scholarly journals Active identification of object parameters with non-scalar inputs-outputs

2020 ◽  
Vol 1703 ◽  
pp. 012029
Author(s):  
G V Troshina ◽  
А А Voevoda
Keyword(s):  
Active Identification ◽  
Object Parameters

THE REALIZATION OF THE ITERATIVE METHOD OF THE LEAST SQUARES FOR THE ESTIMATION OF STATIC OBJECT PARAMETERS IN MATLAB ENVIRONMENT

2017 ◽  
pp. 28-36
Author(s):  
Galina Vasil’evna Troshina ◽  
Alexander Aleksandrovich Voevoda
Keyword(s):  
Parameter Estimation ◽  
Iterative Method ◽  
Least Squares ◽  
Input Signal ◽  
Layer Structure ◽  
Estimation Procedure ◽  
Parameter Estimation Procedure ◽  
Noise Simulation ◽  
Static Object ◽  
Object Parameters

It was suggested to use the system model working in real time for an iterative method of the parameter estimation. It gives the chance to select a suitable input signal, and also to carry out the setup of the object parameters. The object modeling for a case when the system isn't affected by the measurement noises, and also for a case when an object is under the gaussian noise was executed in the MatLab environment. The superposition of two meanders with different periods and single amplitude is used as an input signal. The model represents the three-layer structure in the MatLab environment. On the most upper layer there are units corresponding to the simulation of an input signal, directly the object, the unit of the noise simulation and the unit for the parameter estimation. The second and the third layers correspond to the simulation of the iterative method of the least squares. The diagrams of the input and the output signals in the absence of noise and in the presence of noise are shown. The results of parameter estimation of a static object are given. According to the results of modeling, the algorithm works well even in the presence of significant measurement noise. To verify the correctness of the work of an algorithm the auxiliary computations have been performed and the diagrams of the gain behavior amount which is used in the parameter estimation procedure have been constructed. The entry conditions which are necessary for the work of an iterative method of the least squares are specified. The understanding of this algorithm functioning principles is a basis for its subsequent use for the parameter estimation of the multi-channel dynamic objects.

scholarly journals Physical Parameter Identification Algorithm Modeling for Complex Microsystem via Triangulation Functions

2018 ◽  
Vol 7 (4.36) ◽  
pp. 962
Author(s):  
Elena N. Meshcheryakova ◽  
. .
Keyword(s):  
Parameter Identification ◽  
Physical Parameter ◽  
Delaunay Triangulation ◽  
Model Development ◽  
Physical Object ◽  
Identification Algorithm ◽  
Classification Analysis ◽  
Advantages And Disadvantages ◽  
Object Parameters ◽  
D Model

This article describes the possibility of triangulation function use for the classification, analysis and identification of complex microsystem physical object parameters. They analyzed the existing methods and identification algorithms, their advantages and disadvantages are highlighted. The existing methods of triangulation are considered, the possibility of Delaunay triangulation is described for surfactant signal 3-D model development and analysis. They developed the algorithm to identify the state of an object using the triangulation function that takes into account the change of node coordinates and the length of the triangulation grid edges. They presented the visual UML model. The conclusions are drawn about the possibility of triangulation function use for the analysis of complex microsystem state.  

Organization of primary medical care for patients with osteoporosis

2021 ◽  
Vol 25 (2) ◽  
pp. 7-17
Author(s):  
Elena N. Gladkova
Keyword(s):  
High Risk ◽  
Medical Care ◽  
Hip Fractures ◽  
Osteoporotic Fractures ◽  
Population Based ◽  
Subsequent Treatment ◽  
Primary Medical Care ◽  
Screening Programs ◽  
Active Identification ◽  
The World

The author revises the latest evidence in the literature regarding of organizing medical care for patients with osteoporosis in primary medical care. In the world, there is an increase in the group of older people (60 years and older), therefore, the problem of osteoporosis and osteoporotic fractures becomes very urgent. In Russia, the number of hip fractures will increase by 70% by 2050 compared to 2015. The article provides an overview of studies demonstrating the clinical and cost-effectiveness of population-based screening programs for the identification and subsequent treatment of patients at high risk of fractures, and discusses the issues of secondary prevention of fractures. With the active identification of patients at high risk of fractures and the initiation of antiosteoporotic therapy, a decrease in the incidence of osteoporotic fractures, including hip fractures, is expected.

Active Identification of Petri Net Models

2012 ◽  
Vol 45 (29) ◽  
pp. 278-285
Author(s):  
F. Basile ◽  
P. Chiacchio ◽  
J. Coppola
Keyword(s):  
Petri Net ◽  
Active Identification

scholarly journals Organizational and technological solutions justifying use of non-destructive methods of control when building monolithic constructions of civil buildings and structures

2018 ◽  
Vol 251 ◽  
pp. 05014 ◽  
Author(s):  
Azariy Lapidus ◽  
Alan Khubaev ◽  
Tembot Bidov
Keyword(s):  
Control Method ◽  
Assessment Method ◽  
Expert Assessment ◽  
Mathematical Apparatus ◽  
Industrial Buildings ◽  
Object Parameters ◽  
Non Destructive ◽  
Destructive Methods ◽  
Methods Of Control

The parameters influencing on the use of non-destructive methods of control are considered when building monolithic constructions of civil and industrial buildings and structures. The analysis of the factor influence on the capacity of the method of the non-destructive control with the expert assessment method is made. Based on the qualimetric analysis three the most significant groups of the factors which can influence on the capacity of the use of the non-destructive control method (Pnc) are determined. The mathematical apparatus base is prepared, which characterize the object parameters.

Abnormal Motion Detection for Intelligent Video Surveillance

2011 ◽  
Vol 58-60 ◽  
pp. 2290-2295 ◽  
Author(s):  
Ruo Hong Huan ◽  
Xiao Mei Tang ◽  
Zhe Hu Wang ◽  
Qing Zhang Chen
Keyword(s):  
Kalman Filter ◽  
Object Tracking ◽  
Video Surveillance ◽  
Motion Detection ◽  
Background Subtraction ◽  
Moving Objects ◽  
Video Streams ◽  
Intelligent Video Surveillance ◽  
Tracking Process ◽  
Object Parameters

A method of abnormal motion detection for intelligent video surveillance is presented, which includes object intrusion detection, object overlong stay detection and object overpopulation detection. Background subtraction algorithm is used to detect moving objects in video streams. Kalman filter is applied for object tracking. By the construction of relation matrix, the tracking process is divided into five statuses for prediction and estimation, which are object disappearing, object separating, new object appearing, object sheltering and object matching. The object parameters and predictive information in the next frame which is used to track moving objects is established by Kalman filter. Then, three types of abnormal motion detection are implemented. The relative position of alarm area or guard line with the rectangle boxes of the moving objects is used to detect whether the object is invading. The existing time of the moving objects in monitor area is counted to detect whether the object is staying too long. Moving objects in the monitor area are classified and counted to detect whether the objects are too much. Alarm will be triggered when abnormal motion detection as defined is detected in the monitor area.

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