Detecting children's passive exposure to cocaine and marijuana.

Bhushan, Vikram Vir; Ng, Sally; Spiller, David; Gang, Huang; Inamdar, Sumant

doi:10.2105/ajph.84.4.675-a

Cited by 6 publications

(2 citation statements)

References 9 publications

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“…Video target trajectory acquisition methods can be mainly classified into tracking methods based on deep learning combined with correlation filtering, tracking methods based on prediction, and tracking methods based on optical flow [24]. e classical algorithms corresponding to the three methods are efficient convolution operator ECO [25] algorithm for tracking combined with depth features and correlation filtering [13], Kalman filtering algorithm, and Lucas-Kanade (LK) [26] optical flow algorithm. Although these three algorithms can detect video target trajectories in a specific environment well, there are still some problems in detecting video target trajectories.…”

Section: Improved Tld-based Video Multiobject Detection Andmentioning

confidence: 99%

Application Research on Roller Skater Detection, Tracking, and Trajectory Prediction Based on Video Stream

Duan¹,

Meng²,

Ma³

et al. 2021

Scientific Programming

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With the continuous progress of science and technology, the sport of roller skating has developed rapidly and the technical level of the game has become higher and higher. Its sport performance has been rapidly improved. However, China’s roller skating is relatively late, and there is still a certain gap compared with many Western developed countries. In order to improve the performance of China’s roller skating, this study takes the representative Chinese and foreign excellent speed skaters as the research object and compares the sprinting technology of Chinese and foreign excellent speed skaters by using image measurement and image analysis to obtain the kinematic parameters and data of the athletes’ sprinting technology in the competition state. In view of the problem that the current video target tracking algorithm is easy to follow multiple targets, a video multiobject detection and tracking algorithm with improved tracking learning detection (TLD) is studied with the skater in the video as the research object. For the lost target, the prediction function of Kalman filter algorithm is used to track the trajectory of the typical target in the video, and the trajectory tracked by Kalman filter algorithm is used to compensate the lost part of TLD algorithm, so as to obtain the complete trajectory of the typical target in the video to improve the accuracy of video multiobject tracking. Since the existing trajectory prediction algorithms have the limitation of poor accuracy, a social-long short-term memory (Social-LSTM) network-based video typical target trajectory prediction algorithm is proposed to predict the trajectory sequences of typical targets to be detected by incorporating the contextual environment information and the interaction relationship between multiple target trajectories into the Social-LSTM network. The simulation results show that the proposed trajectory prediction algorithm outperforms the traditional LSTM algorithm, Hidden Markov Model Algorithm, and Hybrid Gaussian model algorithm, which is helpful to improve the accuracy of video roller skater target trajectory prediction, and the tracking success rate is 0.98.

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Section: Improved Tld-based Video Multiobject Detection Andmentioning

confidence: 99%

Application Research on Roller Skater Detection, Tracking, and Trajectory Prediction Based on Video Stream

Duan¹,

Meng²,

Ma³

et al. 2021

Scientific Programming

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“…Low doses of cannabis metabolites were found in the urine of several children. However, the route and specific time of exposure, duration and clinical relevance were not addressed [14][15][16].…”

Section: Discussionmentioning

confidence: 99%

Passive Cannabis Smoking Resulting in a Coma in a 16 Month Old Infant

Ragaband¹

2012

J Clin Case Rep

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We report on 16-month-old infant who was admitted to hospital with severe neurological symptoms following passive inhalation of cannabis. To our knowledge and after deep surveying in the literature, we believe that this is one of the few reported clinical case of the acute severe toxicity after passive inhalation of cannabis smoke by an infant. Urine and serum THC (delta-9-tetrahydrocannabinol) Δ 9 -THC concentrations of 230 and 112 ng/ml were detected. This case report highlights the importance of considering cannabis ingestion in the differential diagnosis of infantile and toddler coma. Moreover, facing the increasing number of cannabis smokers such cases might be more prevalent and therefore physicians, health workers and parents should be alerted about the health hazards of cannabis substances abuse in the presence of children.

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