Sensors
In this project, an LSTM-based Model Predictive Controller (LSTM-MPC), with 200 neurons of each layer, is designed to have a highly efficient control on the temperature. The resulted dataset is attached, for further considerations.
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700 Views
Recently, there has been a resurgence of interest in multimode optical fibers illuminated by a white light source. Largely, in the anticipation of many integrated applications in the biomedical domain and spectral sensing benefiting from the broad spectral range and high numerical aperture. Along these lines, the output light from these fibers can be captured by the physics of partially coherent sources. Yet, the sheer complexity arising from the interplay between partial coherence and microstructure transfer function has posed fundamental challenges in deciphering their response.
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70 Views
The dataset contains spectra of teabags of three different brands collected from different environments. It is intended to be used to evaluate the impact of the operating environment on hand-held NIR spectrometers.
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118 Views
In this dataset, we provided the raw analog-to-digital-converter (ADC) data of a 77GHz mmwave radar for the automotive object detection scenario. The overall dataset contains approximately 19800 frames of radar data as well as synchronized camera images and labels. For each radar frame, its raw data has 4 dimension: samples (fast time), chirps (slow time), transmitters, receivers. The experiment radar was assembled from the TI AWR 1843 board, with 2 horizontal transmit antennas and 4 receive antennas.
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5866 Views
In this dataset, we provided the raw analog-to-digital-converter (ADC) data of a 77GHz mmwave radar for the carry object detection scenario. The overall dataset contains approximately 3000 frames of radar data as well as synchronized camera images and labels. For each radar frame, its raw data has 4 dimensions: samples (fast time), chirps (slow time), transmitters, and receivers. The experiment radar was assembled from the TI cascaded-chip TIDEP-01012 board, with 12 transmit antennas and 16 receive antennas.
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1363 Views
This data is designed for covariance matrix completion to train the neural networks.
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81 Views
This study reports the properties and the sensing mechanism of Pd nanoparticles (PdNPs) decorated n+/n-/n+ double-junction silicon nanobelt (SNB) device as hydrogen (H2) gas sensor. The SNB devices are prepared via CMOS process. Plasma-enhanced atomic layer deposition (PEALD) is adopted for PdNPs deposition as sensing material on the Al2O3 dielectric of SNB devices. The PdNPs-decorated SNB devices working at room temperature are characterizedat H2 concentration ranging from 10 to 1000 ppm.
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17 Views
This study reports the properties and the sensing mechanism of Pd nanoparticles (PdNPs) decorated n+/n-/n+ double-junction silicon nanobelt (SNB) device as hydrogen (H2) gas sensor. The SNB devices are prepared via CMOS process. Plasma-enhanced atomic layer deposition (PEALD) is adopted for PdNPs deposition as sensing material on the Al2O3 dielectric of SNB devices.PEALD of PdNPs provides high conformity and fine control of the particle size. The PdNPs-decorated SNB devices working at room temperature are characterizedat H2 concentration ranging from 10 to 1000 ppm.
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73 Views
This study reports the properties and the sensing mechanism of Pd nanoparticles (PdNPs) decorated n+/n-/n+ double-junction silicon nanobelt (SNB) device as hydrogen (H2) gas sensor. The SNB devices are prepared via CMOS process. Plasma-enhanced atomic layer deposition (PEALD) is adopted for PdNPs deposition as sensing material on the Al2O3 dielectric of SNB devices.PEALD of PdNPs provides high conformity and fine control of the particle size. The PdNPs-decorated SNB devices working at room temperature are characterizedat H2 concentration ranging from 10 to 1000 ppm.
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55 Views
This dataset contains continuous gesture data for both Chinese and English, including 14 Chinese characters and 4 English words. The Chinese characters are: 不 (bù), 程 (chéng), 刀 (dāo), 工 (gōng), 古 (gǔ), 今 (jīn), 力 (lì), 刘 (liú), 木 (mù), 石 (shí), 土 (tǔ), 外 (wài), 中 (zhōng), 乙 (yǐ). The English words included are: 'can', 'NO', 'Who', 'yes'.
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196 Views