Space-dependent color gamut mapping: a variational approach.

Gamut mapping deals with the need to adjust a color image to fit into the constrained color gamut of a given rendering medium. A typical use for this tool is the reproduction of a color image prior to its printing, such that it exploits best the given printer/medium color gamut, namely the colors the printer can produce on the given medium. Most of the classical gamut mapping methods involve a pixel-by-pixel mapping and ignore the spatial color configuration. Recently proposed spatial-dependent approaches for gamut mapping are either based on heuristic assumptions or involve a high computational cost. In this paper, we present a new variational approach for space-dependent gamut mapping. Our treatment starts with the presentation of a new measure for the problem, closely related to a recent measure proposed for Retinex. We also link our method to recent measures that attempt to couple spectral and spatial perceptual measures. It is shown that the gamut mapping problem leads to a quadratic programming formulation, guaranteed to have a unique solution if the gamut of the target device is convex. An efficient numerical solution is proposed with promising results.     

A probabilistic alternative to regression suites

Automated regression suites are essential in developing large applications, while maintaining reasonable quality and timetables. The main argument against the automation of regression suites, in addition to the cost of creation and maintenance, is the observation that if you run the same test many times, it becomes increasingly less likely to find bugs. To alleviate such problems, a new regression suite practice, using random test generators to create regression suites on-the-fly, is becoming more common. In this practice, instead of maintaining tests, we generate test suites on-the-fly by choosing several specifications and generating a number of tests from each specification.     

On the complexity of approximating k-set packing

Given a k-uniform hypergraph, the Maximum k -Set Packing problem is to find the maximum disjoint set of edges. We prove that this problem cannot be efficiently approximated to within a factor of unless P = NP. This improves the previous hardness of approximation factor of by Trevisan. This result extends to the problem of k-Dimensional-Matching.     

A reduction approach to the two-campus transport problem

The two-campus transport problem (TCTP) is a dial-a-ride problem with only two destinations. The problem is motivated by a transport problem between two campuses of an academic college. The two campuses are located in two different cities. Lecturers living in one city are sometimes asked to teach at the other city’s campus. The problem is that of transporting the lecturers from one campus to the other, using a known set of vehicles, so as to minimize the time the lecturers wait for their transport. We mathematically model the general TCTP, and provide an algorithm that solves it, which is polynomial in the number of lecturers. The algorithm is based on a reduction to a shortest path problem.     

Advantages and limitations of in vitro and in vivo methods of iron and zinc bioavailability evaluation in the assessment of biofortification program effectiveness

ABSTRACT

Biofortification aims to improve the micronutrient concentration of staple food crops through the best practices of breeding and modern biotechnology. However, increased zinc and iron concentrations in food crops may not always translate into proportional increases in absorbed zinc (Zn) and iron (Fe). Therefore, assessing iron and zinc bioavailability in biofortified crops is imperative to evaluate the efficacy of breeding programs. This review aimed to investigate the advantages and limitations of in vitro and in vivo methods of iron and zinc bioavailability evaluation in the assessment of biofortification program effectiveness. In vitro, animal and isotopic human studies have shown high iron and zinc bioavailability in biofortified staple food crops. Human studies provide direct knowledge regarding the effectiveness of biofortification, however, human studies are time consuming and are more expensive than in vitro and animal studies. Moreover, in vitro studies may be a useful preliminary screening method to identify promising plant cultivars, however, these studies cannot provide data that are directly applicable to humans. None of these methods provides complete information regarding mineral bioavailability, thus, a combination of these methods should be the most appropriate strategy to investigate the effectiveness of zinc and iron biofortification programs.     

Classification of finger activation for use in a robotic prosthesis arm

Hand amputees would highly benefit from a robotic prosthesis, which would allow the movement of a number of fingers. In this paper we propose using the electromyographic signals recorded by two pairs of electrodes placed over the arm for operating such prosthesis. Multiple features from these signals are extracted whence the most relevant features are selected by a genetic algorithm as inputs for a simple classifier. This method results in a probability of error of less than 2%.     

A simpler analysis of Burrows–Wheeler-based compression

In this paper, we present a new technique for worst-case analysis of compression algorithms which are based on the Burrows–Wheeler Transform. We mainly deal with the algorithm proposed by Burrows and Wheeler in their first paper on the subject [M. Burrows, D.J. Wheeler, A block sorting lossless data compression algorithm, Technical Report 124, Digital Equipment Corporation, Palo Alto, California, 1994], called bw0. This algorithm consists of the following three essential steps: (1) Obtain the Burrows–Wheeler Transform of the text, (2) Convert the transform into a sequence of integers using the move-to-front algorithm, (3) Encode the integers using Arithmetic code or any order-0 encoding (possibly with run-length encoding).     

Equilibrium segregation of Ti to Au–sapphire interfaces

Equilibrium segregation of Ti to Au–sapphire interfaces was measured from dewetted Au(Ti) films on the (0001) surface of sapphire. Quantitative energy dispersive spectroscopy was used to determine a Ti excess at the Au–sapphire interface of 2.2 Ti atoms/nm², which together with an excess of 4.6 Ti atoms/nm² at the (0001) sapphire surface, is associated with a decrease in the solid–solid Au–sapphire interface energy. Quantitative high resolution transmission electron microscopy showed that the segregated Ti is distributed within a 1.54-nm thick intergranular film at the Au–sapphire interface, which is not a bulk phase but rather an equilibrium interface state. As a result, Ti segregation without the formation of a bulk reaction at the interface is associated with a decreased interface energy, improved wetting, and may be an important part of the total complex mechanism responsible for improved wetting and spreading in “reactive” braze systems.     

Cross-Modal Localization via Sparsity

Cross-modal analysis is a natural progression beyond processing of single-source signals. Simultaneous processing of two sources can reveal information that is unavailable when handling the sources separately. Indeed, human and animal perception, computer vision, weather forecasting, and various other scientific and technological fields can benefit from such a paradigm. A particular cross-modal problem is localization: out of the entire data array originating from one source, localize the components that best correlate with the other. For example, auditory and visual data sampled from a scene can be used to localize visual events associated with the sound track. In this paper we present a rigorous analysis of fundamental problems associated with the localization task. We then develop an approach that leads efficiently to a unique, high definition localization outcome. Our method is based on canonical correlation analysis (CCA), where inherent ill-posedness is removed by exploiting sparsity of cross-modal events. We apply our approach to localization of audio-visual events. The proposed algorithm grasps such dynamic audio-visual events with high spatial resolution. The algorithm effectively detects the pixels that are associated with sound, while filtering out other dynamic pixels, overcoming substantial visual distractions and audio noise. The algorithm is simple and efficient thanks to its reliance on linear programming, while being free of user-defined parameters