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EMG Signal Processing and Application Based on Empirical Mode Decomposition
Xu Mengying,
Yang Xiaoli,
Xu Chenli,
Yang Bin
Issue:
Volume 4, Issue 6, November 2019
Pages:
99-103
Received:
10 October 2019
Accepted:
22 November 2019
Published:
6 December 2019
Abstract: With the development of rehabilitation medicine and kinematics, the study of Electromyographic (EMG) signal come into people’s sight. The information obtained from the surface EMG signals can not only reflect the motion state of muscles and joints, but also judge people's motion type, which is one of the important indexes in the study of human body. Based on the EMG as the research object with the detailed analysis to understand the EMG of time domain, frequency domain and SNR, etc. The study of EMG signal denoising and feature extraction is of great value and significance in the field of medical diagnosis. Such as using sEMG signals to assess muscle status and determine postoperative recovery status. Empirical Mode Decomposition (EMD) based on hilbert-huang is a time frequency analysis method for non-linear and non-stationary signals like EMG signals, which has unique advantages and broad prospects in signal analysis and processing. In this paper, we used EMD to decompose signal which contain multiple frequency component into a series of inherent modal parameters, and then combine the method of EMD decomposition and wavelet transform to carry out denoising processing and feature extraction for EMG signals, which can effectively weaken the noise of surface EMG signals and reflect the essential characteristics of the original signal, and classify the damage of EMG signals by analyzing the characteristic values.
Abstract: With the development of rehabilitation medicine and kinematics, the study of Electromyographic (EMG) signal come into people’s sight. The information obtained from the surface EMG signals can not only reflect the motion state of muscles and joints, but also judge people's motion type, which is one of the important indexes in the study of human body...
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Stability and Oscillatory Behavior of the Solutions on a Class of Coupled Van der Pol-Duffing Equations with Delays
Issue:
Volume 4, Issue 6, November 2019
Pages:
104-111
Received:
31 October 2019
Accepted:
29 November 2019
Published:
10 December 2019
Abstract: In the present paper, a class of coupled van der Pol-Duffing oscillators with a nonlinear friction of higher polynomial order model which involves time delays is investigated. The coefficients of the highest order of the polynomial determine the boundedness of the solutions. With special attention to the boundedness of the solutions and the instability of the unique equilibrium point of linearized system, some sufficient conditions to guarantee the existence of oscillatory solutions for the model are obtained based on the generalized Chafee's criterion. Convergence of the trivial solution is determined by the negative real part of eigenvalues of the linearized system. Examples are provided to demonstrate the reduced conservativeness for the parameters of the proposed results. The results obtained shown that the passive decay rate in the model affects the oscillatory frequency and amplitude. When a permanent oscillation occurred, time delays affect mainly oscillatory frequency and amplitude slightly.
Abstract: In the present paper, a class of coupled van der Pol-Duffing oscillators with a nonlinear friction of higher polynomial order model which involves time delays is investigated. The coefficients of the highest order of the polynomial determine the boundedness of the solutions. With special attention to the boundedness of the solutions and the instabi...
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Determination of Forest Reserves Area Using Images Processed by Drones, Neural Networks and Monte Carlo Method
Paulo Marcelo Tasinaffo,
Afonso Henriques Moreira Santos,
Elias Cavalcante Junior,
Carlos Henrique Quartucci Forster,
Rafael Augusto Lopes Shigemura,
Rafael Jacomel,
Victor Ulisses Pugliese,
Bruno Koshin Vazquez Iha,
Adilson Marques da Cunha,
Gildarcio Sousa Goncalves,
Luiz Alberto Vieira Dias
Issue:
Volume 4, Issue 6, November 2019
Pages:
112-129
Received:
26 June 2019
Accepted:
30 July 2019
Published:
24 December 2019
Abstract: Land cover classification analysis from satellite imagery methods are important because they are the basis for characterizing surface conditions and evolution, supporting the management and optimization of land resources, evaluating global climate and environmental changes, and facilitating sustainable regional economic and social development. In order to address these necessities, artificial neural networks have been used extensively. In addition, other methods based on computer vision are very useful to solve this task. In this paper, the authors propose an approach based on Monte Carlo method and artificial neural networks in order to classify regions of small forest reserves from drones’ images and calculate their respective areas. Next to the small forest reserve will be extended a standard rectangular tarpaulin of 250 square meters and based on this reference it will be possible to calculate the area of the forest reserve if the ground is relatively flat. The proposed approach will be compared with a method based on watershed algorithm. The automatic calculation of the forest area through images generated by drones has much practical application for environmental engineers, for example, for the calculation of environmental impact and determination of carbon loss if such forests are consequently deforested.
Abstract: Land cover classification analysis from satellite imagery methods are important because they are the basis for characterizing surface conditions and evolution, supporting the management and optimization of land resources, evaluating global climate and environmental changes, and facilitating sustainable regional economic and social development. In o...
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Symmetric I* Restriction Method of Fuzzy Inference
Yiming Tang,
Guangqing Bao
Issue:
Volume 4, Issue 6, November 2019
Pages:
130-137
Received:
12 November 2019
Accepted:
11 December 2019
Published:
24 December 2019
Abstract: As one of important parts of fuzzy logic, fuzzy inference plays a vital role in the fields of fuzzy control, artificial intelligence, affective computing, image processing and so forth. Two key problems of fuzzy inference are FMP (fuzzy modus ponens) and FMT (fuzzy modus tollens). How to get the ideal solution for FMP and FMT is a difficult problem in the area of fuzzy logic. Aiming at such problem, from the idea of symmetric implicational reasoning, triple I* method and restriction theory, we put forward and investigate the α-symmetric I* restriction method, and then generalize it to the α(x,y)-symmetric I* restriction method. To begin with, the α-symmetric I* restriction principle and the α(x,y)-symmetric I* restriction principle are established. Furthermore, the equivalent condition to let a basic restriction solution exist is given. Then the unified solutions of the α-symmetric I* restriction method and the α(x,y)-symmetric I* restriction method are achieved for R-implications and (S, N)-implications. Besides, some special cases of optimal solutions are shown. Finally, the corresponding conclusions are provided when the two methods degenerate into the α-triple I* restriction method and α(x,y)-triple I* restriction method. These research results would be an important improvement for the fields of fuzzy inference, fuzzy logic and related applications.
Abstract: As one of important parts of fuzzy logic, fuzzy inference plays a vital role in the fields of fuzzy control, artificial intelligence, affective computing, image processing and so forth. Two key problems of fuzzy inference are FMP (fuzzy modus ponens) and FMT (fuzzy modus tollens). How to get the ideal solution for FMP and FMT is a difficult problem...
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An Uncertain Resource Constrained Scheduling Model Based on Uncertainty Theory
Qian Zhang,
Xiaosheng Wang,
Wei Li,
Hao Hu
Issue:
Volume 4, Issue 6, November 2019
Pages:
138-141
Received:
20 November 2019
Accepted:
16 December 2019
Published:
27 December 2019
Abstract: Resource constrained project scheduling problem is to make a schedule for minimizing of the completion time or total cost subject to precedence rules and resource constraints. Traditional resource constrained project scheduling problem research takes into account achieve management goal in certain environment. However, there are many uncertainties in practical projects due to the uncertain factors, which leads to the change of resource availability. In this paper, for better described the uncertain resource constrained project scheduling problem, we firstly consider the uncertain resource availability project scheduling problem based on uncertainty theory. To meet the manger goals, it is assumed that the increased quantities of resource are uncertain variables and the finish time of each activity is a decision variable. Then, an uncertain resource constrained model is built. The goals of the model are to minimize the completion time and the total cost which composed by the activity cost and the additional resource cost. One of the constraints is the finish-start precedence relationship among the project activities. The other constraint is the resource constraint in which the demand of resource shall not exceed the total supply of resource for each resource type at any time. Furthermore, the equivalent form of the above model is given and its equivalence is proved. Finally, a genetic algorithm is applied to search for quasi-optimal scheduling, and a project example is given to illustrate the effectiveness of the model.
Abstract: Resource constrained project scheduling problem is to make a schedule for minimizing of the completion time or total cost subject to precedence rules and resource constraints. Traditional resource constrained project scheduling problem research takes into account achieve management goal in certain environment. However, there are many uncertainties ...
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A Tanker Port Positioning Method of Quantitative Loading Automation
Wenliang Zhu,
Yanzhe Ni,
Tingbo Huang,
Jiahao Han
Issue:
Volume 4, Issue 6, November 2019
Pages:
142-148
Received:
12 November 2019
Accepted:
13 December 2019
Published:
30 December 2019
Abstract: Laser scanning ranging radar is an important tool for machines to perceive the surrounding environment and is widely used in the power, forestry, surveying and mapping industries. At present, the loading of oil and grain oil in our country generally adopts the way of manual loading. The loading arm is inserted into the tank of the tanker for refueling, and the loading operation is very frequent. In order to realize automatic control of grain and oil loading, radar is needed to assist the robot to locate the oil port of the tanker. In this paper, a 360-degree laser scanning ranging radar is used to collect characteristic data of oil hole of tanker for the first time in simulated environment. Cubic spline interpolation was used to smooth and correct the radar scan data. Based on the feature that the distance data of oil port will change rapidly, an edge feature recognition algorithm is proposed to screen and calculate the target point, and then convert it to cartesian coordinate point, which can be used as the positioning target of the robot unit of quantitative loading system. The experimental results show that the method can locate the center of the circle accurately and meet the requirement of feature recognition accuracy.
Abstract: Laser scanning ranging radar is an important tool for machines to perceive the surrounding environment and is widely used in the power, forestry, surveying and mapping industries. At present, the loading of oil and grain oil in our country generally adopts the way of manual loading. The loading arm is inserted into the tank of the tanker for refuel...
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