy the Euler formula, which represents the topological invariant of smooth surfaces. This paper also provides an algorithm that converts the surface network to the Reeb graph for representing contour changes with respect to the height. The discrete elevation data used in this paper is a set of sample points on a terrain surface. Examples are presented to show that the algorithms also appeal to our visual cognition.