On the Noisy Feedback Capacity of Gaussian Broadcast Channels

It is well known that, in general, feedback may enlarge the capacity region of Gaussian broadcast channels. This has been demonstrated even when the feedback is noisy (or partial-but-perfect) and only from one of the receivers. The only case known where feedback has been shown not to enlarge the capacity region is when the channel is physically degraded (El Gamal 1978, 1981). In this paper, we show that for a class of two-user Gaussian broadcast channels (not necessarily physically degraded), passively feeding back the stronger user's signal over a link corrupted by Gaussian noise does not enlarge the capacity region if the variance of feedback noise is above a certain threshold.Comment: 5 pages, 3 figures, to appear in IEEE Information Theory Workshop 2015, Jerusale

Role of phosphate solubilizing fungi during phosphocompost production and their effect on the growth of tomato (Lycopersicon esculentum L) plants

Experiments were conducted to evaluate the effect of phosphate solubilizing fungi (Aspergillus awamori and Trichoderma viride) in phosphocompost preparation along with low grade rock phosphate. Co-inoculation of phosphate-solubilizing fungi significantly increased the nutrient value of the compost that explores high P-solubilizing potential of A.awamori and T.viride which can be exploited for the solubilization of fixed phosphates thereby enhancing soil fertility and plant growth. Rock phosphate application along with phosphate solubilizing fungi increased 69.2% acid phosphatase and 65% alkaline phosphatase activity over ordinary compost. With co-inoculation, maximum P content (64.3%) was observed followed by single inoculation with A.awamori (62.2%). The present findings revealed that phosphate solubilizing fungi can interact positively in promoting nutrient content of compost and plant growth leading to improved yield

Scaling Active Search using Linear Similarity Functions

Active Search has become an increasingly useful tool in information retrieval problems where the goal is to discover as many target elements as possible using only limited label queries. With the advent of big data, there is a growing emphasis on the scalability of such techniques to handle very large and very complex datasets. In this paper, we consider the problem of Active Search where we are given a similarity function between data points. We look at an algorithm introduced by Wang et al. [2013] for Active Search over graphs and propose crucial modifications which allow it to scale significantly. Their approach selects points by minimizing an energy function over the graph induced by the similarity function on the data. Our modifications require the similarity function to be a dot-product between feature vectors of data points, equivalent to having a linear kernel for the adjacency matrix. With this, we are able to scale tremendously: for $n$ data points, the original algorithm runs in $O(n^2)$ time per iteration while ours runs in only $O(nr + r^2)$ given $r$-dimensional features. We also describe a simple alternate approach using a weighted-neighbor predictor which also scales well. In our experiments, we show that our method is competitive with existing semi-supervised approaches. We also briefly discuss conditions under which our algorithm performs well.Comment: To be published as conference paper at IJCAI 2017, 11 pages, 2 figure

ICT-based reforms in local government decision-making in the gram panchayats of Kerala

The beneficial impact of computerisation can be felt in all elements that contribute to decision-making in panchayats in the state of Kerala. However, even though computerisation is bringing about immense improvements compared to traditional administrative practices, but scope still remains for further improvement. Instead of the 'as it is' computerisation that is mostly carried out a process based approach is needed

The Park of Renewable Energy geoethical project

The Park of Renewable Energy is an environmental technology park in the middle of Italy that has an innovative integrated system for the production of renewable energy. Recently, the Park launched a public invitation: to become part of a great widespread community for the production of renewable energy, and to promote energy conservation and a sustainable lifestyle. This empowerment process that turns consumers into energy producers – and also into those who convey the culture of sustainability – might, over time, give life to a community that actually lives according to the geoethical principles of biosustainability. The route for the identification and dissemination of the Park of Renewable Energy community is an interesting example of the generative process, whereby rather than doggedly pursuing a predetermined objective, such as a model to be implemented, the actors involved, “look for directions and values that are inherent in the means available” [Bateson 2000], including communication networks and methodologies of social participation. The community components focus their attention on the action and relationship effects, rather than on ways to reach a predefined goal. In this perspective, the Park of Renewable Energy experience aims to become an interesting object of observation and reflection for its green ethics. This ecological approach promises unexpected new creations: there is a chance we will at last see the birth of a sustainable form of social organization adapted to the human community