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This data is for a compact terahertz (THz) SPICE/ADS model based on the extended EKV MOSFET model with channel segmentation but accounting for the distributed Drude inductance representing the electron inertia critical at THz frequencies. 

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We introduced the task of acoustic question answering (AQA) in https://arxiv.org/abs/1811.10561.

A second version of the dataset was introduced in https://arxiv.org/abs/2106.06147

This dataset aim to promote research in the acoustic reasoning area.

It comprise Acoustic Scenes and multiple questions/answers for each of them.

Each question is accompanied by a functional program which describe the reasoning steps needed in order to answer it.

 

The dataset is constitued is separated in 3 sets :

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The dataset includes sample indoor and outdoor sequences with considerable variations in illumination.

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The performance of most of the classification models is dependent on the data used for training. The data must be reliable, robust and meticulously labelled. In order to form such a data a systematical approach has been designed and moreover, it should be. The data set was collected from a well-known source, namely Center for Language Engineering available at http://www.cle.org.pk. The corpus available on the website used for prediction contains Urdu Naskh data having 4,325 number of lines and 1, 22284 words. This corpus contains three text files.

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A solenoid-operated valve with DC resistance of about 10.3 Ω was exposed to 50 % RH, its rated temperature of 80 °C, and powered at its rated voltage of 12 VDC. (Note: the valve was unrated with regards to relative humidity, RH.) Using Fourier transform infrared (FTIR) spectroscopy, the insulation material was found to be a combination of polystyrene and polyethylene terephthalate. The wire gauge was not disclosed in the valve information sheet.

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Occlusion, glare and secondary reflections formed due to and on the spectacles - results in poor detection, localization, and recognition of eye/face features. We term all the problems related to the usage of spectacles as The spectacle problem. Though several studies on the spectacle detection and removal have been reported in the literature, the study focusing on spectacle problem removal is very limited. One of the main reasons being, the nonavailability of a facial image database highlighting the spectacle problems.

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This database has five different linter quality classes (short cotton fibers), linter has wide applicability in the production of surgical tissue, paper money among other applications. The images available were used to classify the product in an industrial process, through the use of computer vision techniques.

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