5,507 research outputs found
I Was Addicted to Sex With Married Women
No full textAs a young man, Akhil Sharma revelled in the most dangerous of liaisons, having sex with other men's wives – until the thrill began to pall
Maldives Resorts: Eco-Friendly Vacations
No full textLuxurious, exclusive and remote, the Maldives are the ultimate beach escape. They’re also a case study in the risks of global warming. Writer Akhil Sharma visits the country’s most eco-friendly resorts and discovers a remarkable cuisine worth protecting
Recollections of a Hindu Hedonist
No full textNovelist Akhil Sharma grew up in a teetotaling Indian household. Here, he tells how discovering a passion for great wine helped him create a new identity out of a painful past
Ekeland type variational principle for set-valued maps in quasi-metric spaces with applications
No full textIn this paper, we derive a fixed point theorem, minimal element theorems and Ekeland type variational principle for set-valued maps with generalized variable set relations in quasi-metric spaces. These generalized variable set relations are the generalizations of set relations with constant ordering cone, and form the modern approach to compare sets in set-valued optimization with respect to variable domination structures under some appropriate assumptions. At the end, we give application of these variational principles to the capability theory of well-beings via variational rationality.</p
Interview with Lakshmi Raj Sharma, Author of The Tailor’s Needle
No full textInterview with Indian writer Lakshmi Raj Sharma, author of 'The Tailor's needle
Characterizations of robust optimality conditions via image space analysis
No full textIn this paper, we consider general scalar robust optimization problems and study the characterizations for optimality conditions in the general vector spaces where we do not require any topology on the considered space. By using the image space analysis and nonlinear separation function, we derive some necessary and sufficient optimality conditions, especially saddle point sufficient optimality conditions for scalar robust optimization problems. Moreover, we discuss the validity and effectiveness of our results for the shortest path problem.</p
Predicting the infuence of Urban vacant lots on neighborhood property values
No full textVacant lots are municipally-owned land parcels which were acquired post-abandonment or due to tax foreclosures. With time, failure to sell or find alternate uses for vacant lots results in them causing adverse effects on the health and safety of residents, and cost the city both directly and indirectly. Although existing research has tried to define these impacts, cities need quantifiable evidence from within the city to make planning decisions based on these studies. Moreover, trying to understand the impact of vacant lots in an uncontrolled setting makes it difficult to perform A key problem with existing methodologies is that they tend to look at the city as a whole, while ignoring the diverse socioeconomic factors at play. Altogether, city planners are left with little or no actionable information to prioritize conversion of vacant lots. In contrast, for our research we try to model the city as blocks, census tracts and neighborhoods while using relevant features to capture key demographic, economic and geographic characteristics. In addition, we build a deep learning model to quantify the impact of vacant lots on changing property values so as to recommend conversions that yields the maximum benefit through property value tax increase. Our results indicate that our model is able to capture the relationship between vacant lots and property values better than conventionally used algorithms and data models. Further, our model specifically caters to small and mid size cities, which are often neglected in the mainstream urban computing research.Interactive Intelligenc
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