Depth from Dichoptic Edges Depends on Vergence Tuning

Perception ◽  
1983 ◽  
Vol 12 (4) ◽  
pp. 425-438 ◽  
Author(s):  
Jodi D Krol ◽  
Wim A van de Grind
Keyword(s):  
Spatial Distribution ◽  
Control System ◽  
Normal Subjects ◽  
Fine Tuning ◽  
Fixation Disparity ◽  
Low Contrast ◽  
Fixation Distance ◽  
Depth Vision ◽  
Opposite Contrast ◽  
Paradoxical Results

Small but reproducible fixation disparities occur in normal subjects when they view certain types of dichoptic stimuli. During dichoptic as well as stereoptic stimulation the motor fusion process determines first the average vergence state of the eyes. The subsequent fine tuning of vergence is shown to depend on the spatial distribution of contrast edges both of the same contrast sign (‘stereoptic edges’) and of opposite contrast sign (‘dichoptic edges’). Stereoptic edges tend to induce superposition attempts of the vergence control system and dichoptic edges tend to antagonise this process. If a single low-contrast dichoptic edge is presented with zero disparity and within a stereoptic reference frame, a fixation disparity of several minutes of arc results. This influences depth vision since dichoptic edges are perceived (as monocular edges) at the actual rather than at the intended fixation distance. The findings explain previous paradoxical results of eg Kaufman and Pitblado who reported seeing depth in opposite-contrast stereograms. Their results seemed to contradict the well-established ‘same-sign rule’ (SSR) which states that the stereoptic system only detects disparities of edges with the same contrast sign. It is concluded that (i) the SSR holds; (ii) dichoptic (and monocular) edges are seen at the horopter; (iii) the vergence fine tuning prevents superposition of dichoptic edges even if this causes a fixation disparity.

scholarly journals Electrical Damping Assessment and Sensitivity Analysis of a Liquefied Natural Gas Plant: Experimental Validation

Energies ◽  
2020 ◽  
Vol 13 (16) ◽  
pp. 4084
Author(s):  
Lorenzo Bongini ◽  
Rosa Anna Mastromauro ◽  
Daniele Sgrò ◽  
Fabrizio Malvaldi
Keyword(s):  
Sensitivity Analysis ◽  
Control System ◽  
Natural Gas ◽  
Experimental Validation ◽  
Power Conversion ◽  
Liquefied Natural Gas ◽  
Fine Tuning ◽  
Simulation Platform ◽  
Electrical Damping ◽  
Conversion Stage

Liquefied Natural Gas (LNG) plants are commonly island-operated weak grids where the interaction of high-power Variable Frequency Drives (VFDs) with the Turbine-Generator (TG) units might cause Sub-Synchronous Torsional Interaction (SSTI) phenomena. SSTI phenomena can lead the LNG plant to instability conditions. Each LNG plant configuration is characterized by a risk level, which is considered high when the electrical damping at the TG Torsional Natural Frequencies (TNFs) is negative. Starting from a real case study, a detailed electromechanical model of an LNG plant is presented. The model is comprehensive of the control system of the power conversion stage and of the TG unit. Sensitivity analysis, performed on control system parameters, allows one to detect the parameters that impact the electrical damping and the stability of the overall LNG plant. A complete simulation platform is developed. Experimental results are carried out on a real LNG plant considering four different configurations. The theoretical model and the simulation platform allow one to estimate the electrical damping and the results are confirmed by the experimental validation. It is demonstrated that fine tuning of the power conversion stage control parameters can reduce the risk related to torsional instability.

scholarly journals Similarity Retention Loss (SRL) Based on Deep Metric Learning for Remote Sensing Image Retrieval

2020 ◽  
Vol 9 (2) ◽  
pp. 61
Author(s):  
Hongwei Zhao ◽  
Lin Yuan ◽  
Haoyu Zhao
Keyword(s):  
Remote Sensing ◽  
Spatial Distribution ◽  
Image Retrieval ◽  
Learning Strategy ◽  
Metric Learning ◽  
Remote Sensing Image ◽  
Fine Tuning ◽  
Retention Loss ◽  
Deep Metric Learning ◽  
Hard Samples

Recently, with the rapid growth of the number of datasets with remote sensing images, it is urgent to propose an effective image retrieval method to manage and use such image data. In this paper, we propose a deep metric learning strategy based on Similarity Retention Loss (SRL) for content-based remote sensing image retrieval. We have improved the current metric learning methods from the following aspects—sample mining, network model structure and metric loss function. On the basis of redefining the hard samples and easy samples, we mine the positive and negative samples according to the size and spatial distribution of the dataset classes. At the same time, Similarity Retention Loss is proposed and the ratio of easy samples to hard samples in the class is used to assign dynamic weights to the hard samples selected in the experiment to learn the sample structure characteristics within the class. For negative samples, different weights are set based on the spatial distribution of the surrounding samples to maintain the consistency of similar structures among classes. Finally, we conduct a large number of comprehensive experiments on two remote sensing datasets with the fine-tuning network. The experiment results show that the method used in this paper achieves the state-of-the-art performance.

scholarly journals Cortical Contrast Processing in Retinitis Pigmentosa: Evidence of PVEPs Spatial Functions

2020 ◽  
Vol 10 (4) ◽  
pp. 1010-1019
Author(s):  
Rafael Mancebo-Azor ◽  
José Antonio Sáez-Moreno ◽  
José Manuel Rodríguez-Ferrer
Keyword(s):  
Retinitis Pigmentosa ◽  
Evoked Potentials ◽  
Visual Evoked Potentials ◽  
Normal Subjects ◽  
Pattern Reversal ◽  
Check Size ◽  
Low Contrast ◽  
Control Subjects ◽  
The Right ◽  
Visual Evoked

Objective: To study the effect of check width size of the stimuli on the amplitude and latency of the P100 component of visual evoked potentials recorded in patients with retinitis pigmentosa (RP). Methods: Pattern reversal visual evoked potentials (PVEPs) were recorded in 16 RP patients and 20 visually normal subjects. Pattern reversal stimuli with five different check widths and 100% of contrast were projected in the right eye of both patients and control subjects. PVEPs induced by stimuli with 78%, 16%, and 6% of contrast were also recorded in 10 of the control subjects. Results: In RP patients, the amplitude of P100 was smaller than controls in all check sized used and the peak P100 amplitude was obtained with a larger check width than in controls. P100 was also delayed in RP patients in all check sizes studied. The P100 amplitude- and latency-check size functions of RP patients were like those found in control subjects with low contrast stimuli of 16% and 6%. Conclusion: The PVEPs spatial functions of RP patients show quantitative and qualitative changes, suggesting disease induced alteration in the neural processing of stimulus contrast.

Study on the Online Detection Technology of the Band Saw Equipment

2013 ◽  
Vol 753-755 ◽  
pp. 2329-2333
Author(s):  
Guo Jin Chen ◽  
Jing Ni ◽  
Ting Ting Liu ◽  
Hui Peng Chen ◽  
Ming Xu
Keyword(s):  
Control System ◽  
Real Time ◽  
Digital Control ◽  
Surface Profile ◽  
Fine Tuning ◽  
Digital Control System ◽  
The Real ◽  
Detection Technology ◽  
Real Time Detection ◽  
Band Saw

Aiming at the lower automation, accuracy and efficiency of the domestic band sawing machine, this paper studies the real-time detection technology based on the sawing load, develops the digital control system of the constant power sawing with the micro-feed performance to improve the load imbalance of the band saw blades in the sawing process. The real-time detection technology based on the micro-deviation of the band saws trajectory is studied. The digitized deviation-correction control system of the band saws trajectory is developed with the fine-tuning performance of the saw stiffness to correct automatically the band saws trajectory. The weight-detection technology based on the scan reconstruction of the surface profile size is researched. The digital control system of the fixed weight sawing is developed to meet that the weight error of the sawed workpiece is fewer than 3%. That can improve the accuracy and efficiency of the band sawing machine and provide the foundation for the realization of the digital control of the band sawing machine.

Intelligent Control of a Cart and Pole System

2013 ◽  
Vol 397-400 ◽  
pp. 1438-1441
Author(s):  
Hong Li Jia ◽  
Qiang Liu ◽  
Feng Du
Keyword(s):  
Control System ◽  
Fuzzy Control ◽  
Intelligent Control ◽  
Fuzzy Controller ◽  
Real Life ◽  
Fine Tuning ◽  
Vehicle Simulation ◽  
Engineering Software ◽  
Wide Range ◽  
Pole System

The paper focuses on the cart-pole system by using fuzzy control, fuzzy mamdan control theory, the fuzzy controller perturbation amplitude simulation and fine-tuning of different linear and nonlinear model. It applicates MATLAB soft which function is so powerful, suitable for a wide range of engineering software system for vehicle simulation intelligent control. And then adjusting fuzzy controller on PID control system, fuzzy control system, the cart-pole system can provide reliable data for our real life and production in the future.

scholarly journals Segmentation of White Chali Arecanuts using Soft Computing Methods

2020 ◽  
Vol 9 (7) ◽  
pp. 1049-1055
Keyword(s):  
Differential Evolution ◽  
Harmony Search ◽  
Cuckoo Search ◽  
Search Algorithms ◽  
Fine Tuning ◽  
Experimental Result ◽  
Multilevel Thresholding ◽  
Low Contrast ◽  
Morphological Segmentation ◽  
Grading Systems

Performance of computer vision based grading systems is remarkably affected by the efficiency of object segmentation. The automatic segmentation of low contrast objects is a challenging task in various fruit and nut grading systems. In this paper background elimination of white chali arecanut images is carried out using morphological segmentation. The fine-tuning of edge threshold for morphological segmentation is achieved by obtaining threshold values from multilevel thresholding of original grayscale image. The best figure ground segmentation is selected by a network trained using shape parameters of the ground truth masks. The performance of morphological segmentation is evaluated for the best figure ground segmentations using precision, recall and F-scores. Comparison of segmentation performance is done by employing multilevel thresholding based on Otsu, Fuzzy c-mean, Harmony search, Differential Evolution and Cuckoo Search algorithms. The experimental result shows that, multilevel thresholding using Differential Evolution and Cuckoo Search algorithms yield best results for the fine-tuning of edge thresholds and hence the better segmentation performance of the white chali arecanuts

Study on the Control System of Grinding the Nozzle of Twin Flapper-Nozzle Valve

2014 ◽  
Vol 644-650 ◽  
pp. 62-66
Author(s):  
Shu Zhen Yang ◽  
Rui Qian ◽  
Yu Jie Bai
Keyword(s):  
Control System ◽  
Intelligent Control ◽  
Fine Tuning ◽  
Machining Accuracy ◽  
Control Technology ◽  
Working Pressure ◽  
Abrasive Flow Machining ◽  
Intelligent Control System ◽  
High Level ◽  
Very High

In this paper, neural network and grey fuzzy control technology are applied in Abrasive Flow Machining (AFM) to grind the mico-hole in th nozzle of the twin flapper-nozzle valve. An intelligent control system with fine tuning working pressure is established that can predict the process parameters automatically before machining and forcast the flow to adjust the working pressure in machining.The result of experiment indicates that this system has high level of intelligent and can get very high machining accuracy.

scholarly journals Fine-Tuning of the Cpx Envelope Stress Response Is Required for Cell Wall Homeostasis inEscherichia coli

mBio ◽  
2016 ◽  
Vol 7 (1) ◽  
Author(s):  
Antoine Delhaye ◽  
Jean-François Collet ◽  
Géraldine Laloux
Keyword(s):  
Quality Control ◽  
Cell Wall ◽  
Control System ◽  
Stress Response ◽  
Cell Shape ◽  
Protein Quality ◽  
Fine Tuning ◽  
Gram Negative Bacteria ◽  
Gram Negative ◽  
Envelope Stress

ABSTRACTThe envelope of Gram-negative bacteria is an essential compartment that constitutes a protective and permeability barrier between the cell and its environment. The envelope also hosts the cell wall, a mesh-like structure made of peptidoglycan (PG) that determines cell shape and provides osmotic protection. Since the PG must grow and divide in a cell-cycle-synchronized manner, its synthesis and remodeling are tightly regulated. Here, we discovered that PG homeostasis is intimately linked to the levels of activation of the Cpx system, an envelope stress response system traditionally viewed as being involved in protein quality control in the envelope. We first show that Cpx is activated when PG integrity is challenged and that this activation provides protection to cells exposed to antibiotics inhibiting PG synthesis. By rerouting the outer membrane lipoprotein NlpE, a known Cpx activator, to a different envelope subcompartment, we managed to manipulate Cpx activation levels. We found that Cpx overactivation leads to aberrant cellular morphologies, to an increased sensitivity to β-lactams, and to dramatic division and growth defects, consistent with a loss of PG homeostasis. Remarkably, these phenotypes were largely abrogated by the deletion ofldtD, a Cpx-induced gene involved in noncanonical PG cross-linkage, suggesting that this transpeptidase is an important link between PG homeostasis and the Cpx system.Altogether our data show that fine-tuning of an envelope quality control system constitutes an important layer of regulation of the highly organized cell wall structure.IMPORTANCEThe envelope of Gram-negative bacteria is essential for viability. First, it includes the cell wall, a continuous polymer of peptidoglycan (PG) that determines cell morphology and protects against osmotic stress. Moreover, the envelope constitutes a protective barrier between the cell interior and the environment. Therefore, mechanisms called envelope stress response systems (ESRS) exist to monitor and defend envelope integrity against harmful conditions. Cpx is a major ESRS that detects and manages the accumulation of misfolded proteins in the envelope ofEscherichia coli. We found that this protein quality control system also plays a fundamental role in the regulation of PG assembly. Strikingly, the level of Cpx response is critical, as an excessive activation leads to phenotypes associated with a loss of cell wall integrity. Thus, by contributing to PG homeostasis, the Cpx system lies at the crossroads between key processes of bacterial life, including cell shape, growth, division, and antibiotic resistance.

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