scholarly journals Application of lidars in the monitoring system of hydrophysical disturbances from moving objects

2021 ◽  
Vol 3 (397) ◽  
pp. 127-132
Author(s):  
V. Polenin ◽  
Keyword(s):  
Monitoring System ◽  
Moving Objects ◽  
Scientific Discovery ◽  
Physical Phenomenon ◽  
Problem Formulation ◽  
Programming System ◽  
Navigation Problem ◽  
Correct Conclusion ◽  
Scientific Results ◽  
Matlab Programming

Object and purpose of research. The object of this research study is a physical phenomenon of lidar observation of hydrophysical disturbances from an object moving underwater confirmed by the scientific discovery registered with Russian Academy of Natural Sciences (RANS). The purpose is to briefly present the phenomenon essence and to validate the feasibility of underwater monitoring system involving lidars. Materials and methods. The work materials is the phenomenon description and publications confirming its reliability. The feasibility of underwater monitoring system employing lidars is validated by model representation of this system as a group of distributed fixed lidars, which record time instants when a moving underwater object is passing by. The navigation task of locating its coordinates and parameters of motion is solved. Main results. The results demonstrate exact solutions to the problem implemented in MATLAB programming system, which confirms that the model is adequate and its software implementation is correct. Conclusion. The purpose of the work to examine the feasibility of lidar underwater monitoring system is achieved. The new scientific results are the problem formulation and the method of solving a navigation problem to find coordinates and parameters of motion from lidar-detected instants of hydrophysical disturbances. A hypothetical lidar-based monitoring system, if verified experimentally that lidars are sufficiently long-range instruments, is a promising idea.

scholarly journals A Phlegm Stagnation Monitoring Based on VDS Algorithm

2020 ◽  
Vol 2020 ◽  
pp. 1-11
Author(s):  
Zhiguo Gao ◽  
Xin Yu
Keyword(s):  
Real Time ◽  
Monitoring System ◽  
Moving Objects ◽  
Recognition Rate ◽  
Differential Method ◽  
Video Frame ◽  
Moving Targets ◽  
System A ◽  
Video Images ◽  
Svm Algorithm

In the nonmedical sputum monitoring system, a practical solution for phlegm stagnation care of patients was proposed. Through the camera, the video images of patients’ laryngeal area were obtained in real time. After processing and analysis on these video frame images, the throat movement area was found out. A three-frame differential method was used to detect the throat moving targets. Anomalies were identified according to the information of moving targets and the proposed algorithm. Warning on the abnormal situation can help nursing personnel to deal with sputum blocking problem more effectively. To monitor the patients’ situation in real time, this paper proposed a VDS algorithm, which extracted the speed characteristics of moving objects and combined with the DTW algorithm and SVM algorithm for sequence image classification. Phlegm stagnation symptoms of patients were identified timely for further medical care. In order to evaluate the effectiveness, our method was compared with the DTW, SVM, CTM, and HMM methods. The experimental results showed that this method had a higher recognition rate and was more practical in a nonmedical monitoring system.

Study on Tracking in Interested Moving Objects

2011 ◽  
Vol 382 ◽  
pp. 418-421
Author(s):  
Dong Yan Cui ◽  
Zai Xing Xie
Keyword(s):  
Computational Complexity ◽  
Real Time ◽  
Monitoring System ◽  
Moving Objects ◽  
Moving Object ◽  
Experimental Results ◽  
Real Time Monitoring ◽  
Automatic Program ◽  
Inter Frame

This paper presents an automatic program to track in moving objects, using segmentation algorithm quickly and efficiently after the division of a moving object, in the follow-up frame through the establishment of inter-frame vectors to track moving objects of interest. Experimental results show that the algorithm can accurately and effectively track moving objects of interest, and because the algorithm is simple, the computational complexity is small, can be well positioned to meet real-time monitoring system in the extraction of moving objects of interest and tracking needs.

scholarly journals Identification of rolling stock in railway transport management

2018 ◽  
Vol 19 (6) ◽  
pp. 176-179
Author(s):  
Jarosław Moczarski
Keyword(s):  
Transport Process ◽  
Moving Objects ◽  
Computer Application ◽  
Rolling Stock ◽  
Programming Environment ◽  
Railway Transport ◽  
Analysis Techniques ◽  
Matlab Programming ◽  
Transport Management ◽  
Subsequent Identification

An important factor improving the safety of the railway transport process is the automatic recognition of the rolling stock and the transported loads. Using modern data acquisition and analysis techniques allows to identify moving objects by assessing their shape and size. For the creation of digital models of the studied objects and their subsequent identification there was developed a computer application working in Matlab programming environment. The application use the functions of designing, implementing, visualizing and simulating neural networks. The configuration of the test stand allows for carrying out experiments using analog and digital sensors.

scholarly journals Using Deep Learning for Visual Navigation of Drone with Respect to 3D Ground Objects

Mathematics ◽  
2020 ◽  
Vol 8 (12) ◽  
pp. 2140
Author(s):  
Oleg Kupervasser ◽  
Hennadii Kutomanov ◽  
Ori Levi ◽  
Vladislav Pukshansky ◽  
Roman Yavich
Keyword(s):  
Neural Network ◽  
Artificial Neural Network ◽  
Deep Learning ◽  
Time Delay ◽  
Moving Objects ◽  
Visual Navigation ◽  
Navigation Problem ◽  
Position And Orientation ◽  
Artificial Neural ◽  
The Difference

In the paper, visual navigation of a drone is considered. The drone navigation problem consists of two parts. The first part is finding the real position and orientation of the drone. The second part is finding the difference between desirable and real position and orientation of the drone and creation of the correspondent control signal for decreasing the difference. For the first part of the drone navigation problem, the paper presents a method for determining the coordinates of the drone camera with respect to known three-dimensional (3D) ground objects using deep learning. The algorithm has two stages. It causes the algorithm to be easy for interpretation by artificial neural network (ANN) and consequently increases its accuracy. At the first stage, we use the first ANN to find coordinates of the object origin projection. At the second stage, we use the second ANN to find the drone camera position and orientation. The algorithm has high accuracy (these errors were found for the validation set of images as differences between positions and orientations, obtained from a pretrained artificial neural network, and known positions and orientations), it is not sensitive to interference associated with changes in lighting, the appearance of external moving objects and the other phenomena where other methods of visual navigation are not effective. For the second part of the drone navigation problem, the paper presents a method for stabilization of drone flight controlled by autopilot with time delay. Indeed, image processing for navigation demands a lot of time and results in a time delay. However, the proposed method allows to get stable control in the presence of this time delay.

Monitoring System for Persons With Alzheimer's Disease via Video-Object Tracking

2018 ◽  
Vol 9 (2) ◽  
pp. 18-36
Author(s):  
Haitham Asaad Al-Anssari ◽  
Ikhlas Abdel-Qader ◽  
Maureen Mickus
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Optical Flow ◽  
Monitoring System ◽  
Skin Color ◽  
Moving Objects ◽  
Color Space ◽  
Color Information ◽  
Region Detection ◽  
Skin Region

This article presents a framework for a food intake monitoring system intended for use with persons with Alzheimer's disease and other dementias. Alzheimer's disease has a significant impact on the individual's ability to perform their daily activities including eating. Providing assistance with feeding is a major challenge for caregivers, including a significant time commitment. We present a vision-based system that tracks moving objects, such as the hand, using a combined optical flow and skin region detection algorithms. Skin detection is implemented using two different methods. Hue, saturation, and value (HSV) color space, which is on separation of the illuminance component from chrominance one as the first method and skin color information is extracted from subject's face detected using Viola-Johns algorithm for the second method. Once face and other moving skin regions are detected, bounding boxes are created and used to track all moving regions over the video frames, recognizing eating behavior or the lack of it. Based on experimental results the proposed method using optical flow and skin regions segmentation using HSV color detects the hand to mouth eating motion with 92.12% accuracy. The optical flow and skin region segmentation based on face color information achieves a higher accuracy of 94.29%.

On the Limitations of Force Tracking Control for Hydraulic Servosystems

1999 ◽  
Vol 121 (2) ◽  
pp. 184-190 ◽  
Author(s):  
Andrew Alleyne ◽  
Rui Liu
Keyword(s):  
Tracking Control ◽  
Physical Phenomenon ◽  
Problem Formulation ◽  
Feedback Mechanism ◽  
Open Loop ◽  
Simple Solution ◽  
Hydraulic Actuator ◽  
Fundamental Limitations ◽  
Force Tracking ◽  
Solution Methods

This paper presents analysis of a particular force tracking control problem for rectilinear hydraulic actuators governed by a servovalve. It presents no new theory, but rather uses a revealing model reduction insight coupled with Classical analysis to explain a physical phenomenon. As such, this work is an attempt to explain why a seemingly innocuous problem is more subtle than initially believed. A motivation for this problem is given along with prior attempts at a simple solution. It is shown that simple controller solutions are quite adequate for other types of control objectives such as force regulation or position tracking. However, most simple solution methods are shown to be inadequate for force tracking due to fundamental limitations of the problem formulation. Due to an inherent feedback mechanism, the poles of the plant being forced by the hydraulic actuator become zeros of the open loop force transfer function. Therefore, more advanced control algorithms are shown to be a necessity rather than a luxury.

THE MULTIAGENT TECHNOLOGY AND PARADIGM WITHIN SCIENTIFIC DISCOVERY

2007 ◽  
Vol 16 (02) ◽  
pp. 219-242 ◽  
Author(s):  
FRANCESCO AMIGONI ◽  
VIOLA SCHIAFFONATI
Keyword(s):  
Computer Science ◽  
Philosophy Of Science ◽  
Multiagent Systems ◽  
Scientific Practice ◽  
Scientific Discovery ◽  
Theoretical Framework ◽  
The Other ◽  
Research Activity ◽  
Scientific Results ◽  
The One

Scientific practice has been rapidly evolving in the last years under the pressure of developments in computer science and technology. In this paper we present some of the results of our research activity at the boundary between computer science and philosophy of science started in 1997 under Marco Somalvico's impulse and guidance. In particular, we discuss two roles that multiagent systems can play in scientific discovery. From the one hand, they can support scientific practice; from the other hand, they can represent scientific results. The theoretical framework presented in this paper is exemplified in concrete by illustrating specific implemented systems, both taken from the literature and developed by ourselves.

On-Line Fan Monitoring System Based on Improved Intelligent Regression Algorithm

2013 ◽  
Vol 291-294 ◽  
pp. 1874-1879 ◽  
Author(s):  
Xiao Gang Xu ◽  
Song Ling Wang ◽  
Jin Lian Liu ◽  
Fei Li ◽  
Hui Jie Wang
Keyword(s):  
Monitoring System ◽  
Flow Curve ◽  
Differential Pressure ◽  
Support Vector ◽  
Pressure Flow ◽  
Svm Model ◽  
Curve Model ◽  
On Line ◽  
Matlab Programming ◽  
Fitting Error

The running state of the fan has significant influence on the safety and economy of the power plant unit, so it is necessary to monitor the fan performance and running state in real time. According to the basic theory of the fan, there is a stable, good nonlinear mapping relation between the inlet pressure difference and flow, which can be utilized to monitor the flow of the fan. Thus, the fan differential pressure - flow curve model is established by the optimized BP neural network and the modified Support Vector Machine (SVM). The fitting error shows that the improved SVM model is better. Finally, the on-line fan monitoring system software is established by using Visual Basic (VB) language and Matlab programming based on the improved SVM fan differential pressure - flow curve model, which can accurately monitor the fan operation.

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