Edge Detection with Sub-pixel Accuracy Based on Approximation of Edge with Erf Function

Edge detection is an often used procedure in digital image processing. For some practical applications is desirable to detect edges with sub-pixel accuracy. In this paper we present edge detection method for 1-D images based on approximation of real image function with Erf function. This method is verified by simulations and experiments for various numbers of samples of simulated and real images. Results of simulations and experiments are also used to compare proposed edge detection scheme with two often used moment-based edge detectors with sub-pixel precision

Mobile ad hoc network testbed using mobile robot technology

MANET (Mobile Ad Hoc Network) researchers have shown increased interest in using mobile robot technology for their testbed platforms. Thus, the main motivation of this paper is to review various robot-based MANET testbeds that have been developed in previously reported research. Additionally, suggestions to heighten mobility mechanisms by using mobile robots to be more practical, easy and inexpensive are also included in this paper, as we unveils ToMRobot, a low-cost MANET robot created from an ordinary remote control car that is capable of performing a real system MANET testbed with the addition of only a few low-cost electronic components. Despite greatly reduced costs, the ToMRobot does not sacrifice any of the necessary MANET basic structures and will still be easily customizable and upgradeable through the use of open hardware technology like Cubieboard2 and Arduino, as its robot controller. This paper will also include guidelines to enable technically limited MANET researchers to design and develop the ToMRobot. It is hoped that this paper achieves its two pronged objectives namely (i) to facilitate other MANET researchers by providing them with a source of reference that eases their decision making for selecting the best and most suitable MANET mobile robots for real mobility in their MANET testbeds (ii) to provide MANET researchers with a prospect of building their own MANET robots that can be applied in their own MANET testbed in the future

4D and 5D phase-space tomography using slowing-down physics regularization

We compute reconstructions of 4D and 5D fast-ion phase-space distribution functions in fusion plasmas from synthetic projections of these functions. The fast-ion phase-space distribution functions originating from neutral beam injection (NBI) at TCV and Wendelstein 7-X (W7-X) at full, half, and one-third injection energies can be istinguished and particle densities of each component inferred based on 20 synthetic spectra of projected velocities at TCV and 680 at W7-X. Further, we demonstrate that an expansion into a basis of slowing-down distribution functions is equivalent to regularization using slowing-down physics as prior information. Using this technique in a Tikhonov formulation, we infer the particle density fractions for each NBI energy for each NBI beam from synthetic measurements, resulting in six unknowns at TCV and 24 unknowns at W7-X. Additionally, we show that installing 40 LOS in each of 17 ports at W7-X, providing full beam coverage and almost full angle coverage, produces the highest quality reconstructions

Analysis of Sample Correlations for Monte Carlo Rendering

Modern physically based rendering techniques critically depend on approximating integrals of high dimensional functions representing radiant light energy. Monte Carlo based integrators are the choice for complex scenes and effects. These integrators work by sampling the integrand at sample point locations. The distribution of these sample points determines convergence rates and noise in the final renderings. The characteristics of such distributions can be uniquely represented in terms of correlations of sampling point locations. Hence, it is essential to study these correlations to understand and adapt sample distributions for low error in integral approximation. In this work, we aim at providing a comprehensive and accessible overview of the techniques developed over the last decades to analyze such correlations, relate them to error in integrators, and understand when and how to use existing sampling algorithms for effective rendering workflows.publishe

Compressed Suffix Arrays for Massive Data

We present a fast space-efficient algorithm for constructing compressed suffix arrays (CSA). The algorithm requires O(n log n) time in the worst case, and only O(n) bits of extra space in addition to the CSA. As the basic step, we describe an algorithm for merging two CSAs. We show that the construction algorithm can be parallelized in a symmetric multiprocessor system, and discuss the possibility of a distributed implementation. We also describe a parallel implementation of the algorithm, capable of indexing several gigabytes per hour

Telomerase promoter mutations in cancer: an emerging molecular biomarker?

João Vinagre, Vasco Pinto and Ricardo Celestino contributed equally to the manuscript.Cell immortalization has been considered for a long time as a classic hallmark of cancer cells. Besides telomerase reactivation, such immortalization could be due to telomere maintenance through the “alternative mechanism of telomere lengthening” (ALT) but the mechanisms underlying both forms of reactivation remained elusive. Mutations in the coding region of telomerase gene are very rare in the cancer setting, despite being associated with some degenerative diseases. Recently, mutations in telomerase (TERT) gene promoter were found in sporadic and familial melanoma and subsequently in several cancer models, notably in gliomas, thyroid cancer and bladder cancer. The importance of these findings has been reinforced by the association of TERT mutations in some cancer types with tumour aggressiveness and patient survival. In the first part of this review, we summarize the data on the biology of telomeres and telomerase, available methodological approaches and non-neoplastic diseases associated with telomere dysfunction. In the second part, we review the information on telomerase expression and genetic alterations in the most relevant types of cancer (skin, thyroid, bladder and central nervous system) on record, and discuss the value of telomerase as a new biomarker with impact on the prognosis and survival of the patients and as a putative therapeutic target