ORTHOGONAL MOMENTS AND THEIR APPLICATION TO MOTION DETECTION IN IMAGE SEQUENCES

2004 ◽  
Vol 01 (01) ◽  
pp. 77-87 ◽  
Author(s):  
JUN SHEN ◽  
WEI SHEN ◽  
DANFEI SHEN ◽  
YOUFU WU
Keyword(s):  
Motion Detection ◽  
Information Acquisition ◽  
Image Sequences ◽  
Experimental Results ◽  
The Other ◽  
New Method ◽  
Dynamic Scenes ◽  
Orthogonal Moments ◽  
Modern Information

Motion detection is one of the most important subjects in modern information acquisition systems for dynamic scenes. In this paper, we address motion detection in image sequences by the use of smoothed orthogonal Gaussian-Hermite moments. After introducing the orthogonal moments, with their fast calculations and the analysis on their behavior, we present a new method of motion detection in image sequences by the use of temporal Gaussian-Hermite moments. Experimental results are presented and are compared with the other methods, which shows the good performance of smoothed orthogonal Gaussian-Hermite moments for motion detection.

A modified Runge-Kutta method

SIMULATION ◽  
1968 ◽  
Vol 10 (5) ◽  
pp. 221-223 ◽  
Author(s):  
A.S. Chai
Keyword(s):  
Error Estimate ◽  
Linear Combination ◽  
Experimental Results ◽  
The Other ◽  
New Method ◽  
Kutta Method ◽  
Starting Values ◽  
Runge Kutta Method ◽  
Runge Kutta ◽  
A Minor

It is possible to replace k2 in a 4th-order Runge-Kutta for mula (also Nth-order 3 ≤ N ≤ 5) by a linear combination of k1 and the ki's in the last step, using the same procedure for computing the other ki's and y as in the standard R-K method. The advantages of the new method are: It re quires one less derivative evaluation, provides an error estimate at each step, gives more accurate results, and needs a minor change to switch to the RK to obtain the starting values. Experimental results are shown in verification of the for mula.

scholarly journals Double Pole Method in QCD Sum Rules for Vector Mesons

2021 ◽  
Author(s):  
Mikael Souto Maior de Sousa ◽  
Rômulo Rodrigues da Silva
Keyword(s):  
Excited State ◽  
Spectral Density ◽  
Sum Rules ◽  
Ground States ◽  
Experimental Results ◽  
The Other ◽  
New Method ◽  
Vector Mesons ◽  
Qcd Sum Rules ◽  
Simple Modification

The QCD Sum Rules approach had proposed by Shifman, Vaishtein Zakharov Novikov, Okun and Voloshin (SVZNOV) in 1979 and has been used as a method for extracting useful properties of hadrons having the lowest mass, called as ground states. On the other hand, the most recent experimental results make it clear that the study of the excited states can help to solve many puzzles about the new XYZ mesons structure. In this paper, we propose a new method to study the first excited state of the vector mesons, in particular we focus our attention on the study of the ρ vector mesons, that have been studied previously by SVZNOV method. In principle, the method that we used is a simple modification to the shape of the spectral density of the SVZNOV method, which is written as “pole + continuum”, to a new functional form “pole + pole + continuum”. In this way, We may obtain the ρ and the ρ 2 S masses and also their decay constants.

Research of One-Step Commutation Strategy in Matrix Rectifier

2012 ◽  
Vol 516-517 ◽  
pp. 1803-1807
Author(s):  
Xiao Liu ◽  
Qing Fan Zhang ◽  
Dian Li Hou
Keyword(s):  
Experimental Results ◽  
The Other ◽  
New Method ◽  
Current Direction ◽  
Practical Application ◽  
Output Current ◽  
Input Line ◽  
One Step

Due to the absence of natural free-wheeling paths, the commutation in matrix rectifiers is much more complicated than in the other kinds of AC-DC converters. In this paper, based on the measurement of the output current direction and the signs of the input line-to-line voltages, a new one-step commutation strategy is applied in the design of matrix rectifier. Experimental results show that the new method is valid and feasible, founding a basis of further practical application.

scholarly journals Knowledge Enhanced Event Causality Identification with Mention Masking Generalizations

2020 ◽  
Author(s):  
Jian Liu ◽  
Yubo Chen ◽  
Jun Zhao
Keyword(s):  
Experimental Results ◽  
The Other ◽  
New Method ◽  
Language Understanding ◽  
Definite Advantage ◽  
Unseen Data ◽  
Benchmark Datasets ◽  
The One ◽  
Context Specific ◽  
Task Adaptation

Identifying causal relations of events is a crucial language understanding task. Despite many efforts for this task, existing methods lack the ability to adopt background knowledge, and they typically generalize poorly to new, previously unseen data. In this paper, we present a new method for event causality identification, aiming to address limitations of previous methods. On the one hand, our model can leverage external knowledge for reasoning, which can greatly enrich the representation of events; On the other hand, our model can mine event-agnostic, context-specific patterns, via a mechanism called event mention masking generalization, which can greatly enhance the ability of our model to handle new, previously unseen cases. In experiments, we evaluate our model on three benchmark datasets and show our model outperforms previous methods by a significant margin. Moreover, we perform 1) cross-topic adaptation, 2) exploiting unseen predicates, and 3) cross-task adaptation to evaluate the generalization ability of our model. Experimental results show that our model demonstrates a definite advantage over previous methods.

Predicting Bugs in Software Performance Test Process

2013 ◽  
Vol 321-324 ◽  
pp. 2965-2968
Author(s):  
Yun Yu ◽  
Feng Chen
Keyword(s):  
Performance Test ◽  
Relevance Vector Machine ◽  
Experimental Results ◽  
The Other ◽  
New Method ◽  
Prediction Algorithm ◽  
Software Performance ◽  
Dynamic Features ◽  
Software Bugs ◽  
Test Process

Accurately predicting software bugs is one of software engineering’s great tasks. Current bug prediction algorithm take one aspect of software for granted, while neglecting the other aspect. This paper extracted static and dynamic features from software, which were used to predict bugs using relevance vector machine algorithm. Experimental results show that the new method outperforms others to a great extent.

The Influence of Water Regime on the Performance of Aquatic Plants

1994 ◽  
Vol 29 (4) ◽  
pp. 127-132 ◽  
Author(s):  
Naomi Rea ◽  
George G. Ganf
Keyword(s):  
Deep Water ◽  
Aquatic Plants ◽  
Water Regime ◽  
Optimal Performance ◽  
Experimental Results ◽  
The Other ◽  
Full Potential ◽  
Influence Of Water ◽  
Emergent Species

Experimental results demonstrate bow small differences in depth and water regime have a significant affect on the accumulation and allocation of nutrients and biomass. Because the performance of aquatic plants depends on these factors, an understanding of their influence is essential to ensure that systems function at their full potential. The responses differed for two emergent species, indicating that within this morphological category, optimal performance will fall at different locations across a depth or water regime gradient. The performance of one species was unaffected by growth in mixture, whereas the other performed better in deep water and worse in shallow.

Mining discriminative patches for script identification in natural scene images

2021 ◽  
Vol 40 (1) ◽  
pp. 551-563
Author(s):  
Liqiong Lu ◽  
Dong Wu ◽  
Ziwei Tang ◽  
Yaohua Yi ◽  
Faliang Huang
Keyword(s):  
Neural Networks ◽  
Experimental Results ◽  
The Other ◽  
Natural Scene ◽  
Fixed Size ◽  
Script Identification ◽  
Aspect Ratios ◽  
Novel Approach ◽  
Public Datasets ◽  
Natural Scene Images

This paper focuses on script identification in natural scene images. Traditional CNNs (Convolution Neural Networks) cannot solve this problem perfectly for two reasons: one is the arbitrary aspect ratios of scene images which bring much difficulty to traditional CNNs with a fixed size image as the input. And the other is that some scripts with minor differences are easily confused because they share a subset of characters with the same shapes. We propose a novel approach combing Score CNN, Attention CNN and patches. Attention CNN is utilized to determine whether a patch is a discriminative patch and calculate the contribution weight of the discriminative patch to script identification of the whole image. Score CNN uses a discriminative patch as input and predict the score of each script type. Firstly patches with the same size are extracted from the scene images. Secondly these patches are used as inputs to Score CNN and Attention CNN to train two patch-level classifiers. Finally, the results of multiple discriminative patches extracted from the same image via the above two classifiers are fused to obtain the script type of this image. Using patches with the same size as inputs to CNN can avoid the problems caused by arbitrary aspect ratios of scene images. The trained classifiers can mine discriminative patches to accurately identify some confusing scripts. The experimental results show the good performance of our approach on four public datasets.

scholarly journals DV-DVFS: merging data variety and DVFS technique to manage the energy consumption of big data processing

2021 ◽  
Vol 8 (1) ◽  
Author(s):  
Hossein Ahmadvand ◽  
Fouzhan Foroutan ◽  
Mahmood Fathy
Keyword(s):  
Big Data ◽  
Energy Consumption ◽  
Processing Time ◽  
Experimental Results ◽  
The Other ◽  
Data Sets ◽  
Multiple Sources ◽  
Evaluation Phase ◽  
Dynamic Voltage ◽  
Processing Resources

AbstractData variety is one of the most important features of Big Data. Data variety is the result of aggregating data from multiple sources and uneven distribution of data. This feature of Big Data causes high variation in the consumption of processing resources such as CPU consumption. This issue has been overlooked in previous works. To overcome the mentioned problem, in the present work, we used Dynamic Voltage and Frequency Scaling (DVFS) to reduce the energy consumption of computation. To this goal, we consider two types of deadlines as our constraint. Before applying the DVFS technique to computer nodes, we estimate the processing time and the frequency needed to meet the deadline. In the evaluation phase, we have used a set of data sets and applications. The experimental results show that our proposed approach surpasses the other scenarios in processing real datasets. Based on the experimental results in this paper, DV-DVFS can achieve up to 15% improvement in energy consumption.

scholarly journals Competing Conventions with Costly Information Acquisition

Games ◽  
2021 ◽  
Vol 12 (3) ◽  
pp. 53
Author(s):  
Roberto Rozzi
Keyword(s):  
Information Acquisition ◽  
Evolutionary Model ◽  
Equilibrium Selection ◽  
The Other ◽  
Group Interactions ◽  
Social Coordination ◽  
Long Run ◽  
Stochastic Stability Analysis ◽  
The Stability ◽  
The Cost

We consider an evolutionary model of social coordination in a 2 × 2 game where two groups of players prefer to coordinate on different actions. Players can pay a cost to learn their opponent’s group: if they pay it, they can condition their actions concerning the groups. We assess the stability of outcomes in the long run using stochastic stability analysis. We find that three elements matter for the equilibrium selection: the group size, the strength of preferences, and the information’s cost. If the cost is too high, players never learn the group of their opponents in the long run. If one group is stronger in preferences for its favorite action than the other, or its size is sufficiently large compared to the other group, every player plays that group’s favorite action. If both groups are strong enough in preferences, or if none of the groups’ sizes is large enough, players play their favorite actions and miscoordinate in inter-group interactions. Lower levels of the cost favor coordination. Indeed, when the cost is low, in inside-group interactions, players always coordinate on their favorite action, while in inter-group interactions, they coordinate on the favorite action of the group that is stronger in preferences or large enough.

A new method for monitoring the redox potential of fuel salt based on the deposition of 95Nb on Hastelloy C276

2021 ◽  
Vol 109 (5) ◽  
pp. 357-365
Author(s):  
Zhiqiang Cheng ◽  
Zhongqi Zhao ◽  
Junxia Geng ◽  
Xiaohe Wang ◽  
Jifeng Hu ◽  
...  
Keyword(s):  
Redox Potential ◽  
Molten Salt ◽  
Specific Activity ◽  
Chemical Reduction ◽  
Quantitative Approach ◽  
Experimental Results ◽  
New Method ◽  
Molten Salt Reactor ◽  
Fuel Salt ◽  
Well Correlation

Abstract To develop the application of 95Nb as an indicator of redox potential for fuel salt in molten salt reactor (MSR), the specific activity of 95Nb in FLiBe salt and its deposition of 95Nb on Hastelloy C276 have been studied. Experimental results indicated that the amount of 95Nb deposited on Hastelloy C276 resulted from its chemical reduction exhibited a positive correlation with the decrease of 95Nb activity in FLiBe salt and the relative deposition coefficient of 95Nb to 103Ru appeared a well correlation with 95Nb activity in FLiBe salt. Both correlations implied that the measurement of 95Nb activity deposited on Hastelloy C276 specimen might provide a quantitative approach for monitoring the redox potential of fuel salt in MSR.

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