Direct experimental observation of salt induced aspect ratio tunable PFPT silver-nanowire formation: SERS-based ppt level Hg2+ sensing from ground water

RSC Advances ◽  
2016 ◽  
Vol 6 (51) ◽  
pp. 45279-45289 ◽  
Author(s):  
M. Bhattacharya ◽  
A. R. Mandal ◽  
S. Das Chakraborty ◽  
Arpan Maiti ◽  
Achyut Maity ◽  
...  
Keyword(s):  
Aspect Ratio ◽  
Ground Water ◽  
Real Time ◽  
Experimental Observation ◽  
Silver Nanowire ◽  
Common Salt ◽  
Nanowire Synthesis

A common salt induced aspect ratio tunable PFPT silver nanowire synthesis with a plausible explanation based on real-time direct experimental observation finds application as a potential assay for ppt level Hg(ii) sensing from ground water.

System for Detecting Driver Alertness while Driving

2021 ◽  
Vol 9 (VI) ◽  
pp. 2095-2099
Author(s):  
Prajwal Chandrakant Sapkal
Keyword(s):  
Aspect Ratio ◽  
Real Time ◽  
Raspberry Pi ◽  
Time Data ◽  
Facial Landmarks ◽  
Remote Location ◽  
Python Language ◽  
Falling Asleep ◽  
Time Basis ◽  
Main Component

In this project, we are going to present a system for sleep detection alarm to monitor the driver, based on the real time surveillance and alert him as well as post it at remote location whenever it’s necessary using cloud platform. This device is to be developed using the Raspberry Pi, Open CV library and camera module. The required coding part of the project will be done using Python language. The main component of the project will be pretrained landmark detector as a software part. It identifies 68 points on the human face. The Dlib’s landmark will detect 68 facial landmarks which enables us to extract the various facial structures using simple Python array slices. The facial landmarks of fully closed eye and a fully opened eye will be first plotted. This data is further processed and tested with some results which will give the information about driver’s alertness. Once the facial landmarks associated with an eye are determined, we can apply the Eye Aspect Ratio (EAR) algorithm. In our case, we’ll be monitoring the eye aspect ratio to see if the values of the facial landmarks, thus implying that the driver/user has closed their eyes or distracted from driving or yawn. Once implemented, our algorithm will start by localising the facial landmarks on real time basis. We can then will be able to monitor the eye aspect ratio to determine if the eyes are close or nearly close which will be the indicator for driver is falling asleep. And then finally raising an alarm if the eye aspect ratio is below a pre-defined threshold for a sufficiently long amount of time. The alarm will be loud enough to wake up the driver and bring back his attention. At the same time data is passed to remote location using cloud whenever it’s necessary.

Real-time classification for autonomous drowsiness detection using eye aspect ratio

2020 ◽  
Vol 158 ◽  
pp. 113505 ◽  
Author(s):  
Caio Bezerra Souto Maior ◽  
Márcio José das Chagas Moura ◽  
João Mateus Marques Santana ◽  
Isis Didier Lins
Keyword(s):  
Aspect Ratio ◽  
Real Time ◽  
Drowsiness Detection ◽  
Real Time Classification

scholarly journals Titanium dioxide high aspect ratio nanoparticle hydrothermal synthesis optimization

2015 ◽  
Vol 13 (1) ◽  
Author(s):  
Paulina Półrolniczak ◽  
Mariusz Walkowiak
Keyword(s):  
Titanium Dioxide ◽  
Hydrothermal Synthesis ◽  
Aspect Ratio ◽  
High Aspect Ratio ◽  
Reaction Conditions ◽  
Practical Guidelines ◽  
Nanowire Synthesis ◽  
The Relationship

AbstractTiOThe relationship between reaction conditions and morphology is discussed and practical guidelines for titanium dioxide nanowire synthesis are suggested

scholarly journals Real-Time Driver Drowsiness Detection using Computer Vision

2021 ◽  
Vol 11 (1) ◽  
pp. 109-113
Author(s):  
Mahek Jain ◽  
◽  
Bhavya Bhagerathi ◽  
Dr. Sowmyarani C N ◽  
◽  
...  
Keyword(s):  
Computer Vision ◽  
Aspect Ratio ◽  
Real Time ◽  
Threshold Value ◽  
Transportation Safety ◽  
Road Accidents ◽  
Text To Speech ◽  
Upper Lip ◽  
Lower Lip ◽  
Driver Drowsiness

The proposed system aims to lessen the number of accidents that occur due to drivers’ drowsiness and fatigue, which will in turn increase transportation safety. This is becoming a common reason for accidents in recent times. Several faces and body gestures are considered such as signs of drowsiness and fatigue in drivers, including tiredness in eyes and yawning. These features are an indication that the driver’s condition is improper. EAR (Eye Aspect Ratio) computes the ratio of distances between the horizontal and vertical eye landmarks which is required for detection of drowsiness. For the purpose of yawn detection, a YAWN value is calculated using the distance between the lower lip and the upper lip, and the distance will be compared against a threshold value. We have deployed an eSpeak module (text to speech synthesizer) which is used for giving appropriate voice alerts when the driver is feeling drowsy or is yawning. The proposed system is designed to decrease the rate of accidents and to contribute to the technology with the goal to prevent fatalities caused due to road accidents.

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