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Action Unit (AU) detection from facial images is an important classification task in affective computing. However most existing approaches use carefully engineered feature extractors along with off-the-shelf classifiers. There has also been less focus on how well classifiers generalize when tested on different datasets. In our paper, we propose a(More)
The clinical efficacy of the widely used chemotherapeutic drug methotrexate (MTX) is limited due to its associated hepatotoxicity. Pomegranate polyphenols are of huge health benefits and known to possess remarkable antioxidant properties capable of protecting normal cells from various stimuli-induced oxidative stress and cell death. In this study, we(More)
Speech emotion recognition is an important problem with applications as varied as human-computer interfaces and affective computing. Previous approaches to emotion recognition have mostly focused on extraction of carefully engineered features and have trained simple classifiers for the emotion task. There has been limited effort at representation learning(More)
There has been a lot of prior work on representation learning for speech recognition applications, but not much emphasis has been given to an investigation of effective representations of affect from speech, where the paralinguistic elements of speech are separated out from the verbal content. In this paper, we explore denoising autoencoders for learning(More)
Molecular mechanisms involved in arsenic-induced toxicity are complex and elusive. Liver is one of the most favored organs for arsenic toxicity as methylation of arsenic occurs mostly in the liver. In this study, we have selected a range of environmentally relevant doses of arsenic to examine the basis of arsenic toxicity and the role of pomegranate fruit(More)
Green tea (GT)-based chemoprevention has shown promising results in various cancer models. However, the effective dose may not be far from the toxic dose because of inefficient systemic delivery and limited bio-availability of GT polyphenols. We have used GT polyphenols to successfully reduce gold to corresponding gold nanoparticles (NPs) in a single step;(More)
This paper describes a method for improving the final accuracy and the convergence speed of Particle Swarm Optimization (PSO) by adapting its inertia factor in the velocity updating equation and also by adding a new coefficient to the position updating equation. These modifications do not impose any serious requirements on the basic algorithm in terms of(More)
This paper applies the Differential Evolution (DE) algorithm to the task of automatic fuzzy clustering in a Multi-objective Optimization (MO) framework. It compares the performances of two multi-objective variants of DE over the fuzzy clustering problem, where two conflicting fuzzy validity indices are simultaneously optimized. The resultant Pareto optimal(More)
Invasive weed optimization (IWO) has been found to be a simple but powerful algorithm for function optimization over continuous spaces. It has reportedly outperformed many types of evolutionary algorithms and other search heuristics when tested over both benchmark and real-world problems. However the performance of most search heuristics deteriorates(More)