Wyniki 1-4 spośród 4 dla zapytania: authorDesc:"Konrad KANIA"

Image reconstruction in ultrasound transmission tomography using the Fermat’s Principle DOI:10.15199/48.2020.01.41

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The construction of a physical model of an ultrasonic tomograph is highly problematic due to the complexity of the acoustic phenomena necessary for modeling in the case of a heterogeneous environment of propagation of acoustic waves in small limited spaces [1]. The radial propagation model commonly used in transmission tomography turns out to be sufficient for effective detection of disturbances in the interior of objects and is used in commercial solutions, for example for non-invasive examination of the state of trees. The lack of the correct physical model does not allow us to fully understand phenomena occurring during imaging with the help of acoustic waves. Problems such as [2-14] are used to solve optimization problems. In tomography, methods [15-25] are used to solve the inverse problem. This work is a collection of numerical experiments that use the Fermat principle, originally used in optics, to better understand the process of acoustic wave propagation during tomographic measurements using ultrasound [26-40] to create a more precise solver for problems with ultrasound tomography. Algorithm Classical approach to modeling the ultrasonic tomographical system is to approximate the behavior of the system by the model of straight rays of propagation between two ultrasonic sensors. There are many works confirming the effectiveness of such a solutions in the terms of reliable ability of imaging positions of inclusions along the domain of tomographical system. The effectiveness of that types of models can be also confirmed by practical analysis of a measurement data from tomographical device. As the example Figure 2 shows the sensitivity visualization of the tomographical system. Presented visualization is made for one pair of sensor and is created on the basis of real measurement data with one air inclusion with water background. One can see that higher sensitivity is concentrated approximately along the line between [...]

Object detection using radio imaging tomography and tomographic sensors DOI:10.15199/48.2020.01.40

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The goal of the project and articles is to present a comprehensive device (device system) capable of measuring the strength of the received signal for the needs of a radio tomography and being able to act as a "Beacon" device. One of the main tasks of the system is the exchange of information between receivers and transmitters regarding the strength of the radio signal. After polling all devices, a measurement matrix will be created and the image reconstruction will be performed on its basis. The second main task of the system is to provide localization services using small radio transmitters called beacons [1-5]. There are many methods to solve optimization problems and being elements of a specific system [6-16]. In the tomography, deterministic methods and machine learning [17-36] are used to solve the inverse problem. The development of electronics and computing methods, the IoT and the fall in prices of hardware equipment, has created favorable conditions for the development and expansion of existing intelligent building systems. At present, the potential of available technologies is not fully exploited and is usually limited to the ability to control devices using a tablet or smartphone. Technologies related to the accumulation and processing of large amounts of data and computational intelligence are not commonly used in building intelligent systems. The increasing availability of all types of sensors, falling electronic component prices, the growing popularity of Internet technology, and the potential of large data volumes generated by the building's use process, is a developing area that will be heavily exploited in the coming years. The proposed system enables one to adjust the beacon position using data from several receivers using tomographic techniques. Real Time Locating Systems is one of the most dynamically developing branches of ICT. RLTS systems can be divided into systems operating in open spaces and wo[...]

Analysis of geospatial areas using electrical resistance tomography DOI:10.15199/48.2020.02.08

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All reconstruction methods (TV regularization and Gauss-Newton method) indicate that there is an area with very low specific conductivity just below the earth's surface. The best results (the smallest percentage error and the largest correlation coefficient) were obtained by the Gauss- Newton method with Laplace regularization [1]. The conductivity distribution on the tested surface is continuous. The choice of a regularization parameter has a very strong impact on the convergence of the objective function optimization algorithm [2-18]. Electrical resistivity tomography (ERT) is an imaging technique that uses various electrical properties of the environment. In this method, the power source is connected to the object, and then voltage drops at its edge are measured. Based on the collected measurements, the image inside the object is reconstructed. To this end, forward and inverse problems are solved. To solve a forward problem, the finite element method is most often used. Electric tomography has a relatively low image resolution. Difficulties in obtaining high resolution result mainly from a limited number of measurements, non-linear current flow through the given medium and too low sensitivity of measured voltages depending on changes in conductivity inside the area. Electrical resistance tomography is often used interchangeably with the EIT, especially in environmental and process solutions. ERT is a technique that gives the best results in detailed imaging of soil geological properties. The electrical properties of the soil depend to a large extent on such hydrological properties of rocks and soils as the formation of porosity and water saturation. In addition, this technique is sensitive to temporary temperature changes caused by the introduced steam, air flows, temperature changes or the movement of liquid contaminants. The soil environment in which pipelines and other steel structures are laid has a fundamental imp[...]

Analysis of geospatial areas using electrical resistance tomography DOI:10.15199/48.2020.02.08

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All reconstruction methods (TV regularization and Gauss-Newton method) indicate that there is an area with very low specific conductivity just below the earth's surface. The best results (the smallest percentage error and the largest correlation coefficient) were obtained by the Gauss- Newton method with Laplace regularization [1]. The conductivity distribution on the tested surface is continuous. The choice of a regularization parameter has a very strong impact on the convergence of the objective function optimization algorithm [2-18]. Electrical resistivity tomography (ERT) is an imaging technique that uses various electrical properties of the environment. In this method, the power source is connected to the object, and then voltage drops at its edge are measured. Based on the collected measurements, the image inside the object is reconstructed. To this end, forward and inverse problems are solved. To solve a forward problem, the finite element method is most often used. Electric tomography has a relatively low image resolution. Difficulties in obtaining high resolution result mainly from a limited number of measurements, non-linear current flow through the given medium and too low sensitivity of measured voltages depending on changes in conductivity inside the area. Electrical resistance tomography is often used interchangeably with the EIT, especially in environmental and process solutions. ERT is a technique that gives the best results in detailed imaging of soil geological properties. The electrical properties of the soil depend to a large extent on such hydrological properties of rocks and soils as the formation of porosity and water saturation. In addition, this technique is sensitive to temporary temperature changes caused by the introduced steam, air flows, temperature changes or the movement of liquid contaminants. The soil environment in which pipelines and other steel structures are laid has a fundamental imp[...]

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