Digital signal processing
We introduce a new database of voice recordings with the goal of supporting research on vulnerabilities and protection of voice-controlled systems (VCSs). In contrast to prior efforts, the proposed database contains both genuine voice commands and replayed recordings of such commands, collected in realistic VCSs usage scenarios and using modern voice assistant development kits.
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Spoken Indian Language Identification Database
(9 languages, 8 different utterance lengths)
Languages
- Assamese
- Bengali
- Gujarati
- Hindi
- Kannada
- Malayalam
- Marathi
- Tamil
- Telugu
Durations
- 30 sec
- 10 sec
- 5 sec
- 3 sec
- 1 sec
- 0.5 sec
- 0.2 sec
- 0.1 sec
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Dataset used for "A Machine Learning Approach for Wi-Fi RTT Ranging" paper (ION ITM 2019). The dataset includes almost 30,000 Wi-Fi RTT (FTM) raw channel measurements from real-life client and access points, from an office environment. This data can be used for Time of Arrival (ToA), ranging, positioning, navigation and other types of research in Wi-Fi indoor location. The zip file includes a README file, a CSV file with the dataset and several Matlab functions to help the user plot the data and demonstrate how to estimate the range.
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We conducted an undersea magnetic induction (MI) communication experiment in the South China Sea to demonstrate the feasibility of a rotating permanent magnet transmitter. The rotating permanent magnet transmitter is placed on the floating platform for generating the inductive magnetic field, and a ferrite-rod coil with the glue-filled waterproof seal is hung in the seawater as a receiving antenna. This data is a received magnetic signal at a depth of 30 m in seawater.
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This dataset accompanies a paper titled "Detection of Metallic Objects in Mineralised Soil Using Magnetic Induction Spectroscopy".
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This paper presents a novel implementation scheme
of the essential circuit blocks for high performance, full-precision
Booth multipliers leveraging a hybrid logic style. By exploiting
the behavior of parasitic capacitance of MOSFETs, a carefully
engineered design style is employed to reduce dynamic power dissipation
while improving the glitch immunity of the circuit blocks.
The circuit-level techniques along with the proposed signal-flow
optimization scheme prevent the generation and propagation
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This paper applies AI (artificial intelligence) technology to analyze low-dose HRCT (High-resolution chest radiography) data in an attempt to detect COVID-19 pneumonia symptoms. A new model structure is proposed with segmentation of anatomical structures on DNNs-based (deep learning neural network) methods, relying on an abundance of labeled data for proper training.
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Dataset asscociated with a paper in IEEE Transactions on Pattern Analysis and Machine Intelligence
"The perils and pitfalls of block design for EEG classification experiments"
DOI: 10.1109/TPAMI.2020.2973153
If you use this code or data, please cite the above paper.
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This work develops a novel power control framework for energy-efficient powercontrol in wireless networks. The proposed method is a new branch-and-boundprocedure based on problem-specific bounds for energy-efficiency maximizationthat allow for faster convergence. This enables to find the global solution forall of the most common energy-efficient power control problems with acomplexity that, although still exponential in the number of variables, is muchlower than other available global optimization frameworks.
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