Artificial Intelligence
Computer vision and image processing have made significant progress in many real-world applications, including environmental monitoring and protection. Recent studies have shown that computer vision and image processing can be used to quantify water turbidity, a crucial physical parameter in water quality assessment. This paper presents a procedure to determine water turbidity using deep learning methods, specifically, convolutional neural network (CNN). At first, water samples were located inside a dark cabin before digital images of the samples were captured with a smartphone camera.
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a novel two-electrode, frequency-scan electrical impedance tomography (EIT) system for gesture recognition
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The research were incorporated an extended cohort monitoring campaign, validation of an existing exposure model and development of a predictive model for COPD exacerbations evaluated against historical electronic health records.
A miniature personal sensor unit were manufactured for the study from a prototype developed at the University of Cambridge. The units monitored GPS position, temperature, humidity, CO, NO, NO2, O3, PM10 and PM2.5.
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Evaluation data of the experiments for the paper "Comparison of Anomaly Detectors: Context Matters".
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166 Views
This is an ontology used for the identification of common algae involved in harmful algal bloom events. This ontology is used as a guide to determine the algae species to be identified by the expert system.
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In recent years, drones have been used to transport payloads to remote and difficult access areas. A payload delivery with assisted relay system of two unmanned aerial vehicles (UAVs) is implemented. A local and web remote monitoring and control from a ground control station (GCS) for a pre-planned autonomous trajectory flight is developed in this work.
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930 Views
There is an industry gap for publicly available electric utility infrastructure imagery. The Electric Power Research Institute (EPRI) is filling this gap to support public and private sector AI innovation. This dataset consists of ~30,000 images of overhead Distribution infrastructure. These images have been anonymized, reviewed, and .exif image-data scrubbed. EPRI intends to label these data to support its own research activities. As these labels are created, EPRI will periodically update this dataset with those data.
Update: July 2022
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To study the driver's behavior in real traffic situations, we conducted experiments using an instrumented vehicle, which comprises:
(i) a camera, installed above the vehicle's side window and oriented toward the driver, and (ii) a Mobile Digital Video Recorder (MDVR).
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3559 Views
The "eternal war in cache" has reached browsers, with multiple cache-based side-channel attacks and countermeasures being suggested. A common approach for countermeasures is to disable or restrict JavaScript features deemed essential for carrying out attacks.
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341 Views