Does (linguistic) Computation Need Culture to Make Cognition Viable?

AbstractThis paper will deal with how and in what ways (linguistic) computation as part of linguistic competence may relate to aspects of culture in the context of the cognition which becomes viable by being grounded in the possible conjunction of mental computations and cultural praxis. The possibilities of cultural capacities are enormous across societies and/or cultures, but linguistic computations as have been postulated are restricted by the nature of constraints specific to natural language. The purpose of this paper is to see the consequences of how these two can make cognition viable

Qualitative and Quantitative Analysis of Aflatoxins in Dry Fruits and Nuts from Central India

In central part of India, dry fruits and nuts are mostly sold in loose conditions and hence may get fungal infections, and may have aflatoxins to the levels beyond the safe limits. The present study is an attempt to showcase the present scenario of aflatoxins in dry fruits and nuts from Central India, both qualitatively and quantatively. Out of 84 samples, 15 were found to have the presence of at least one aflatoxin. HPLC detection showed that AFB1 is the major aflatoxin. The total aflatoxins were found in the range of 25.4 - 393.51 μg kg-1, which is beyond the safe limit set by regulatory authorities. Further, dry figs were the most contaminated among tested dry fruits, and 5 out 12 samples (41.6%) were contaminated, followed by cashew nuts (33.3%). Samples sold in loose packing were found more contaminated with aflatoxins. The study advocates that selling of such dry fruits in loose form should be banned by the regulatory authorities

Flag Aggregator: Scalable Distributed Training under Failures and Augmented Losses using Convex Optimization

Modern ML applications increasingly rely on complex deep learning models and large datasets. There has been an exponential growth in the amount of computation needed to train the largest models. Therefore, to scale computation and data, these models are inevitably trained in a distributed manner in clusters of nodes, and their updates are aggregated before being applied to the model. However, a distributed setup is prone to Byzantine failures of individual nodes, components, and software. With data augmentation added to these settings, there is a critical need for robust and efficient aggregation systems. We define the quality of workers as reconstruction ratios $\in (0,1]$, and formulate aggregation as a Maximum Likelihood Estimation procedure using Beta densities. We show that the Regularized form of log-likelihood wrt subspace can be approximately solved using iterative least squares solver, and provide convergence guarantees using recent Convex Optimization landscape results. Our empirical findings demonstrate that our approach significantly enhances the robustness of state-of-the-art Byzantine resilient aggregators. We evaluate our method in a distributed setup with a parameter server, and show simultaneous improvements in communication efficiency and accuracy across various tasks. The code is publicly available at https://github.com/hamidralmasi/FlagAggregato

Carbon credit for sustainable developement

The Greenhouse Gases which include Carbon dioxide, Methane and also other oxides on account of incomplete combustion substantially disturb the balance of the heat in the earth’s atmosphere leading to warming of the atmospheric temperature which is called as Global Warming and considered a major threat to life on earth. In today’s world situation, it is very much necessary to find out the solution for the global impact of pollution for the survival of life. The rules & regulations which are meant for the control of pollution are seen to be somewhat ineffective. One of the reasons behind the failure of such systems is that there are no attractive proposals in front of industries. The solution requires obviously the attraction in terms of economy. With this, the Kyoto Protocol, 1997, supported by United Nations Framework Convention on Climate Change (UNFCCC) gave a wonder full solution which may prove to be the golden midway between the reduction in pollution & the economy. Sustainable and clean renewable energy systems such as hybrid solar/wind electric generators can be used to eliminate or reduce carbon dioxide emissions by replacing old diesel, oil, gas or coal fired electric generators which emit greenhouse gases that produce global warming. Carbon sequestration credits or offsets are calculated by the amount of carbon emissions that would have been emitted if a diesel or other traditional polluting electric generator was used to produce the same amount of electricity. Companies and electric utilities in countries can buy these emission reduction carbon credits to replace the emissions from their coal burning electric power plants to meet regulatory requirements