70 research outputs found
Radon-Like Features and their Application to Connectomics
In this paper we present a novel class of so-called Radon-Like features, which allow for aggregation of spatially distributed image statistics into compact feature descriptors. Radon-Like features, which can be efficiently computed, lend themselves for use with both supervised and unsupervised learning methods. Here we describe various instantiations of these features and demonstrate there usefulness in context of neural connectivity analysis, i.e. Connectomics, in electron micrographs. Through various experiments on simulated as well as real data we establish the efficacy of the proposed features in various tasks like cell membrane enhancement, mitochondria segmentation, cell background segmentation, and vesicle cluster detection as compared to various other state-of-the-art techniques.Engineering and Applied Science
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Maximizing all margins: Pushing face recognition with Kernel Plurality
We present two theses in this paper: First, performance of most existing face recognition algorithms improves if instead of the whole image, smaller patches are individually classified followed by label aggregation using voting. Second, weighted plurality voting outperforms other popular voting methods if the weights are set such that they maximize the victory margin for the winner with respect to each of the losers. Moreover, this can be done while taking higher order relationships among patches into account using kernels. We call this scheme Kernel Plurality. We verify our proposals with detailed experimental results and show that our framework with Kernel Plurality improves the performance of various face recognition algorithms beyond what has been previously reported in the literature. Furthermore, on five different benchmark datasets - Yale A, CMU PIE, MERL Dome, Extended Yale B and Multi-PIE, we show that Kernel Plurality in conjunction with recent face recognition algorithms can provide state-of-the-art results in terms of face recognition rates.Engineering and Applied Science
Quantifying Spatio Temporal Changes in Coastal Buit-up area of South Goa based on Landsat Imageries using Google Earth Engine
Urban flooding has become a significant concern across many towns and cities in the Asia Pacific. Vulnerabilityand its components must be understood in order to minimize flood risks. Rapid urban growth occurs in developing countries,resulting from unplanned settlements growing along the rivers, and coastlines are at greater risk. On average, a total of 40%of the world’s population lives in narrow coastal belts that take up 7% of the total world land area. Coastal areas areurbanizing at an unprecedented rate that is posing a common threat to humans and ecosystems. Low-lying coastal areas areespecially susceptible to climate change related coastal hazards such as; sea level rise, storm surge, coastal flooding, landsubsidence etc.This study has been carriedoutacross four talukas of South Goa district, India's smallest state, locatedalong the Arabian sea. The low-lying coastal belt of South Goa district is dotted with world famous sandy beaches ofPalolem, Agonda, Colva etc. which attract millions of tourists every year. The present study has assessed the spatio-temporalgrowth of built-up land in low-lying coastal areas (Marmugao, Salcette, Quepem and Canacona) of South goa district.GoogleEarthEngineplatformwasusedtoestimateNormalizedDifferenceBuildIndex(NDBI)basedonLandsatETM+/OLI imageries for 2009, 2015 and 2020 to determine and map spatio-temporal changes in the total built-up area. Theresult revealed that there had been a rapid built-up area increment in South goa coastal belt by 24.94 Sq. Km between 2009(88.46 Sq. Km) and 2015 (113.40 Sq. Km) and by 15.14 Sq. Km between 2015 (113.40 Sq. Km) and 2020 (128.54 Sq. Km).The main driving force behind this phenomenon is the extensive land use changes for haphazard tourism development (inSalcetteandCanacona)andimmigration(inMarmugao).However,theconversionoftraditionalpaddyfieldsandmodification of natural drainage systemtoincrease built-up areas cansignificantly increase the physical andsocialvulnerability in low lying areas of Salcette and Canacona against the coastal hazards. This study may help urban planners/authoritiestolettheregiondevelopin sustainablemanne
Dissolution rates of various brands of proton pump inhibitors in combination with domperidone: an in vitro study
Background: Drug solubility, bioavailability, and dissolution rates are important in establishing in vivo efficacy. Eight brands of domperidone proton pump inhibitor combination drugs were compared to enable physicians to take an informed decision regarding the dissolution rates of various domperidone-PPI combinations available in the Indian market to allow identification and prescription of the drug with better bioavailability.
Methods: The in vitro dissolution rate of a combination of domperidone-PPI drugs was measured using the United States Pharmacopeia dissolution paddle apparatus. Each flask of the dissolving testing apparatus contained one tablet and 900 mL of the media, which was dissolved in pure water with 1% Tween® stored at 37.4°C. At regular intervals, aliquots were removed, filtered, and the amount of drug released was measured. The cumulative drug release was calculated using a standard formula.
Results: P04 and P07 had the fastest and the slowest onsets of action, respectively. P01 (Omez DSR) and P08 exhibited the longest and the shortest durations of action, respectively. The P05, P06, and P08 formulations had greater particulate matter than the other formulations. Under in vitro conditions, the bioavailability of Omez DSR was nearly two-fold higher than P07 and five-fold higher than P08.
Conclusions: Although P04 exhibited the fastest onset of action, Omez DSR had the longest duration of action, superior bioavailability, and ensured the rapid and continuous release of domperidone. Omez DSR demonstrated superior properties compared with other brands
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Detection of Neuron Membranes in Electron Microscopy Images Using Multi-scale Context and Radon-Like Features
Automated neural circuit reconstruction through electron microscopy (EM) images is a challenging problem. In this paper, we present a novel method that exploits multi-scale contextual information together with Radon-like features (RLF) to learn a series of discriminative models. The main idea is to build a framework which is capable of extracting information about cell membranes from a large contextual area of an EM image in a computationally efficient way. Toward this goal, we extract RLF that can be computed efficiently from the input image and generate a scale-space representation of the context images that are obtained at the output of each discriminative model in the series. Compared to a single-scale model, the use of a multi-scale representation of the context image gives the subsequent classifiers access to a larger contextual area in an effective way. Our strategy is general and independent of the classifier and has the potential to be used in any context based framework. We demonstrate that our method outperforms the state-of-the-art algorithms in detection of neuron membranes in EM images.Engineering and Applied Science
Inhomogeneous polarization evolution resolves a fundamental issue in non-Hermitian transverse optical beam shifts
Depending on the system parameters, the transverse optical beam shift in
reflection can be non-Hermitian with real eigenvalues and non-orthogonal
eigenstates. We reveal that such an unusual resemblance with typical PT
(parity-time)-symmetric systems originates from the beam's momentum domain
polarization evolution. Specifically, for partial reflection, the momentum
domain inhomogeneous polarization evolution of the beam is at the heart of all
the peculiarities in the corresponding eigenspectrum of the transverse shift
operator. These findings put forward the notion of novel non-Hermitian
spin-orbit photonics and enable common polarization optical elements to act as
PT-symmetric non-Hermitian systems
Did Covid-19 lockdown positively affect the urban environment and UN- Sustainable Development Goals?
Nigam, R., Tripathi, G., Priya, T., Luis, A. J., Vaz, E., Kumar, S., Shakya, A., Damásio, B., Kotha, M., & Yu, B. (Ed.) (2022). Did Covid-19 lockdown positively affect the urban environment and UN- Sustainable Development Goals? PLoS ONE, 17(9), 1-21. [e0274621]. https://doi.org/10.1371/journal.pone.0274621This work quantifies the impact of pre-, during- and post-lockdown periods of 2020 and 2019 imposed due to COVID-19, with regards to a set of satellite-based environmental parameters (greenness using Normalized Difference Vegetation and water indices, land surface temperature, night-time light, and energy consumption) in five alpha cities (Kuala Lumpur, Mexico, greater Mumbai, Sao Paulo, Toronto). We have inferenced our results with an extensive questionnaire-based survey of expert opinions about the environment-related UN Sustainable Development Goals (SDGs). Results showed considerable variation due to the lockdown on environment-related SDGs. The growth in the urban environmental variables during lockdown phase 2020 relative to a similar period in 2019 varied from 13.92% for Toronto to 13.76% for greater Mumbai to 21.55% for Kuala Lumpur; it dropped to −10.56% for Mexico and −1.23% for Sao Paulo city. The total lockdown was more effective in revitalizing the urban environment than partial lockdown. Our results also indicated that Greater Mumbai and Toronto, which were under a total lockdown, had observed positive influence on cumulative urban environment. While in other cities (Mexico City, Sao Paulo) where partial lockdown was implemented, cumulative lockdown effects were found to be in deficit for a similar period in 2019, mainly due to partial restrictions on transportation and shopping activities. The only exception was Kuala Lumpur which observed surplus growth while having partial lockdown because the restrictions were only partial during the festival of Ramadan. Cumulatively, COVID-19 lockdown has contributed significantly towards actions to reduce degradation of natural habitat (fulfilling SDG-15, target 15.5), increment in available water content in Sao Paulo urban area(SDG-6, target 6.6), reduction in NTL resulting in reducied per capita energy consumption (SDG–13, target 13.3).publishersversionpublishe
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