1. Signal processor for optical fiber sensors based on MEMS Fabry-Perot interferometer : master's thesisNikola Uremović, 2020, magistrsko delo Opis: In the master thesis, we have created an interrogation system for measuring the change of the optical path in the Fabry-Perot interferometer caused by the strain of the surface at which it was attached to. The change of strain can be calculated via a change in optical path length which is visible as a shift in phase angle. The system will be used as a system for measuring strain, although it can be used for measuring various physical parameters that can cause a change in optical path length, such as pressure, force, temperature, etc. Initially, the theoretical background of the system and project components are represented and explained, following the building process of the electronic and optical part of the project. Lastly, the working principle and programming algorithms of a system are presented and explained. Measurement results are shown at the end, as well as the conclusion that is drawn from the thesis.
Ključne besede: optical fibers, sensors, interferometer, signal processing
Objavljeno v DKUM: 04.11.2020; Ogledov: 633; Prenosov: 75
 Celotno besedilo (5,11 MB) |
2. Application of fuzzy AHP approach to selection of organizational structure with consideration to contextual dimensionsAlireza Aslani, Feryal Aslani, 2012, izvirni znanstveni članek Opis: The literature of organizational structure design is relatively rich along with conceptual and complex patterns. This complexity arising from the number of elements and numerous relations in addition to the nature of variables. Thereby, the lack of operational decision-making models is felt to propose adequate structural designs in practice. In this article, the researchers employ a fuzzy multi attribute decision making model (FMADM) to select the most suitable organizational structure based on expert’s judgments and by deploying contextual dimensions of the organization. Since the organizational changes especially in the structural levels are along with resistances among involved staffs, the implementation of this model is a supportive tool in addition to help the managers to make a qualified decision and change.
Ključne besede: organizational structure designing, business process reengineering, development management, integration, fuzzy ahpimage analysis, probabilistic modeling, signal processing, license plate recognition
Objavljeno v DKUM: 28.11.2017; Ogledov: 1084; Prenosov: 333
Celotno besedilo (576,00 KB)
Gradivo ima več datotek! Več... |
3. An overview of image analysis algorithms for license plate recognitionKhalid Aboura, Rami Al-Hmouz, 2017, izvirni znanstveni članek Opis: Background and purpose: We explore the problem of License Plate Recognition (LPR) to highlight a number of algorithms that can be used in image analysis problems. In management support systems using image object recognition, the intelligence resides in the statistical algorithms that can be used in various LPR steps. We describe a number of solutions, from the initial thresholding step to localization and recognition of image elements. The objective of this paper is to present a number of probabilistic approaches in LPR steps, then combine these approaches together in one system. Most LPR approaches used deterministic models that are sensitive to many uncontrolled issues like illumination, distance of vehicles from camera, processing noise etc. The essence of our approaches resides in the statistical algorithms that can accurately localize and recognize license plate.
Design/Methodology/Approach: We introduce simple and inexpensive methods to solve relatively important problems, using probabilistic approaches. In these approaches, we describe a number of statistical solutions, from the initial thresholding step to localization and recognition of image elements. In the localization step, we use frequency plate signals from the images which we analyze through the Discrete Fourier Transform. Also, a probabilistic model is adopted in the recognition of plate characters. Finally, we show how to combine results from bilingual license plates like Saudi Arabia plates.
Results: The algorithms provide the effectiveness for an ever-prevalent form of vehicles, building and properties management. The result shows the advantage of using the probabilistic approached in all LPR steps. The averaged classification rates when using local dataset reached 79.13%.
Conclusion: An improvement of recognition rate can be achieved when there are two source of information especially of license plates that have two independent texts.
Ključne besede: image analysis, probabilistic modeling, signal processing, license plate recognition
Objavljeno v DKUM: 28.11.2017; Ogledov: 1014; Prenosov: 335
Celotno besedilo (1,01 MB)
Gradivo ima več datotek! Več... |
4. The different methods of displacement monitoring at loading tests of bridges or different structuresBoštjan Kovačič, Rok Kamnik, Andrii Bieliatynskyi, 2016, objavljeni znanstveni prispevek na konferenci Opis: By measuring the displacements and deformations at different structures we deal in the Faculty of Civil Engineering, transportation Engineering and Architecture in University of Maribor for about 20 years. At that time we measured over 600 structures. Most loading tests of bridges and Viaducts were made. The measurements of movements needed to be as precise and accurate as possible. To do that laboratory test of instruments were made to see which instrument gives us reliable results. Displacements can be determined by geodetic and physical methods, depends of the construction. The use of geodetic methods are still preferable. In the paper the measurements with the total station, the level and rotation level, photogrammetry and solutions on the field by physical methods with inductive transducers are presented. We need to measure displacements as quick as possible but efficiently because we can not repeat the measurements under the same conditions. Also the surveying on the bridge and in the lab with the comparison of methods is presented under the different hard terrain conditions - water beneath the construction, big height of the structure, unapproachability, large span structures.
Ključne besede: bridges, measurements, strain gauge, load test, deformation, strain, signal processing
Objavljeno v DKUM: 02.08.2017; Ogledov: 994; Prenosov: 310
Celotno besedilo (3,15 MB)
Gradivo ima več datotek! Več... |
5. Vertical displacements measuring methods during bridge load testsBoštjan Kovačič, Ante Marendić, Rok Kamnik, Mikhail Volkov, Vera Roy, 2016, objavljeni znanstveni prispevek na konferenci Opis: This article introduces the use of the GNSS method for the load testings of bridge structures. We know that there area lot of methods by which you can determine vertical displacement. However, as new bridge constructions are constructed over almost impossible and inaccessible gorges and valleys, the classic measurements method do not allow us to determine vertical displacement so reliably any more or they are very time-consuming. The GNSS method is well known but there are difficulties when determining the altitude component of this method, which is rather questionable. For this purpose, the methods were tested as practical examples in which some difficulties were encountered, so subsequently another test recording was performed of altitude changes using this method.
Ključne besede: bridges, measurements, strain gauge, load test, deformation, strain, signal processing
Objavljeno v DKUM: 29.08.2016; Ogledov: 1381; Prenosov: 419
Celotno besedilo (1,55 MB)
Gradivo ima več datotek! Več... |
6. Analysis of neuromuscular disorders using statistical and entropy metrics on surface EMGRok Istenič, Prodromos A. Kaplanis, Constantinos S. Pattichis, Damjan Zazula, 2008, izvirni znanstveni članek Opis: This paper introduces the surface electromyogram (EMG) classification system based on statistical and entropy metrics. The system is intended for diagnostic use and enables classification of examined subject as normal, myopathic or neuropathic, regarding to the acquired EMG signals. 39 subjects in total participated in the experiment, 19 normal, 11 myopathic and 9 neuropathic. Surface EMG was recorded using 4-channel surface electrodes on the biceps brachii muscle at isometric voluntary contractions. The recording time was only 5 seconds long to avoid muscle fatigue, and contractions at fiveforce levels were performed, i.e. 10, 30, 50, 70 and 100 % of maximal voluntary contraction. The feature extraction routine deployed the wavelet transform and calculation of the Shannon entropy across all the scales in order to obtain a feature set for each subject. Subjects were classified regarding the extracted features using three machine learning techniques, i.e. decision trees, support vector machines and ensembles of support vector machines. Four 2-class classifications and a 3-class classification were performed. The scored classification rates were the following: 64+-11% for normal/abnormal, 74+-7% for normal/myopathic, 79+-8% for normal/neuropathic, 49+-20% for myopathic/neuropathic, and 63+-8% for normal/myopathic/neuropathic.
Ključne besede: surface electromyography, neuromuscular disorders, neuropathy, myopathy, EMG signals, signal processing, wavelet transform, metrics
Objavljeno v DKUM: 31.05.2012; Ogledov: 1593; Prenosov: 40
 Povezava na celotno besedilo |
