Showing papers by "Neeraj Sharma published in 2018"
TL;DR: An algorithm for postprocessing DCE-MRI data using multistable stochastic resonance (MSSR) technique is proposed and marked regions of interest (ROIs) are labeled as normal and microadenoma of pituitary obtained with increased level of accuracy and confidence.
Abstract: Magnetic resonance imaging (MRI) is the modality of choice as far as imaging diagnosis of pathologies in the pituitary gland is concerned. Furthermore, the advent of dynamic contrast enhanced (DCE) has enhanced the capability of this modality in detecting minute benign but endocrinologically significant tumors called microadenoma. These lesions are visible with difficulty and a low confidence level in routine MRI sequences, even after administration of intravenous gadolinium. Techniques to enhance the visualization of such foci would be an asset in improving the overall accuracy of DCE-MRI for detection of pituitary microadenomas. The present study proposes an algorithm for postprocessing DCE-MRI data using multistable stochastic resonance (MSSR) technique. Multiobjective ant lion optimization optimizes the contrast enhancement factor (CEF) and anisotropy of an image by varying the parameters associated with the dynamics of MSSR. The marked regions of interest (ROIs) are labeled as normal and microadenoma of pituitary obtained with increased level of accuracy and confidence using proposed algorithm. The increased difference between the mean intensity curves obtained using these ROIs validated the obtained subjective results. Furthermore, the proposed MSSR-based algorithm has been evaluated on standard T1 and T2 weighted BrainWeb dataset images and quantified in terms of CEF, peak signal to noise ratio (PSNR), structure similarity index measure (SSIM), and universal quality index (UQI). The obtained mean values of CEF 1.22, PSNR 27.68, SSIM 0.75, UQI 0.83 for twenty dataset images were highest among considered contrast enhancement algorithms for the comparison.
28 citations
TL;DR: In this article, the authors proposed a cascaded stochastic resonance (DSR) which exploits the properties of modified potential neuron model and quartic bistable model of DSR.
Abstract: Background The contrast enhancement of Magnetic Resonance Imaging (MRI) data is quite challenging as the noise present in this data also get amplified in this process. Dynamic Stochastic Resonance (DSR) is the technique that utilizes the noise to enhance the contrast of MRI data. Method The present study proposes the cascaded stochastic resonance, which exploits the properties of modified potential neuron model and quartic bistable model of DSR. The Multi-objective Particle Swarm Optimization (MOPSO) tunes the DSR parameters associated with the cascading of both the models. The MOPSO produces a set of the solution called Pareto front for the maximization of two image quality measures, i.e., contrast enhancement factor and universal image quality index. Further, the maximization of another image quality measure, i.e., anisotropy helps to obtain the optimum enhanced image from the Pareto fronts solution. Results The present study included the simulated and real MRI data. The results show that the proposed method obtained mean contrast enhancement factor, universal image quality index and anisotropy equal to 1.79, 0.78 and 0.021 respectively. These values are better than those obtained for classical bistable DSR and other conventional contrast enhancement techniques. The proposed algorithm has been tested on real MRI data as well and found valuable in the diagnosis of lacunar infarct and mesial temporal sclerosis. Conclusion The cascaded DSR based on MOPSO has shown promising results and may be highly beneficial to the diagnosis of different brain pathology.
20 citations
Journal Article•
8 citations
TL;DR: In this article, the state of Jammu and Kashmir has received new nymphalid butterfly records based on butterfly surveys conducted in different ecosystems in a span of two years, and the sightings are based on the butterfly surveys performed in Jammu region.
Abstract: The present communication deals with the new nymphalid butterfly records from the state of Jammu and Kashmir. The sightings are based on the butterfly surveys conducted in different ecosystems of Jammu region in a span of two years. The paper calls for more organized and intensive butterfly surveys to understand their status, distribution and population dynamics in and around Jammu.
6 citations
TL;DR: The proposed noise estimation approach followed by filtering is giving better de-noising and segmentation results as compared to standard filters considered.
1 citations
11 Apr 2018
TL;DR: In this article, the authors present a proof corrected by the author available online since mercredi 19 septembre 2018 and available since 17 September 2018, since the publication of this article.
Abstract: IRBM - In Press.Proof corrected by the author Available online since mercredi 19 septembre 2018
Journal Article•
TL;DR: The aim of this work is to choose a topology for mobile WSN and improve the network connectivity as a whole while considering and influencing the energy consumption among all the nodes in the network.
Abstract: How to maintain connectivity is an important issue in ad hoc networks. A special cases of such network is Wireless Sensor Networks (WSN), which are often deployed in harsh environments and also susceptible to a number of problems that may negatively affect the connectivity among the nodes. An moreover factor that increases the charge of connectivity maintenance in ad hoc networks is when the nodes can move. When it come to the WSN domain, this aspect is still more problematic, as the often small sensor nodes have in general a limited energy budget, and then should not use maximum energy in the management of their connectivity. The aim of this work is to choose a topology for mobile WSN and improve the network connectivity as a whole while considering and influencing the energy consumption among all the nodes in the network. Different network topologies are considered and discussed. After assessment of the pros and cons of the estimation quality, when applied to each studied topology, a clustered hierarchical algorithm was chosen for network deployment. By means of a link valuer and considering different variables, a metric have been defined to estimate the link reliability. As a result, improved network connectivity is reported.Keywords-component; Mobile WSN connectivity; distributed energy consumption deployment; clustered hierarchical topology; link estimator.
Journal Article•
TL;DR: The Fraunhofer Umsicht Cryogenic Grinding Facility at Oberhausen in the Ruhr area of Germany as mentioned in this paper has been used for high-temperature fine-grinding.
Abstract: -The production of finest powders of viscoelastic and plastic materials is often very energy consumptive and therefore expensive or even not possible at ambient temperatures. At low temperatures, many materials become brittle so that they can be grinded more effectively. To achieve these temperatures, the materials are presently cooled with liquid nitrogen (LN2), which is followed by high operation costs. Cryogenic grinding is a proven Technology that is extremely effective, especially for plastics and rubbers, according to Frank Burmester, an engineer with industrial gas supplier Air Products in Germany. But as he pointed out: “Unfortunately, all too often it’s put in a box marked ‘too expensive’”. Now a new independent pilot plant and consultancy service dedicated to cryogenic grinding is set to change engineers’ perceptions of this method of size reduction Based at Oberhausen in the Ruhr area of Germany, the facility is run by Fraunhofer Umsicht, a research institution specialising in environmental, safety and energy technology that forms part of Germany’s Fraunhofer Gesellschaft. The 2 0 0 kg/h pilot plant, which is equipped with six different mills, was started up on 10 November.“This plant is unique – no university or company in the world has such a wonderful facility for cryogenic grinding,” said Burmester. Air Products is supporting the project along with several manufacturers of grinding equipment, and Burmester has been closely involved. Notable features, he says, are the use of mechanical refrigeration alongside liquid nitrogen, and a control system based on a neural network. At Fraunhofer UMSICHT, a low-temperature fine-grinding plant in technical scale was erected for research. Investigations for optimisation of cooling equipment resulted in the development of an innovative technology based on cooling technology.With this technology, the usage of LN2 could be dramatically reduced.The contribution presents some results of our research in the fields mentioned above. A discussion of the new developments compared to the established techniques will complete the presentation. Keywordscryogenic grinding; lN2-consumption; cooling of granulate materials; alternative technology; cooling equipment 1-INTRODUCTION Historically, cryogenic grinding solutions have been used for hard-to-grind or specialist materials, particularly tough materials like plastics and rubbers, and to date have not been widely used in the production of pharmaceuticals and nutraceuticals.However, increased demand for ultra-fine grinding technologies and, in particular, the need to control particle size and maximise yields and throughputs, is encouraging many pharmaceutical processors to review their technological options. We can provide full systems or Component parts, including flow controls, control panels, cooling conveyor and tunnel freezers. Our systems use liquid nitrogen to cool and control the temperature of your product or mill so you can grind more efficiently in an inert atmosphere. They can help you. Increase production rates, improve product quality, achieve finer particle size and more uniform particle distribution, facilitate difficult material separation and prevent explosion. Our cryogenic specialists can help you determine which system is best for your operation based on your current system, the material you process and your goals. Generally the term cryogenics refers to the science of very low temperatures. Though, this is not specifically defined and can be referred to the temperatures lower than 120°K, the boiling point of air (Timmerhaus and Reed 2007) or 100°K (Karassik et al. 2008). Typical cryogens are usually in the form of liquid gases and can be defined as liquid nitrogen (LN2), oxygen, helium (LHe), methane, ethane and argon. However, in machining, sometimes temperatures higher than 100°K are also considered by some authors as cryogenics e.g. cryogenic machining using liquid and/or solid carbon dioxide. The efforts on liquefying permanent gases goes back to the mid-18th century and the development of the first two thermodynamic laws, followed by liquefaction of oxygen (1877), nitrogen, hydrogen and finally helium in 1908 (Kalia 2009, Timmerhaus and Reed2007, Dhokia 2009). The word “cryogenic” was first used by Heike Kamerlingh Onnes in 1894 as an adjective in the title of his paper “On the cryogenic laboratory at Leiden and on the production of very low temperatures” (Timmerhaus and Reed 2007).The early industrial usage of cryogenic technology was limited to the use of liquid oxygen particularly in oxygen-acetylene welding and oxygen furnaces 347 International Journal of Engineering Research & Technology (IJERT)