Analysis of implementation opportunities for selected conventional counter-based circuits in selected FPGA structures in terms of time performance

2014 ◽  
Author(s):  
Jaroslaw Wrotniak ◽  
Krzysztof Pucher ◽  
Dariusz Polok
Keyword(s):  
Time Performance

Extraversion and Dopamine

1998 ◽  
Vol 3 (1) ◽  
pp. 37-50 ◽  
Author(s):  
Thomas H. Rammsayer
Keyword(s):  
Individual Differences ◽  
D2 Receptor ◽  
D2 Receptors ◽  
Behavioral Differences ◽  
Biological Mechanisms ◽  
Brain Dopamine ◽  
Personality Dimension ◽  
Time Performance ◽  
Reaction Time Performance ◽  
Induced Changes

Recent research suggests that individual differences in brain dopamine (DA) functioning may be related to the personality dimension of extraversion. The present study was designed to further elucidate the biological mechanisms underlying behavioral differences between extraverts and introverts. For this purpose, the differential effects of a pharmacologically induced blockade of mesolimbocortical DA D2 receptors on reaction-time performance were investigated in 24 introverted and 24 extraverted subjects. Introverts were found to be much more susceptible to pharmacologically induced changes in D2 receptor activity than extraverts. This finding provides additional experimental evidence for the notion that individual differences in D2 receptor responsivity may represent a neurobiological substratum for the personality dimension of extraversion.

Real-time Performance Monitoring of MPC Based on Covariance Index Prediction

2014 ◽  
Vol 39 (5) ◽  
pp. 658-663 ◽  
Author(s):  
Xue-Min TIAN ◽  
Ya-Jie SHI ◽  
Yu-Ping CAO
Keyword(s):  
Real Time ◽  
Performance Monitoring ◽  
Time Performance

Single Depth View Based Real-Time Reconstruction of Hand-Object Interactions

2021 ◽  
Vol 40 (3) ◽  
pp. 1-12
Author(s):  
Hao Zhang ◽  
Yuxiao Zhou ◽  
Yifei Tian ◽  
Jun-Hai Yong ◽  
Feng Xu
Keyword(s):  
Real Time ◽  
Synthetic Data ◽  
Real Data ◽  
Depth Image ◽  
Real Time System ◽  
The Real ◽  
Time Performance ◽  
Contact Constraint ◽  
Object Shapes ◽  
Object Interactions

Reconstructing hand-object interactions is a challenging task due to strong occlusions and complex motions. This article proposes a real-time system that uses a single depth stream to simultaneously reconstruct hand poses, object shape, and rigid/non-rigid motions. To achieve this, we first train a joint learning network to segment the hand and object in a depth image, and to predict the 3D keypoints of the hand. With most layers shared by the two tasks, computation cost is saved for the real-time performance. A hybrid dataset is constructed here to train the network with real data (to learn real-world distributions) and synthetic data (to cover variations of objects, motions, and viewpoints). Next, the depth of the two targets and the keypoints are used in a uniform optimization to reconstruct the interacting motions. Benefitting from a novel tangential contact constraint, the system not only solves the remaining ambiguities but also keeps the real-time performance. Experiments show that our system handles different hand and object shapes, various interactive motions, and moving cameras.

scholarly journals Formation Control and Obstacle Avoidance Algorithm of a Multi-USV System Based on Virtual Structure and Artificial Potential Field

2021 ◽  
Vol 9 (2) ◽  
pp. 161
Author(s):  
Xun Yan ◽  
Dapeng Jiang ◽  
Runlong Miao ◽  
Yulong Li
Keyword(s):  
Obstacle Avoidance ◽  
Potential Field ◽  
Formation Control ◽  
Shape Change ◽  
Artificial Potential Field ◽  
Generation Algorithm ◽  
Time Performance ◽  
Movement Ability ◽  
Window Approach ◽  
Avoidance Problem

This paper proposes a formation generation algorithm and formation obstacle avoidance strategy for multiple unmanned surface vehicles (USVs). The proposed formation generation algorithm implements an approach combining a virtual structure and artificial potential field (VSAPF), which provides a high accuracy of formation shape keeping and flexibility of formation shape change. To solve the obstacle avoidance problem of the multi-USV system, an improved dynamic window approach is applied to the formation reference point, which considers the movement ability of the USV. By applying this method, the USV formation can avoid obstacles while maintaining its shape. The combination of the virtual structure and artificial potential field has the advantage of less calculations, so that it can ensure the real-time performance of the algorithm and convenience for deployment on an actual USV. Various simulation results for a group of USVs are provided to demonstrate the effectiveness of the proposed algorithms.

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