The main objective of fog removal algorithm is to estimate the airlight map for the given image and then perform the necessary operations on the image in order to overcome the fog in the image and enhance the quality of the image. The dark channel prior method of fog removal is more suitable and time-saving in real-time systems. In this paper, an efficient approach for fog removal of foggy images based on the combination of dark channel prior and genetic algorithm is presented. It is found that the proposed method is more suitable for obtaining the better quality of the image than the most of the existing methods.
In September 2019, young people in India led a series of protest events, taking inspiration from a digital campaign for a series of Climate Strikes. Our article explores these events in the context of “millennial India,” particularly in terms of the networks that emerged in the course of climate action in two different regions. By using evidence from Delhi in the north and Bengaluru in the south, we also develop a comparative sociology of digital-first environmental movements and show how the significance of Twitter can only be understood in relation to the formations of social capital on the ground.
The cycle of abstraction-reconstruction, which occurs as a fundamental principle in the development of culture and in cognitive processes, is described and analyzed. This approach leads to recognition of boundary conditions for and directions of probable development of cognitive tools. It is shown how the transition from a conventional Japanese-English character dictionary to a multi-dimensional language database is an instance of such an abstraction-reconstruction cycle. The individual phases in the design of a multidimensional language database based upon different computer software technologies are investigated in regard to the underlying cycle, The methods used in the design of a multi-dimensional language database include the use of UNIX software tools, classical database methods as well as the use of search engines based upon f i l l text search. Several directions of application and extension for multi-dimensional language databases are discussed.
Misinformation easily spreads on social media and fact-checkers have an important role in correcting falsehoods. Most misinformation is of a partisan nature and appeals selectively to users on the basis of ideology. Thus, it is possible that fact checks may not overcome existing ideological divisions on social media. We examine this separately for a slice of Twitter users, following certain partisan outlets from India and the US. In both cases, users of left-leaning news outlets are more likely to follow and share content by fact checkers. Followers of right-leaning outlets rarely follow or amplify fact checkers and only selectively engage to reply to posts by fact checkers. Our analysis of 7mn partisan news users from two of the world’s largest democracies suggests that exposure to fact-checking therefore remains largely restricted to left-leaning Twitter users with little evidence that these interventions penetrate among right-leaning slices, where partisan misinformation also circulates
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