<p>The proliferation of efficient edge computing has enabled a paradigm shift of how we monitor and interpret urban air quality. Coupled with the dense spatiotemporal resolution realized from large-scale wireless sensor networks, we can achieve highly accurate realtime local inference of airborne pollutants. In this paper, we introduce a novel Deep Neural Network architecture targeted at latent time-series regression tasks from continuous, exogenous sensor measurements, based on the Transformer encoder scheme and designed for deployment on low-cost power-efficient edge processors.

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15 Views

In this project, we propose a new comprehensive realistic cyber security dataset of IoT and IIoT applications, called Edge-IIoTset, which can be used by machine learning-based intrusion detection systems in two different modes, namely, centralized and federated learning. Specifically, the proposed testbed is organized into seven layers, including, Cloud Computing Layer, Network Functions Virtualization Layer, Blockchain Network Layer, Fog Computing Layer, Software-Defined Networking Layer, Edge Computing Layer, and IoT and IIoT Perception Layer.

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201 Views

These data is used to test the performance of the proposed in-motion inital alignment method.

 

These data includes the raw data of inertial measurement units, the raw data of GPS and the reference attitude angles.

All these data is simulated.

The frequency of inertial measurement units and GPS are 100Hz and 1Hz, respectively.

The data are explained below:

imu=[gryo;acc;time]       Unit is rad; m/s; s

GPS=[lat;lon;height;ve;vn;vu]; Unit is rad; rad; m; m/s; m/s; m/s

Ref_angle=[pitch;roll;yaw];      Unit is rad; rad; rad

 

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This dataset consists of the training and the evaluation datasets for the LiDAR-based maritime environment perception presented in our journal publication "Maritime Environment Perception based on Deep Learning." Within the datasets, LiDAR raw data are processed using Deep Neural Networks (DNN). In the training dataset, we introduce the method for generating training data in Gazebo simulation. In the evaluation datasets, we provide the real-world tests conducted by two research vessels, respectively.

 

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125 Views

Cu (II) ion has potential roles in a lot of living metabolisms that its detection and removal are extremely important for flagship branches of science. In this paper, fluorescent and easy-make silica gel immobilized BODIPY were successfully prepared via a simple synthesis procedure for the rapid recognition of Cu (II) ions. The optimal emission and excitation wavelength of the synthesized hybrid material, Si-APTMS-BODIPY, was 543 nm and 460 nm, respectively.

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3 Views

We upload the orig.inal measured ecg and impedance data, in xlxs forms, the 1st column is sampling time,the second is amplitude. We use these files and OriginPro to  verify the correctness of the model. And use matlab to verify the algorithm's  effectiveness.. More information if you needed,, pls connect the following email: 17112020021@fudan.edu.cn

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25 Views

Any work using this dataset should cite the following paper:

 Nirmalya Thakur and Chia Y. Han, "An open access dataset of tweets related to exoskeletons and 100 research questions, " arXiv [cs.CY], 2021.

 

Abstract

 

Instructions: 

Please refer to the paper

Nirmalya Thakur and Chia Y. Han, "An open access dataset of tweets related to exoskeletons and 100 research questions", arXiv [cs.CY], 2021.

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433 Views

 

The dataset contains temperature measurements taken with an 8x8 infrared array (Panasonic Grid-EYE) over a period of three weeks during 2018 in Bucharest, Romania, in an educational facility.

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170 Views

The Firearm Recoil Dataset was collected utilizing a wrist worn accelerometer to record the recoil generated from one subject’s use of 15 different firearms of the Handgun, Rifle and Shotgun class. The type of the firearm based on its ability to auto-load or not is also denoted. 

Instructions: 

Datasets are broken up into seperate CSV files for each individual firearm. Details associated with the firearm utilized and data collection specifications is outlined in the Readme File. If you use this datasets for your research, please cite the following paper:

Md. Abdullah Al Hafiz Khan, David Welsh, and Nirmalya Roy. Firearm Detection Using Wrist Worn Tri-Axis Accelerometer Signals, in Proceedings of the 4th Workshop on sensing systems and applications using wrist worn smart devices (WristSense’18), co-located with PerCom, March 2018

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255 Views

Skeleton datasets for Normal, Antalgic, Stiff legged, Lurching, Steppage, and Trendelenburg gaits.

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281 Views

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