Liquid Bridges: A Novel Approach for Dispensing Biofluids, Characterisation and Correlations

2007 ◽  
Author(s):  
Magali Forget ◽  
Mark Davies
Keyword(s):  
Detection Algorithm ◽  
Design Tool ◽  
Microgravity Environment ◽  
Experimental Investigations ◽  
Point Of Interest ◽  
Novel Approach ◽  
Dimensionless Groups ◽  
Canny Edge ◽  
Good Repeatability ◽  
Isothermal Mass

Control of fluids at the microscale represents an important point of interest in the widely studied field of Microfluidics. In fact, most of the biological and medical research undergone would benefit from Microfluidic solutions. One of the engineering challenges brought about by this technologic evolution involves the dispensing of fluids at these scales. The study presented in this paper concerns the development of a novel dispenser of biofluids, which would find its first application in the measurement of multi-gene expression levels as part of cancer diagnosis. The studied geometry is termed “two-way liquid bridge” and consists of injecting a continuous fluid to be segmented via an inlet PFE tubing in a microgravity environment until an isothermal mass of liquid is held by surface tension between the inlet and outlet tubings, parallel and opposite. Due to constant pressurisation of the microgravity environment, this mass eventually ruptures delivering a segmented volume of biofluids on which an analysis such as PCR can be performed. Experimental investigations were conducted in a backlighted transparent PMMA device in which fluids were injected using Harvard Apparatus syringe pumps. A CMOS colour camera recorded the images which were automatically analysed using a Canny edge detection algorithm. A dimensional analysis was conducted highlighting the main dimensionless groups for a complete understanding of the occurring phenomena. Experimental observations showed good repeatability and consistency in the dispensing process. It was also shown that fluids flowrates, tubings sizes and length of separation between inlet and outlet tubings have a direct impact on the size and frequency of the produced droplets. The present paper addresses the complete characterisation of the geometry as well as the establishment of correlations in order to provide a useful engineering design tool.

A Novel Approach of Controlling Stoppage of Drip Infusion Using Image Processing on Raspberry PI Platform

2021 ◽  
Vol 58 (S) ◽  
pp. 65-72
Author(s):  
Hartono Pranjoto ◽  
Lanny Agustine ◽  
Diana Lestariningsih ◽  
Yesiana Dwi Wahyu Werdani ◽  
Widya Andyardja ◽  
...  
Keyword(s):  
Image Processing ◽  
Digital Camera ◽  
Detection Algorithm ◽  
Processing Technique ◽  
Image Processing Technique ◽  
Raspberry Pi ◽  
Novel Approach ◽  
Pinch Valve ◽  
Canny Edge ◽  
Infusion Fluid

Intravenous drip diffusion is a common practice to treat patients in hospitals. During treatment, nurses must check the condition of the infusion bag frequently before running out of fluid. This research proposes a novel method of checking the infusion bag using an image processing technique on a compact Raspberry PI platform. The infusion monitoring system proposed here is based solely on capturing the image of the infusion bag and the accompanying bag/ tube. When the infusion fluid enters the patient, the surface of the liquid will decrease, and at the end will reach the bottom of the infusion bag. When the image of the fluid surface touches the bottom of the infusion bag, a mechanism will trigger a relay, and then activate a pinch valve to stop the flow of the infusion fluid before it runs out. The entire system incorporates a digital camera and Raspberry as the image processor. The surface of the liquid is determined using the Canny Edge Detection algorithm, and its relative position in the tube is determined using the Hough Line Transform. The raw picture of the infusion bag and the processed image are then sent via a wireless network to become part of a larger system and can be monitored via a simple smartphone equipped with the proper application, thus becoming an Internet of Things (IoT). With this approach, nurses can carry on other tasks in caring for the patients while this system substitutes some work on checking the infusion fluid.

Application of Improved Canny Edge Detection Algorithm in Coal-Rock Interface Recognition

2012 ◽  
Vol 220-223 ◽  
pp. 1279-1283 ◽  
Author(s):  
Li Hong Dong ◽  
Peng Bing Zhao
Keyword(s):  
Edge Detection ◽  
Detection Algorithm ◽  
Canny Edge Detection ◽  
Edge Detection Algorithm ◽  
Canny Edge ◽  
Rock Interface ◽  
Coal Rock ◽  
Image Edge ◽  
Canny Algorithm ◽  
Canny Edge Detection Algorithm

The coal-rock interface recognition is one of the critical automated technologies in the fully mechanized mining face. The poor working conditions underground result in the seriously polluted edge information of the coal-rock interface, which affects the positioning precision of the shearer drum. The Gaussian filter parameters and the high-low thresholds are difficult to select in the traditional Canny algorithm, which causes the information loss of gradual edge and the phenomenon of false edge. Consequently, this paper presents an improved Canny edge detection algorithm, which adopts the adaptive median filtering algorithm to calculate the thresholds of Canny algorithm according to the grayscale mean and variance mean. This algorithm can protect the image edge details better and can restrain the blurred image edge. Experimental results show that this algorithm has improved the edge extraction effect under the case of noise interference and improved the detection precision and accuracy of the coal-rock image effectively.

scholarly journals Considering multiple process observables to determine material model parameters for FE-cutting simulations

2021 ◽  
Author(s):  
Marvin Hardt ◽  
Thomas Bergs
Keyword(s):  
Chip Thickness ◽  
Material Model ◽  
Experimental Investigations ◽  
Model Parameters ◽  
Inverse Approach ◽  
Local Material ◽  
Novel Approach ◽  
Validation Parameters ◽  
Multiple Process ◽  
Cutting Simulations

AbstractAnalyzing the chip formation process by means of the finite element method (FEM) is an established procedure to understand the cutting process. For a realistic simulation, different input models are required, among which the material model is crucial. To determine the underlying material model parameters, inverse methods have found an increasing acceptance within the last decade. The calculated model parameters exhibit good validity within the domain of investigation, but suffer from their non-uniqueness. To overcome the drawback of the non-uniqueness, the literature suggests either to enlarge the domain of experimental investigations or to use more process observables as validation parameters. This paper presents a novel approach merging both suggestions: a fully automatized procedure in conjunction with the use of multiple process observables is utilized to investigate the non-uniqueness of material model parameters for the domain of cutting simulations. The underlying approach is two-fold: Firstly, the accuracy of the evaluated process observables from FE simulations is enhanced by establishing an automatized routine. Secondly, the number of process observables that are considered in the inverse approach is increased. For this purpose, the cutting force, cutting normal force, chip temperature, chip thickness, and chip radius are taken into account. It was shown that multiple parameter sets of the material model can result in almost identical simulation results in terms of the simulated process observables and the local material loads.

An Improved Edge Detection Algorithm Based on Canny Operator

2013 ◽  
Vol 347-350 ◽  
pp. 3541-3545 ◽  
Author(s):  
Dan Dan Zhang ◽  
Shuang Zhao
Keyword(s):  
Edge Detection ◽  
Detection Algorithm ◽  
Image Simulation ◽  
Edge Image ◽  
Canny Operator ◽  
Edge Detection Algorithm ◽  
Image Edge Detection ◽  
Canny Edge ◽  
Image Edge ◽  
Canny Edge Detection Algorithm

The traditional Canny edge detection algorithm is analyzed in this paper. To overcome the difficulty of threshold selecting in Canny algorithm, an improved method based on Otsu algorithm and mathematical morphology is proposed to choose the threshold adaptively and simultaneously. This method applies the improved Canny operator and the image morphology separately to image edge detection, and then performs image fusion of the two results using the wavelet fusion technology to obtain the final edge-image. Simulation results show that the proposed algorithm has better anti-noise ability and effectively enhances the accuracy of image edge detection.

Revisiting knowledge distillation for light-weight visual object detection

2021 ◽  
Vol 43 (13) ◽  
pp. 2888-2898
Author(s):  
Tianze Gao ◽  
Yunfeng Gao ◽  
Yu Li ◽  
Peiyuan Qin
Keyword(s):  
Object Detection ◽  
Essential Element ◽  
Detection Algorithm ◽  
Positive Sample ◽  
Detection Methods ◽  
Visual Object ◽  
Light Weight ◽  
Model Compression ◽  
Novel Approach ◽  
Knowledge Distillation

An essential element for intelligent perception in mechatronic and robotic systems (M&RS) is the visual object detection algorithm. With the ever-increasing advance of artificial neural networks (ANN), researchers have proposed numerous ANN-based visual object detection methods that have proven to be effective. However, networks with cumbersome structures do not befit the real-time scenarios in M&RS, necessitating the techniques of model compression. In the paper, a novel approach to training light-weight visual object detection networks is developed by revisiting knowledge distillation. Traditional knowledge distillation methods are oriented towards image classification is not compatible with object detection. Therefore, a variant of knowledge distillation is developed and adapted to a state-of-the-art keypoint-based visual detection method. Two strategies named as positive sample retaining and early distribution softening are employed to yield a natural adaption. The mutual consistency between teacher model and student model is further promoted through a hint-based distillation. By extensive controlled experiments, the proposed method is testified to be effective in enhancing the light-weight network’s performance by a large margin.

Innovative Passive Flame Ameliorator for a Diffusion Flame Burner Using Chevrons

2015 ◽  
Vol 787 ◽  
pp. 732-735
Author(s):  
A. Alaguraja ◽  
S. Balaji ◽  
Inti Sandeep ◽  
M. Karthikeyan ◽  
S. Soma Sundaram
Keyword(s):  
Diffusion Flame ◽  
Acoustic Noise ◽  
Combustion Process ◽  
Ambient Air ◽  
Premixed Flame ◽  
Experimental Investigations ◽  
Exhaust Gas ◽  
Novel Approach ◽  
Flame Burner ◽  
Safety Considerations

Diffusion flame burners are mainly used in industries over premixed flame burners for safety considerations. But the combustion process in a diffusion flame is not complete and the flame is usually in bright yellow in colour in contrast to the premixed flame which gives a bluish flame. To improve the combustion process in a diffusion flame burner a novel approach, using chevrons has been carried out. The chevrons are found to reduce the aero-acoustic noise in the exhaust jets of aircraft engines by allowing better mixing of the exhaust gas with the ambient air. The similar concept is used here where the tips of the burners are cut in the form of chevrons. Experimental investigations are carried out on burners with three and four chevrons in addition to a standard burner using LPG as the fuel. The results indicate that with the introduction of chevrons the diffusion flame becomes more compact. The premixed region, in the diffusion flame, where the air and fuel is mixed well is found to increase by nearly 100 % with the usage of chevrons, indicating better mixing of fuel and air. The results also indicate that increasing the number of chevrons from three to four does not show much variation. Further experiments are to be carried out to determine the improved fuel consumption with the usage of chevrons.

scholarly journals Moving Objects Detection & Recognition using Hybrid Canny Edge Detection Algorithm in Digital Image Processing

2019 ◽  
Vol 8 (9S3) ◽  
pp. 56-60
Keyword(s):  
Object Detection ◽  
Moving Objects ◽  
Detection Method ◽  
Learning Algorithm ◽  
Detection Algorithm ◽  
Moving Objects Detection ◽  
Canny Edge ◽  
Objects Detection ◽  
Canny Edge Detection Algorithm ◽  
Day By Day

Recognition and detection of an object in the watched scenes is a characteristic organic capacity. Animals and human being play out this easily in day by day life to move without crashes, to discover sustenance, dodge dangers, etc. Be that as it may, comparable PC techniques and calculations for scene examination are not all that direct, in spite of their exceptional advancement. Object detection is the process in which finding or recognizing cases of articles (for instance faces, mutts or structures) in computerized pictures or recordings. This is the fundamental task in computer. For detecting the instance of an object and to pictures having a place with an article classification object detection method usually used learning algorithm and extracted features. This paper proposed a method for moving object detection and vehicle detection.

scholarly journals Identification of Image Edge Using Quantum Canny Edge Detection Algorithm

2019 ◽  
Vol 13 (2) ◽  
pp. 133-144 ◽  
Author(s):  
Dini Sundani ◽  
◽  
Sigit Widiyanto ◽  
Yuli Karyanti ◽  
Dini Tri Wardani ◽  
...  
Keyword(s):  
Edge Detection ◽  
Detection Algorithm ◽  
Canny Edge Detection ◽  
Edge Detection Algorithm ◽  
Canny Edge ◽  
Image Edge ◽  
Canny Edge Detection Algorithm

scholarly journals 3D Image Edge Detection Algorithm for Depth Detection

2019 ◽  
Vol 8 (2S11) ◽  
pp. 3555-3557
Keyword(s):  
Edge Detection ◽  
Detection Algorithm ◽  
Edge Detection Algorithm ◽  
3 Dimensional ◽  
3D Objects ◽  
Image Edge Detection ◽  
Canny Edge ◽  
Image Edge ◽  
3D Scene ◽  
Edge Recognition

Showing a genuine 3 dimensional (3D) objects with the striking profundity data is dependably a troublesome and cost-devouring procedure. Speaking to 3D scene without a noise (raw image) is another case. With a honed technique for survey profundity measurement can be effortlessly gotten, without requiring any extraordinary instrument. In this paper, we have proposed an edge recognition process in a profundity picture dependent on the picture based smoothing and morphological activities.In this strategy, we have utilized the guideline of Median sifting, which has a prestigious element for edge safeguarding properties. The edge discovery was done dependent on the Canny Edge Detection Algorithm. Along these lines this strategy will help to identify edges powerfully from profundity pictures and add to advance applications top to bottom pictures

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