scholarly journals Research on Evaluation Method of Sports Events Based on Edge Algorithm

2021 ◽  
Vol 2021 ◽  
pp. 1-9
Author(s):  
FangXiao Deng ◽  
A. Gudamu
Keyword(s):  
Evaluation Method ◽  
Computational Cost ◽  
Computational Time ◽  
Learning Technology ◽  
Data Set ◽  
Research On Evaluation ◽  
Sports Events ◽  
Traditional Sports ◽  
Set Up ◽  
High Computational Cost

In view of the high computational cost and long computational time of IoT edge algorithm in traditional sports event evaluation, this paper optimizes IoT edge algorithm by introducing deep reinforcement learning technology. Set the IoT edge algorithm cycle through the IoT topology to obtain the data upload speed. In order to improve the evaluation efficiency of sports events, the process of edge algorithm is designed. The contribution rate of evaluation index is calculated, and the consistency, minimum deviation, and minimum difference of the results are taken as the standard to design the evaluation method of sports events. In order to verify the performance of the optimized edge algorithm, the test data set and test platform are set up and the comparative experiment is designed. Compared with the traditional methods, the edge algorithm based on DSLL has lower computational cost, shorter computational time, higher evaluation accuracy, and more practical results.

Evolution Strategy Sampling Consensus for Robust Estimator

2016 ◽  
Vol 20 (5) ◽  
pp. 788-802 ◽  
Author(s):  
Yuichiro Toda ◽  
◽  
Naoyuki Kubota
Keyword(s):  
Genetic Diversity ◽  
Computational Cost ◽  
Evolution Strategy ◽  
Computational Time ◽  
Adaptive Mutation ◽  
Robust Estimator ◽  
Data Set ◽  
Trade Off ◽  
Matrix Estimation ◽  
3D Point Clouds

RANdom SAmple Consensus (RANSAC) has been applied to many 3D image processing problems such as homography matrix estimation problems and shape detection from 3D point clouds, and is one of the most popular robust estimator methods. However, RANSAC has a problem related to the trade-off between computational cost and stability of search because RANSAC is based on random sampling. Genetic Algorithm SAmple Consensus (GASAC) based on a population-based multi-point search was proposed in order to improve RANSAC. GASAC can improve the performance of search. However, it is sometimes difficult to maintain the genetic diversity in the search if the large size of outliers is included in a data set. Furthermore, a computational time of GASAC sometimes is slower than that of RANSAC because of calculation of the genetic operators. This paper proposes Evolution Strategy SAmple Consensus (ESSAC) as a new robust estimator. ESSAC is based on Evolution Strategy in order to maintain the genetic diversity. In ESSAC, we apply two heuristic searches to ESSAC. One is a search range control, the other is adaptive/self-adaptive mutation. By applying these heuristic searches, the trade-off between computational speed and search stability can be improved. Finally, this paper shows several experimental results in order to evaluate the effectiveness of the proposed method.

scholarly journals Comparison between Meta-Heuristic Algorithms for Path Planning

2020 ◽  
Author(s):  
Lídia Rocha ◽  
Kelen Vivaldini
Keyword(s):  
Execution Time ◽  
Path Length ◽  
Heuristic Algorithms ◽  
Computational Cost ◽  
Computational Time ◽  
Complex Environments ◽  
Swarm Optimization ◽  
Glowworm Swarm Optimization ◽  
Aerial Vehicle ◽  
High Computational Cost

Unmanned Aerial Vehicle (UAV) has been increasingly employed in several missions with a pre-defined path. Over the years, UAV has become necessary in complex environments, where it demands high computational cost and execution time for traditional algorithms. To solve this problem meta-heuristic algorithms are used. Meta-heuristics are generic algorithms to solve problems without having to describe each step until the result and search for the best possible answer in an acceptable computational time. The simulations are made in Python, with it, a statistical analyses was realized based on execution time and path length between algorithms Particle Swarm Optimization (PSO), Grey Wolf Optimization (GWO) and Glowworm Swarm Optimization (GSO). Despite the GWO returns the paths in a shorter time, the PSO showed better performance with similar execution time and shorter path length. However, the reliability of the algorithms will depend on the size of the environment. PSO is less reliable in large environments, while the GWO maintains the same reliability.

scholarly journals Estudo comparativo de métricas de ranking em Redes Sociais

2020 ◽  
Author(s):  
Samuel O. Silva ◽  
Bruno O. Goulart ◽  
Maria Júlia M. Schettini ◽  
Carolina Xavier ◽  
João Gabriel Silva
Keyword(s):  
Information Diffusion ◽  
Computational Cost ◽  
Rank Correlation ◽  
Correlation Coefficients ◽  
Computational Time ◽  
Short Term ◽  
Vertex Ranking ◽  
Influential Nodes ◽  
Low Computational Cost ◽  
High Computational Cost

The use of modeling and application of complex networks in several areas of knowledge have become an important tool for understanding different phenomena; among them some related to the structures and dissemination of information on social medias. In this sense, the use of a network's vertex ranking can be applied in the detection of influential nodes and possible foci of information diffusion. However, calculating the position of the vertices in some of these rankings may require a high computational cost. This paper presents a comparative study between six ranking metrics applied in different social medias. This comparison is made using the rank correlation coefficients. In addition, a study is presented on the computational time spent by each ranking. Results show that the Grau ranking metric has a greater correlation with other metrics and has low computational cost in its execution, making it an efficient indication in detecting influential nodes when there is a short term for the development of this activity.

scholarly journals Hardware in the loop co-simulation of finite set-model predictive control using FPGA for a three level CHB inverter

2020 ◽  
Vol 11 (4) ◽  
pp. 1719
Author(s):  
Mai Van Chung ◽  
Do Tuan Anh ◽  
Phuong Vu ◽  
Linh Manh Nguyen
Keyword(s):  
Control Algorithm ◽  
Computational Cost ◽  
Current Control ◽  
Computational Time ◽  
Hardware In The Loop ◽  
Field Programmable ◽  
Power Switches ◽  
Finite Set ◽  
Predictive Controller ◽  
High Computational Cost

Along with the development of powerful microprocessors and microcontrollers, the applications of the model predictive controller, which requires high computational cost, to fast dynamical systems such as power converters and electric drives have become a tendency recently. In this paper, two solutions are offered to quickly develop the finite set predictive current control for induction motor fed by 3-level H-Bridge cascaded inverter. First, the field programmable gate array (FPGA) with capability of parallel computation is employed to minimize the computational time. Second, the hardware in the loop (HIL) co-simulation is used to quickly verify the developed control algorithm without burden of time on hardware design since the motor and the power switches are emulated on a real-time platform with high-fidelity mathematical models. The implementation procedure and HIL co-simulation results of the developed control algorithm shows the effectiveness of the proposed solution.

Research on Evaluation Method of the Bridge Strengthening Effect Based on Fiber Optic Sensor

2013 ◽  
Vol 791-793 ◽  
pp. 1901-1904 ◽  
Author(s):  
Yong Jiu Wei ◽  
Jin Tao Zhang ◽  
Yun Long Zhang ◽  
Xiang Chun Xi ◽  
Kun Li ◽  
...  
Keyword(s):  
Evaluation Method ◽  
Fiber Optic ◽  
Fiber Optic Sensor ◽  
Strengthening Effect ◽  
Research On Evaluation ◽  
Optic Sensor ◽  
Bridge Strengthening ◽  
Railroad Bridge ◽  
Set Up ◽  
Bragg Grating Sensor

A new evaluation method of the bridge strengthening effect is proposed based on the fiber optic sensor. The monitor layout scheme of bridge is designed to monitor the bridge strengthening effect accurately by measuring dynamic load moment and transverse vibration of the railroad bridge using the fiber Bragg grating sensor. At first, the paper presents the evaluation principle of the bridge strengthening. And then the fiber sensors are set up on the railroad bridge for extracting data of the health status from these sensors. The effect of the strengthening could be shown from the data change after bridge strengthening applied. The researches provide the scheme of the bridge strengthening quality evaluation, which is the base for the control of construction quality for new bridge strengthening technology.

An Alternate Algorithm for (3x3) Median Filtering of Digital Images

2012 ◽  
Vol 2 (1) ◽  
pp. 7-9 ◽  
Author(s):  
Satinderjit Singh
Keyword(s):  
Median Filter ◽  
Computational Cost ◽  
Spatial Coherence ◽  
General Purpose ◽  
Median Filtering ◽  
Basic Algorithm ◽  
Temporal Complexity ◽  
Filter Kernel ◽  
One Step ◽  
High Computational Cost

Median filtering is a commonly used technique in image processing. The main problem of the median filter is its high computational cost (for sorting N pixels, the temporal complexity is O(N·log N), even with the most efficient sorting algorithms). When the median filter must be carried out in real time, the software implementation in general-purpose processorsdoes not usually give good results. This Paper presents an efficient algorithm for median filtering with a 3x3 filter kernel with only about 9 comparisons per pixel using spatial coherence between neighboring filter computations. The basic algorithm calculates two medians in one step and reuses sorted slices of three vertical neighboring pixels. An extension of this algorithm for 2D spatial coherence is also examined, which calculates four medians per step.

Improving the Computational Cost for Copied Region Detection in Forensic Images

2016 ◽  
Vol 2 (1) ◽  
pp. 55
Author(s):  
Tu Huynh-Kha ◽  
Thuong Le-Tien ◽  
Synh Ha ◽  
Khoa Huynh-Van
Keyword(s):  
Wavelet Transform ◽  
Euclidean Distance ◽  
Research Work ◽  
Computational Cost ◽  
Correlation Coefficients ◽  
Zernike Moments ◽  
Computational Time ◽  
Discrete Wavelet ◽  
Feature Vectors ◽  
Region Detection

This research work develops a new method to detect the forgery in image by combining the Wavelet transform and modified Zernike Moments (MZMs) in which the features are defined from more pixels than in traditional Zernike Moments. The tested image is firstly converted to grayscale and applied one level Discrete Wavelet Transform (DWT) to reduce the size of image by a half in both sides. The approximation sub-band (LL), which is used for processing, is then divided into overlapping blocks and modified Zernike moments are calculated in each block as feature vectors. More pixels are considered, more sufficient features are extracted. Lexicographical sorting and correlation coefficients computation on feature vectors are next steps to find the similar blocks. The purpose of applying DWT to reduce the dimension of the image before using Zernike moments with updated coefficients is to improve the computational time and increase exactness in detection. Copied or duplicated parts will be detected as traces of copy-move forgery manipulation based on a threshold of correlation coefficients and confirmed exactly from the constraint of Euclidean distance. Comparisons results between proposed method and related ones prove the feasibility and efficiency of the proposed algorithm.

Methods for studying dissolved oxygen levels in coastal and estuarine waters receiving combined sewer overflows

1995 ◽  
Vol 32 (2) ◽  
pp. 95-103
Author(s):  
José A. Revilla ◽  
Kalin N. Koev ◽  
Rafael Díaz ◽  
César Álvarez ◽  
Antonio Roldán
Keyword(s):  
Dissolved Oxygen ◽  
Coastal Waters ◽  
Computational Cost ◽  
Oxygen Deficit ◽  
Alternative Methods ◽  
Coastal Zones ◽  
Combined Sewer Overflows ◽  
Sewer Systems ◽  
Combined Sewer ◽  
High Computational Cost

One factor in determining the transport capacity of coastal interceptors in Combined Sewer Systems (CSS) is the reduction of Dissolved Oxygen (DO) in coastal waters originating from the overflows. The study of the evolution of DO in coastal zones is complex. The high computational cost of using mathematical models discriminates against the required probabilistic analysis being undertaken. Alternative methods, based on such mathematical modelling, employed in a limited number of cases, are therefore needed. In this paper two alternative methods are presented for the study of oxygen deficit resulting from overflows of CSS. In the first, statistical analyses focus on the causes of the deficit (the volume discharged). The second concentrates on the effects (the concentrations of oxygen in the sea). Both methods have been applied in a study of the coastal interceptor at Pasajes Estuary (Guipúzcoa, Spain) with similar results.

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