Effect of Light Illumination on Leaves Movement of Mimosa pudica

2015 ◽  
Vol 771 ◽  
pp. 63-67 ◽  
Author(s):  
Hariyadi Soetedjo ◽  
Bagus Haryadi ◽  
Danu Taspyanto
Keyword(s):  
Real Time ◽  
Observation Time ◽  
Natural Phenomenon ◽  
Light Illumination ◽  
Mimosa Pudica ◽  
Normal Position ◽  
Ultrasonic Signals ◽  
Ultrasonic Apparatus ◽  
Top View ◽  
Effect Of Light

A study on the effect of light illumination introduced to the leaves of Mimosa pudica was carried out using different light intensities. The leaves will open gradually from the closed condition after the light was illuminated. Plant of M. pudica was placed in the dark box during measurement meanwhile the Petiole (part of the stem) of the plant was at normal position (hanging up). The camera was fixed to the box to monitor the leaves’ movement continuous and real time. By using this method the change of the top view area of the leaves could be observed. A crossed line was drawn on the image recorded and was measured its length. The calculation of the length gives the percentage of leaves at open during the observation time. Ultrasonic apparatus was also used to monitor the change of leaves. From the results, at an illumination intensity of 200 Lux, the percentage of leaves to open completely with respects to the observation time was found to increase nonlinearly by taking the time of 25 minutes. For intensities of 400 Lux, the trend of curve was also similar but increase rapidly. The ultrasonic signals show much stable at 200 Lux comparing to 400 Lux that was fluctuating. That may be due to the relatively faster movement of the leaves to open. This natural phenomenon is interesting and may introduce any change of natural indication that could be explored for further applications.

Probing the Dynamic Self-Assembly Behaviour of Photoswitchable Wormlike Micelles in Real Time

2018 ◽  
Author(s):  
Elaine A. Kelly ◽  
Judith E. Houston ◽  
Rachel Evans
Keyword(s):  
Real Time ◽  
Absorption Spectroscopy ◽  
Self Assembly ◽  
Uv Light ◽  
Wormlike Micelles ◽  
Tetraethylene Glycol ◽  
Light Illumination ◽  
First Time ◽  
Dependent Processes

Understanding the dynamic self-assembly behaviour of azobenzene photosurfactants (AzoPS) is crucial to advance their use in controlled release applications such as<i></i>drug delivery and micellar catalysis. Currently, their behaviour in the equilibrium <i>cis-</i>and <i>trans</i>-photostationary states is more widely understood than during the photoisomerisation process itself. Here, we investigate the time-dependent self-assembly of the different photoisomers of a model neutral AzoPS, <a>tetraethylene glycol mono(4′,4-octyloxy,octyl-azobenzene) </a>(C<sub>8</sub>AzoOC<sub>8</sub>E<sub>4</sub>) using small-angle neutron scattering (SANS). We show that the incorporation of <i>in-situ</i>UV-Vis absorption spectroscopy with SANS allows the scattering profile, and hence micelle shape, to be correlated with the extent of photoisomerisation in real-time. It was observed that C<sub>8</sub>AzoOC<sub>8</sub>E<sub>4</sub>could switch between wormlike micelles (<i>trans</i>native state) and fractal aggregates (under UV light), with changes in the self-assembled structure arising concurrently with changes in the absorption spectrum. Wormlike micelles could be recovered within 60 seconds of blue light illumination. To the best of our knowledge, this is the first time the degree of AzoPS photoisomerisation has been tracked <i>in</i><i>-situ</i>through combined UV-Vis absorption spectroscopy-SANS measurements. This technique could be widely used to gain mechanistic and kinetic insights into light-dependent processes that are reliant on self-assembly.

scholarly journals Lightning Monitoring Integrated System

2019 ◽  
Author(s):  
Michell Cruz ◽  
Marcio Lopes ◽  
Alen Vieira ◽  
Flávio Santos ◽  
Ricardo Shinkai ◽  
...  
Keyword(s):  
Real Time ◽  
Satellite Images ◽  
Integrated System ◽  
Decision Makers ◽  
Natural Phenomenon ◽  
Tabular Data ◽  
Web Based ◽  
Detection Systems ◽  
Lightning Detection ◽  
Intuitive Interface

Lightning is a natural phenomenon and presents severe risks to people and animals, as well as affects several segments of the productive sector. A web-based lightning monitoring system has been developed to integrate different lightning detection systems, as well as to generate spatial and tabular data and products, capable of assisting specialists and decision makers. The system also allows combining lightning data with satellite images, increasing the capacity of analysis in near real time. This tool proved to be stable and efficient, with an intuitive interface that facilitates interaction with users.

SEM, EDX spectroscopy and real-time optical microscopy of electroformed silicon nitride-based light emitting memory device

2020 ◽  
Vol 89 (1) ◽  
pp. 10303
Author(s):  
Mustafa Anutgan ◽  
Tamila Anutgan ◽  
Ismail Atilgan
Keyword(s):  
Silicon Nitride ◽  
Optical Microscopy ◽  
Real Time ◽  
Semiconductor Device ◽  
Process Conditions ◽  
Sem Images ◽  
Cross Sectional ◽  
Light Emitting ◽  
Edx Analyses ◽  
Top View

An ordinary amorphous silicon nitride-based p-i-n diode was electroformed under optimized process conditions, which led to its instant transformation to a semiconductor device with two-in-one properties: a bright visible light emitting diode and a resistive memory switching device; i.e. light emitting memory (LEM). In the present work, for a thorough understanding of the changes that occur during electroforming, SEM images and EDX analyses were performed on both top-view and cross-section of both as-deposited and electroformed diodes. It was seen from the top-view images that while the diode surface of the as-deposited diode had a smooth and homogeneous ITO top electrode, the electroformed diode exhibited a rough ITO surface. EDX analyses showed that ITO was completely removed from many point-like regions on the diode surface. Cross-sectional SEM images showed no clue of any material diffusion through the diode structure during electroforming, which was one of the suspected situations about our model. EDX results also showed no considerable increase of any of the ingredients of the ITO alloy (In, Sn or O) across the semiconductor (p-i-n) layers of the electroformed diode. In contrast to the roughened surface of the electroformed diode, the silicon-based layers of the diode below the ITO electrode seemed to be well-preserved. Real-time optical microscopy showed that the light is emitted through the regions of the diode surface where the residual ITO top electrode is present.

scholarly journals Face Recognition in an Unconstrained and Real-Time Environment Using Novel BMC-LBPH Methods Incorporates with DJI Vision Sensor

2020 ◽  
Vol 9 (4) ◽  
pp. 54
Author(s):  
Md Manjurul Ahsan ◽  
Yueqing Li ◽  
Jing Zhang ◽  
Md Tanvir Ahad ◽  
Munshi Md. Shafwat Yazdan
Keyword(s):  
Face Recognition ◽  
Real Time ◽  
Local Binary Pattern ◽  
Computation Time ◽  
Threshold Value ◽  
Light Illumination ◽  
Rainy Weather ◽  
Face Datasets ◽  
Bad Weather ◽  
Pattern Histogram

Face recognition (FR) in an unconstrained environment, such as low light, illumination variations, and bad weather is very challenging and still needs intensive further study. Previously, numerous experiments on FR in an unconstrained environment have been assessed using Eigenface, Fisherface, and Local binary pattern histogram (LBPH) algorithms. The result indicates that LBPH FR is the optimal one compared to others due to its robustness in various lighting conditions. However, no specific experiment has been conducted to identify the best setting of four parameters of LBPH, radius, neighbors, grid, and the threshold value, for FR techniques in terms of accuracy and computation time. Additionally, the overall performance of LBPH in the unconstrained environments are usually underestimated. Therefore, in this work, an in-depth experiment is carried out to evaluate the four LBPH parameters using two face datasets: Lamar University data base (LUDB) and 5_celebrity dataset, and a novel Bilateral Median Convolution-Local binary pattern histogram (BMC-LBPH) method was proposed and examined in real-time in rainy weather using an unmanned aerial vehicle (UAV) incorporates with 4 vision sensors. The experimental results showed that the proposed BMC-LBPH FR techniques outperformed the traditional LBPH methods by achieving the accuracy of 65%, 98%, and 78% in 5_celebrity dataset, LU dataset, and rainy weather, respectively. Ultimately, the proposed method provides a promising solution for facial recognition using UAV.

scholarly journals Classification of Continuous Sky Brightness Data Using Random Forest

2020 ◽  
Vol 2020 ◽  
pp. 1-11
Author(s):  
Rhorom Priyatikanto ◽  
Lidia Mayangsari ◽  
Rudi A. Prihandoko ◽  
Agustinus G. Admiranto
Keyword(s):  
Random Forest ◽  
Observation Time ◽  
Classification Model ◽  
Posterior Distributions ◽  
Random Forest Algorithm ◽  
Negative Effect ◽  
Sky Brightness ◽  
Global Statistics ◽  
Effect Of Light

Sky brightness measuring and monitoring are required to mitigate the negative effect of light pollution as a byproduct of modern civilization. Good handling of a pile of sky brightness data includes evaluation and classification of the data according to its quality and characteristics such that further analysis and inference can be conducted properly. This study aims to develop a classification model based on Random Forest algorithm and to evaluate its performance. Using sky brightness data from 1250 nights with minute temporal resolution acquired at eight different stations in Indonesia, datasets consisting of 15 features were created to train and test the model. Those features were extracted from the observation time, the global statistics of nightly sky brightness, or the light curve characteristics. Among those features, 10 are considered to be the most important for the classification task. The model was trained to classify the data into six classes (1: peculiar data, 2: overcast, 3: cloudy, 4: clear, 5: moonlit-cloudy, and 6: moonlit-clear) and then tested to achieve high accuracy (92%) and scores (F-score = 84% and G-mean = 84%). Some misclassifications exist, but the classification results are considerably good as indicated by posterior distributions of the sky brightness as a function of classes. Data classified as class-4 have sharp distribution with typical full width at half maximum of 1.5 mag/arcsec2, while distributions of class-2 and -3 are left skewed with the latter having lighter tail. Due to the moonlight, distributions of class-5 and -6 data are more smeared or have larger spread. These results demonstrate that the established classification model is reasonably good and consistent.

Period Coded Phase Shifting Strategy for Real–time 3-D Structured Light Illumination

2011 ◽  
Vol 20 (11) ◽  
pp. 3001-3013 ◽  
Author(s):  
Yongchang Wang ◽  
Kai Liu ◽  
Qi Hao ◽  
Daniel L. Lau ◽  
Laurence G. Hassebrook
Keyword(s):  
Real Time ◽  
Structured Light ◽  
Phase Shifting ◽  
Light Illumination ◽  
Structured Light Illumination ◽  
Shifting Strategy
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