Computer Science
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ISSN 1508-2806
e-ISSN: 2300-7036
Issue Date
2017
Volume
Vol. 18
Number
No. 4
Description
Reviewed by: Dennis Nunez Fernandez, Natalia Chechina, Ivan Gankevich, Andre Koelewijn, Valeria Krzhizhanovskaya, Natalia Melnikova, Ilya Mokhov, Alexander Pyayt, Jonathan Simm, Vlado Stankovski, Hubert Wójtowicz
Journal Volume
Computer Science
Vol. 18 (2017)
Projects
Pages
Articles
From Linear Classifier to Convolutional Neural Network for Hand Pose Recognition
(Wydawnictwa AGH, 2017) Rościszewski, Paweł
Recently gathered image datasets and new capabilities of high performance computing systems allowed developing new artificial neural network models and training algorithms. Using the new machine learning models, computer vision tasks can be accomplished based on the raw values of image pixels, instead of specific features. The principle of operation of deep artificial neural networks is more and more resembling of what we believe to be happening in the human visual cortex. In this paper we build up an understanding of convolutional neural networks through investigating supervised machine learning methods suchas K-Nearest Neighbors, linear classifiers and fully connected neural networks. We provide examples and accuracy results based on our implementation aimed for the problem of hand pose recognition.
Smart levee in Poland. Full-scale monitoring experimental study of levees by different methods
(Wydawnictwa AGH, 2017) Sekuła, Klaudia; Borecka, Aleksandra ; Kessler, Daniel; Majerski, Patryk
This paper presents two types of control and measurement networks used in the levee built as part of the ISMOP project. The first control and measurement network based on pore pressure and temperature sensors. Additionally, it contains the fiber-optic technology. The second network include design experimental sensors, constructed for the development of solutions that can be used in existing flood embankments.
Analysis of annual temperature distribution inside the experimental embankment
(Wydawnictwa AGH, 2017) Bukowska-Belniak, Barbara; Dwornik, Maciej; Leśniak, Andrzej
The aim of this paper is analysis of temperatures distribution inside experimental embankment from August 2015 to September 2016. Analysis was carried out in order to interpretation of the results of the flood experiments performed on the experimental embankment. The reference for year temperature changes in the embankment at various depths was obtained. A simplified model of temperature changes depending on the depth was made. The model parameters which can be used for modelling the temperatures in the embankment during the experiments were estimated.
Optimal selection of numerical models for flood embankment pore pressure and temperature data
(Wydawnictwa AGH, 2017) Chuchro, Monika; Dwornik, Maciej; Szostek, Kamil; Leśniak, Andrzej
The aim of the ISMOP project is to study processes in earthen flood embankments: water filtration, pore pressure changes, and temperature changes due to varying water levels in the riverbed. Developing a system for continuous monitoring of flood embankment stability is the main goal of this project. A full-size earthen flood embankment with built-in sensors was built in Czernichow and used to conduct experiments involving the simulation of different flood waves, with parameters mostly measured at time intervals of 15 minutes. Numerical modelling—in addition to providing information about phenomena occurring in the embankment due to external factors and changes in water level—could be used to assess the state of the embankment. Modelling was performed using Itasca Flac 2D 7.0 with an assumed grid cell size of 10x10 cm. The water level in the embankment simulated the water flow in the Wisła River and the temperature of the air and water. Data about the state of the flood embankment was exported every hour. Using numerical models and real experiment data, a model-driven module was used to perform comparisons. Analyses of each half-section of the flood embankment were carried out separately using similarity measures and an aggregate window. For the tests, the North-West (NW) half cross-section of the embankment was chosen, which contains pore pressure and temperature sensors UT6 to UT10. The water level in the embankment was raised to a height of 3m, the best numerical model was considered the one that best matched the actual data recorded by the sensors during the experiment. The experiment period was from 9pm on 29/08/2016 to 9am on 03/09/2016. Seventeen numerical models of the water level rising to 2, 3, and 4 meters were compared against real experimental data from the NW half cross-section. The first step was to verify the similarity between the incoming data from the sensors. If the correlation value exceeded 0.8, the data from the sensors was averaged. The experimental data was then compared against the numerical models using least absolute deviations L1-Norm. The L1-Norm varied from 26 to 32, depending on window length and the numerical model used.
Influence of initial water saturation in earthen levees on results of numerical modelling of infiltration processes
(Wydawnictwa AGH, 2017) Dwornik, Maciej; Franczyk, Anna; Leśniak, Andrzej; Krawiec, Krzysztof
Levees in Poland are mostly earthen constructions. The stability of earthen levees depends largely on factors such as the construction material, meteorological conditions and natural elements. The influence of initial water saturation of pore space on levee stability is analysed in this paper. Analysis was performed using numerical modelling and water pore pressure results were compared against data obtained from sensors located in a levee. The numerical modelling shows the moderate influence of initial water level on distribution of water pore pressure during high water level.