Automating ICSI With Rotationally Oscillating Drill (Ros-Drill©) Using Visual Feedback

2010 ◽  
Author(s):  
Jhon Diaz ◽  
Nejat Olgac ◽  
Mehdi Karzar Jeddi ◽  
Tai-Hsi Fan
Keyword(s):  
Real Time ◽  
Visual Feedback ◽  
Oscillation Phase ◽  
The Real ◽  
Rotational Oscillation ◽  
Line Part ◽  
On Line ◽  
Species Specific ◽  
Validation Tests ◽  
Visual Feedback Control

ICSI (Intra-Cytoplasmic Sperm Injection) has attracted research interest from both biological and engineering groups. This technique is used to create genetically identical offsprings of many different species (mice, rats, cattle et al.). We focus on a relatively recent technology for ICSI, called Ros-Drill© (Rotationally Oscillating Drill). In this paper, we present a procedure to automate a critical part of the ICSI operation: initiation of the rotational oscillation phase. (The visual feedback is on the real-time visual monitoring of the tip of the injection pipette. First, the real-time feature extraction in visual feedback is explained). The proposed algorithm which does this is split up into two parts: off-line and on-line. In the off-line part a proper thresholding grey level is determined. In the on-line part a realtime algorithm tracks the tip of the injecting pipette. A predetermined, species-specific penetration depth is used to initiate the rotational oscillation action of the drill. This real-time visual feedback control is compared with an earlier curvature-based analysis. Algorithmic stages as well as the outcomes from the concept validation tests are presented.

The Real-Time Prediction of Surface Roughness Based on Genetic Wavelet Network

2010 ◽  
Vol 102-104 ◽  
pp. 610-614 ◽  
Author(s):  
Jun Chi ◽  
Lian Qing Chen
Keyword(s):  
Surface Roughness ◽  
Real Time ◽  
Back Propagation ◽  
Cutting Parameters ◽  
Wavelet Network ◽  
Back Propagation Algorithm ◽  
The Real ◽  
Roughness Model ◽  
On Line ◽  
Artificial Network

A methodology based on relax-type wavelet network was proposed for predicting surface roughness. After the influencing factors of roughness model were analyzed and the modified wavelet pack algorithm for signal filtering was discussed, the structure of artificial network for prediction was developed. The real-time forecast on line was achieved by the nonlinear mapping and learning mechanism in Elman algorithm based on the vibration acceleration and cutting parameters. The weights in network were optimized using genetic algorithm before back-propagation algorithm to reduce learning time.The validation of this methodology is carried out for turning aluminum and steel in the experiments and its prediction error is measured less than 3%.

Application of Quantitative Real-Time PCR in the Detection of Prion-Protein Gene Species-Specific DNA Sequences in Animal Meals and Feedstuffs

2006 ◽  
Vol 69 (4) ◽  
pp. 891-896 ◽  
Author(s):  
FEDERICA BELLAGAMBA ◽  
SERGIO COMINCINI ◽  
LUCA FERRETTI ◽  
FRANCO VALFRÈ ◽  
VITTORIO M. MORETTI
Keyword(s):  
Real Time ◽  
Prion Protein ◽  
Dna Sequences ◽  
Real Time Pcr ◽  
Animal Feed ◽  
Quantitative Estimation ◽  
Taqman Assay ◽  
Quantitative Real Time Pcr ◽  
The Real ◽  
Species Specific

This study describes a method for quantitative and species-specific detection of animal DNA from different species (cattle, sheep, goat, swine, and chicken) in animal feed and feed ingredients, including fish meals. A quantitative real-time PCR approach was carried out to characterize species-specific sequences based on the amplification of prion-protein sequence. Prion-protein species-specific primers and TaqMan probes were designed, and amplification protocols were optimized in order to discriminate the different species with short PCR amplicons. The real-time quantitative PCR approach was also compared to conventional species-specific PCR assays. The real-time quantitative assay allowed the detection of 10 pg of ruminant, swine, and poultry DNA extracted from meat samples processed at 130°C for 40 min, 200 kPa. The origin of analyzed animal meals was characterized by the quantitative estimation of ruminant, swine, and poultry DNA. The TaqMan assay was used to quantify ruminant DNA in feedstuffs with 0.1% of meat and bone meal. In conclusion, the proposed molecular approach allowed the detection of species-specific DNA in animal meals and feedstuffs.

scholarly journals Effect of Different Feedback Modalities on Swimming Pace: Which Feedback Modality is Most Effective?

2018 ◽  
Vol 65 (1) ◽  
pp. 187-195
Author(s):  
Cesare Altavilla ◽  
Roberto Cejuela ◽  
Pablo Caballero-Pérez
Keyword(s):  
Real Time ◽  
Visual Feedback ◽  
Effect Size ◽  
Medium Effect ◽  
Front Crawl ◽  
The Real ◽  
Medium Effect Size ◽  
Fast Start ◽  
Feedback Modalities ◽  
Split Time

Abstract To compare the effect of three different feedback modalities on swimming pace, sixteen male swimmers and triathletes participated in this study. Each participant swam 3 x 400 m, one for each feedback modality, swimming front crawl at 80% of their individual swimming critical speed. Three feedback modalities were examined: self-pacing, real time visual feedback and real time voice feedback. The swimmers adopted a fast start in all feedback modalities. In the real time voice feedback modality, the data recorded during the second lap (200 m) showed a significant improvement of their swimming pace approaching the swimming pace intended (-1.47 s, p < .01, medium effect size 0.79). A significant improvement toward the swimming pace intended was also noticed at the third split time (300 m) (0.05 s, p < .01, large effect size 0.81) and at the fourth split time (400 m) (0.46 s, p < .01, medium effect size 0.76). In self-pacing, the swimmers were not able to swim in line with the swimming pace intended. In real time visual feedback modality, the swimmers did not show a significant improvement approaching the swimming pace intended. The results revealed that communication with the swimmers using the real time voice feedback induced a significant improvement in their swimming pace and could help the athletes to swim with accurate and consistent pace.

Interactive Two-Stage Rendering Technique of Deformable Part Through Haptic Interface

2011 ◽  
Author(s):  
Zhaoguang Wang ◽  
Georges Dumont
Keyword(s):  
Real Time ◽  
Degrees Of Freedom ◽  
Rigid Body Dynamics ◽  
Haptic Interaction ◽  
Two Stage ◽  
Deformation Spaces ◽  
The Real ◽  
Time Deformation ◽  
Main Challenge ◽  
On Line

Virtual Reality technology has been widely applied in the background of industrial evaluation applications. However, a large majority of these applications are focusing on haptics-based assemblies which mainly deal with rigid-body dynamics. Here we concern the real-time haptic interaction with deformable mock-ups aiming at the industrial design evaluation of mechanical parts. The main challenge of this application is that a tradeoff between the deformation accuracy and the interaction performance has to be achieved. In this paper, we propose a two-stage method for a real-time deformation modelling by combining an off-line pre-computation phase and an on-line deformation interaction phase. The key contributions of this paper lie on two aspects. First, during off-line phase, we propose a mesh analysis method which allows us to pre-compute different deformation spaces by anticipating the evaluation scenarios. Moreover, a real-time switch among different deformation spaces is developed so that the on-line deformation computation can focus on degrees of freedom where necessary with respect to users’ interactions. Second, during on-line phase, we apply a division scheme to divide the deformation process into two separate modules which are implemented on different threads to ensure the haptic interaction performance. Experiments are carried out based on a prototype implementation concerning different models of growing complexity. The deformation accuracy and the real-time performance are discussed.

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