Mean shift based gradient vector flow for image segmentation

In recent years, gradient vector flow (GVF) based algorithms have been successfully used to segment a variety of 2-D and 3-D imagery. However, due to the compromise of internal and external energy forces within the resulting partial differential equations, these methods may lead to biased segmentation results. In this paper, we propose MSGVF, a mean shift based GVF segmentation algorithm that can successfully locate the correct borders. MSGVF is developed so that when the contour reaches equilibrium, the various forces resulting from the different energy terms are balanced. In addition, the smoothness constraint of image pixels is kept so that over- or under-segmentation can be reduced. Experimental results on publicly accessible datasets of dermoscopic and optic disc images demonstrate that the proposed method effectively detects the borders of the objects of interest.

Food of the Blue

An episode of BBC Radio 4's detective series 'Baldi'. Paolo Baldi finds himself in a world of superstar academics, but why are their bloodless corpses littering the college? And what is that thing they drink to rejuvenate the venerable institution?

You have free access to this content 5.8 GHz full duplex amplitude shift keying retrodirective interrogator array

This article describes a practical demonstration of a complete full-duplex “amplitude shift keying (ASK)” retrodirective radio frequency identification (RFID) transceiver array.The interrogator incorporates a “retrodirective array (RDA)” with a dual-conversion phase conjugating architecture in order to achieve better performance than is possible with conventional RFID solutions. Here mixers phase conjugate the incoming signal and a carrier recovery circuit recovers incoming angle of arrival phase information of an encoded amplitude shift keyed signal. The resulting interrogator provides a receiver sensitivity level of -109 dBm. A four element square patch RDA gives a 3 dB automatic beam steering angle of acceptance of ±45°. When compared to an RFID system operating by conventional (non-retrodirective) means retrodirective action leads to improved range extension of up to 16 times at ±45°. Operator pointing accuracy requirements are also reduced due to automatic retrodirective self-pointing. These features significantly enhance deployment opportunities requiring long range low equivalent isotropic radiation power (EIRP) and/or RFID tagging of moving platforms. © 2012 Wiley Periodicals, Inc. Microwave Opt Technol Lett 55:160–164, 2013; View this article online at wileyonlinelibrary.com. DOI 10.1002/mop.27258

Overcoming the Scalability Challenges of Epidemic Simulations on Blue Waters

Modeling dynamical systems represents an important application class covering a wide range of disciplines including but not limited to biology, chemistry, finance, national security, and health care. Such applications typically involve large-scale, irregular graph processing, which makes them difficult to scale due to the evolutionary nature of their workload, irregular communication and load imbalance. EpiSimdemics is such an application simulating epidemic diffusion in extremely large and realistic social contact networks. It implements a graph-based system that captures dynamics among co-evolving entities. This paper presents an implementation of EpiSimdemics in Charm++ that enables future research by social, biological and computational scientists at unprecedented data and system scales. We present new methods for application-specific processing of graph data and demonstrate the effectiveness of these methods on a Cray XE6, specifically NCSA's Blue Waters system.

Using entropy based mean shift filter and modified watershed transform for grain segmentation

Life science research aims to continuously improve the quality and standard of human life. One of the major challenges in this area is to maintain food safety and security. A number of image processing techniques have been used to investigate the quality of food products. In this paper,we propose a new algorithm to effectively segment connected grains so that each of them can be inspected in a later processing stage. One family of the existing segmentation methods is based on the idea of watersheding, and it has shown promising results in practice.However,due to the over-segmentation issue,this technique has experienced poor performance in various applications,such as inhomogeneous background and connected targets. To solve this problem,we present a combination of two classical techniques to handle this issue.In the first step,a mean shift filter is used to eliminate the inhomogeneous background, where entropy is used to be a converging criterion. Secondly,a color gradient algorithm is used in order to detect the most significant edges, and a marked watershed transform is applied to segment cluttered objects out of the previous processing stages. The proposed framework is capable of compromising among execution time, usability, efficiency and segmentation outcome in analyzing ring die pellets. The experimental results demonstrate that the proposed approach is effectiveness and robust.

Preliminary investigation of mixed adsorbents for the removal of copper and methylene blue from aqueous solutions

With most recent studies being focused on the development of
advanced chemical adsorbents, this paper investigates the possibility of
using two natural low-cost materials for selective adsorption. Multiadsorbent
systems containing tea waste and dolomite have been tested for
their effectiveness in the removal of copper and methylene blue from
aqueous solutions. The effects of contact time, solution pH and
adsorption isotherms on the sorption behaviour were investigated. The
Langmuir and Freundlich isotherms adequately described the adsorption of
copper ions and methylene blue by both materials in different systems.
The highest adsorption capacities for Cu and MB were calculated as 237.7
at pH 4.5 and 150.44 mg.g‒1 at pH 7 for DO and TW+DO respectively. Tea
waste (TW) and dolomite (DO) were characterized by Fourier transform
infrared spectroscopy, scanning electron microscopy and Energy dispersive
X-ray analysis. The removal of Cu and MB by dolomite was mainly via
surface complexation while physisorption was responsible for most of the
Cu and MB adsorption onto tea waste. Identifying the fundamental mechanisms and behaviour is key to the development of practical multi-adsorbent packed columns.

Chemistry and Mechanism of Alizarin Red S and Methylene Blue Biosorption onto Olive Stone: Equilibrium and Kinetic

The biosorption process of anionic dye Alizarin Red S (ARS) and cationic dye methylene blue (MB) as a function of solution pH, initial concentration and contact time onto olive stone (OS) biomass has been investigated. The main objectives of the current study are to: (i) study the chemistry and the mechanism of ARS and MB biosorption onto olive stone and the type of OS–ARS, MB interactions occurring, (ii) study the biosorption equilibrium and kinetic experimental data required for the design and operation of column reactors. Equilibrium biosorption isotherms and kinetics were also examined. Experimental equilibrium data were fitted to four different isotherms by non-linear regression method, however, the biosorption experimental data for ARS and MB dyes were well interpreted by the Temkin and Langmuir isotherms, respectively. The maximum monolayer adsorption capacity for ARS and MB dyes were 109.0 and 102.6 mg/g, respectively. The kinetic data of the two dyes could be better described by the pseudo second-order model. The data showed that olive stone can be effectively used for removing dyes from wastewater.