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The paper proposes a high gain, metamaterial based super wideband (SWB) antenna. The SWB antenna has two inverted U slots which are responsible for two notches at 3.5 GHz and 5.5 GHz frequencies. A flower-shaped slot is etched from the radiator to obtain the SWB characteristics. The super wideband antenna has dimensions of 30×35 ×1.5 mm 3 with FR4 substrate. The antenna has a frequency bandwidth of 3.1 GHz -15 GHz for S11 < -10dB. A metamaterial unit cell is designed and simulated for permittivity and permeability characteristics. This shows a negative refractive index in the band of 2.4 GHz to 8 GHz and 8.2 GHz to 9 GHz. A 3×3 array of metamaterial cells is used as a superstrate for the improvement of the gain characteristics. The fabricated prototype SWB antenna with superstrate has measured frequency bandwidth 3.1-15 GHz with notched bands at 3.5 GHz and 5.5 GHz. The experimental and simulated results are in line with each other.

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This paper describes our proposed system & experiments performed to detect contextual emotion in texts for SemEval 2019 Task 3. We exploit sentiment information, syntactic patterns & semantic relatedness to capture diverse aspects of the text. Word level embeddings such as Glove, FastText, Emoji along with sentence level embeddings like Skip-Thought, DeepMoji & Unsupervised Sentiment Neuron were used as input features to our architecture. We democratize the learning using ensembling of models with different parameters to produce the final output. This paper discusses comparative analysis of the significance of these embeddings and our approach for the task.

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