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Computational Intelligence

Due to the smaller size, low cost, and easy operational features, small unmanned aerial vehicles (SUAVs) have become more popular for various defense as well as civil applications. They can also give threat to national security if intentionally operated by any hostile actor(s). Since all the SUAV targets have a high degree of resemblances in their micro-Doppler (m-D) space, their accurate detection/classification can be highly guaranteed by the appropriate deep convolutional neural network (DCNN) architecture.

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In the view of national security, radar micro-Doppler (m-D) signatures-based recognition of suspicious human activities becomes significant. In connection to this, early detection and warning of terrorist activities at the country borders, protected/secured/guarded places and civilian violent protests is mandatory.

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The dataset includes active power measurements for a residential dwelling (apartment) located in Bucharest, Romania, collected at 1s second reporting rate over several months.
Always-on appliances include the refrigerator and the wireless router. Several other appliances are installed in the residential unit: washing machine, lighting fixtures, electrical iron, vacuum cleaner, various ICT charging devices, and air conditioning (seldom used).

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In the last few years, several organizations have manifested their concern over the increase in use of Hateful Speech or Hate Speech for short, this concept refers to forms of expression or audio-visual content that encourage discrimination or violence against individuals or groups solely based on their gender, sexual orientation, ethnicity, religion or nationality.

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<p>Numerical comparison serves as a major tool in evaluating the performance of optimization algorithms, especially nondeterministic algorithms, but existing methods may suffer from a ‘cycle ranking’ paradox and/or a ‘survival of the nonfittest paradox. This paper searches for paradox-free data analysis methods for numerical comparison. It is discovered that a class of sufficient conditions exist for designing paradox-free analysis. Rigorous modeling and deduction are applied to a class of profile methods employing a filter.

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Please cite the following paper when using this dataset:

N. Thakur and C.Y. Han, “An Exploratory Study of Tweets about the SARS-CoV-2 Omicron Variant: Insights from Sentiment Analysis, Language Interpretation, Source Tracking, Type Classification, and Embedded URL Detection,” Journal of COVID, 2022, Volume 5, Issue 3, pp. 1026-1049

Abstract

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This dataset supports a review and an in-depth analysis on the environmental impacts of integrated circuits (ICs). The paper is currently under review.

We gathered data from foundry reports, industry roadmaps, scientific literature, and commercial state-of-the-art LCA databases. All assumptions are detailed. 

More information can be found on the GitHub repository : https://github.com/ThibaultPirson/environmental-footprint-IC.

 

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