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514 results on '"gaussian kernel"'

502. Depth dependence of the single chamber response function of the I'mRT MatriXX array in a 6 MV photon beam.

Author

Alashrah S, Kandaiya S, Lum LS, and Cheng SK

Subjects
Equipment Design, Equipment Failure Analysis, Photons, Radiation Dosage, Reproducibility of Results, Sensitivity and Specificity, Radiometry instrumentation, Radiotherapy, Conformal instrumentation, Transducers
Abstract

One of the factors which influence the spatial resolution of a 2D detector array is the size of the single detector, another the transport of the secondary electrons from the walls into the measuring volume. In this study, the single ion chamber dose response function of an I'mRT MatriXX array was determined by comparison between slit beam dose profiles measured with the array and with EBT2 radiochromic film in a solid water-equivalent phantom at a shallow depth of 0.5cm and at a depth of 5cm beyond the depth dose maximum for a 6 MV photon beam. The dose response functions were obtained using two methods, the best fit method and the deconvolution method. At the shallow depth, a Lorentz function and at 5cm depth a Gaussian function, both with the same FWHM of 7.4mm within limits of uncertainty, were identified as the best suited dose response functions of the 4.5mm diameter single array chamber. These dose response functions were then tested on various dose profiles whose true shape had been determined with EBT2 film and with the IC03 ionization chamber. By convolving these with the Lorentz kernel (at shallow depth) and the Gaussian kernel (at 5cm depth) the signal profiles measured with the I'mRT MatriXX array were closely approximated. Thus, the convolution of TPS-calculated dose profiles with these dose response functions can minimize the differences between calculation and measurement which occur due to the limited spatial resolution of the I'mRT MatriXX detector., (Copyright © 2013. Published by Elsevier GmbH.)

Published
2013
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503. Introducing kernel based morphology as an enhancement method for mass classification on mammography.

Author

Amirzadi A and Azmi R

Abstract

Since mammography images are in low-contrast, applying enhancement techniques as a pre-processing step are wisely recommended in the classification of the abnormal lesions into benign or malignant. A new kind of structural enhancement is proposed by morphological operator, which introduces an optimal Gaussian Kernel primitive, the kernel parameters are optimized the use of Genetic Algorithm. We also take the advantages of optical density (OD) images to promote the diagnosis rate. The proposed enhancement method is applied on both the gray level (GL) images and their OD values respectively, as a result morphological patterns get bolder on GL images; then, local binary patterns are extracted from this kind of images. Applying the enhancement method on OD images causes more differences between the values therefore a threshold method is applied toremove some background pixels. Those pixels that are more eligible to be mass are remained, and some statistical texture features are extracted from their equivalent GL images. Support vector machine is used for both approaches and the final decision is made by combining these two classifiers. The classification performance rate is evaluated by Az, under the receiver operating characteristic curve. The designed method yields Az = 0.9231, which demonstrates good results.

Published
2013

504. Iterative local Gaussian clustering for expressed genes identification linked to malignancy of human colorectal carcinoma.

Author

Wasito I, Hashim SZ, and Sukmaningrum S

Abstract

Gene expression profiling plays an important role in the identification of biological and clinical properties of human solid tumors such as colorectal carcinoma. Profiling is required to reveal underlying molecular features for diagnostic and therapeutic purposes. A non-parametric density-estimation-based approach called iterative local Gaussian clustering (ILGC), was used to identify clusters of expressed genes. We used experimental data from a previous study by Muro and others consisting of 1,536 genes in 100 colorectal cancer and 11 normal tissues. In this dataset, the ILGC finds three clusters, two large and one small gene clusters, similar to their results which used Gaussian mixture clustering. The correlation of each cluster of genes and clinical properties of malignancy of human colorectal cancer was analysed for the existence of tumor or normal, the existence of distant metastasis and the existence of lymph node metastasis.

Published
2007
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505. Zpracování data z teplotních měření pro účely inverzní úlohy vedení tepla

Author

Luks, Tomáš, Komínek, Jan, Brachna, Róbert, Luks, Tomáš, Komínek, Jan, and Brachna, Róbert

Abstract

Táto bakalárska práca sa zaoberá digitálnymi filtrami a odstraňovaním šumu z teplotných meraní. Základným aparátom k správnemu pochopeniu vlastností filtrov je diskrétna Fourierova transformácia, ktorá je v práci objasnená na ilustračnom príklade. Ďalej sa práca venuje popisu lineárnych filtrov a návrhu základných typov vhodných k redukcií šumu. Analýzou dát z experimentu je navrhnutý adaptívny filter. Tento filter sa podrobí ďalšej analýze pomocou simulovaného procesu chladenia s umelým šumom a porovná sa s ostatnými konvenčnými filtrami. Jedným zrovnávacím kritériom je porovnanie tvaru krivky záznamu teploty so simulovanou. Druhým kritériom je rekonštruovaná okrajová podmienka, ktorá je výstupom inverznej úlohy vedenia tepla., This bachelor's thesis deals with digital filters and noise removal from temperature measurements. The basic concept for the proper understanding of properties of filters is the discrete Fourier transform, which is illustrated on a given example. Next, the thesis considers linear filters and the design of basic types for noise reduction. An adaptive filter is designed by analyzing experimental data. This filter is subjected to further analysis using a simulated cooling process disrupted with artificially added noise and will be compared to other conventional filters. One criterion is to compare the curve of the filtered temperature to the simulated one. The second criterion is the reconstructed boundary condition, which is the output of the inverse heat conduction task.

506. Zpracování data z teplotních měření pro účely inverzní úlohy vedení tepla

Author

Luks, Tomáš, Komínek, Jan, Brachna, Róbert, Luks, Tomáš, Komínek, Jan, and Brachna, Róbert

Abstract

Táto bakalárska práca sa zaoberá digitálnymi filtrami a odstraňovaním šumu z teplotných meraní. Základným aparátom k správnemu pochopeniu vlastností filtrov je diskrétna Fourierova transformácia, ktorá je v práci objasnená na ilustračnom príklade. Ďalej sa práca venuje popisu lineárnych filtrov a návrhu základných typov vhodných k redukcií šumu. Analýzou dát z experimentu je navrhnutý adaptívny filter. Tento filter sa podrobí ďalšej analýze pomocou simulovaného procesu chladenia s umelým šumom a porovná sa s ostatnými konvenčnými filtrami. Jedným zrovnávacím kritériom je porovnanie tvaru krivky záznamu teploty so simulovanou. Druhým kritériom je rekonštruovaná okrajová podmienka, ktorá je výstupom inverznej úlohy vedenia tepla., This bachelor's thesis deals with digital filters and noise removal from temperature measurements. The basic concept for the proper understanding of properties of filters is the discrete Fourier transform, which is illustrated on a given example. Next, the thesis considers linear filters and the design of basic types for noise reduction. An adaptive filter is designed by analyzing experimental data. This filter is subjected to further analysis using a simulated cooling process disrupted with artificially added noise and will be compared to other conventional filters. One criterion is to compare the curve of the filtered temperature to the simulated one. The second criterion is the reconstructed boundary condition, which is the output of the inverse heat conduction task.

507. Zpracování data z teplotních měření pro účely inverzní úlohy vedení tepla

Author

Luks, Tomáš, Komínek, Jan, Luks, Tomáš, and Komínek, Jan

Abstract

Táto bakalárska práca sa zaoberá digitálnymi filtrami a odstraňovaním šumu z teplotných meraní. Základným aparátom k správnemu pochopeniu vlastností filtrov je diskrétna Fourierova transformácia, ktorá je v práci objasnená na ilustračnom príklade. Ďalej sa práca venuje popisu lineárnych filtrov a návrhu základných typov vhodných k redukcií šumu. Analýzou dát z experimentu je navrhnutý adaptívny filter. Tento filter sa podrobí ďalšej analýze pomocou simulovaného procesu chladenia s umelým šumom a porovná sa s ostatnými konvenčnými filtrami. Jedným zrovnávacím kritériom je porovnanie tvaru krivky záznamu teploty so simulovanou. Druhým kritériom je rekonštruovaná okrajová podmienka, ktorá je výstupom inverznej úlohy vedenia tepla., This bachelor's thesis deals with digital filters and noise removal from temperature measurements. The basic concept for the proper understanding of properties of filters is the discrete Fourier transform, which is illustrated on a given example. Next, the thesis considers linear filters and the design of basic types for noise reduction. An adaptive filter is designed by analyzing experimental data. This filter is subjected to further analysis using a simulated cooling process disrupted with artificially added noise and will be compared to other conventional filters. One criterion is to compare the curve of the filtered temperature to the simulated one. The second criterion is the reconstructed boundary condition, which is the output of the inverse heat conduction task.

508. Zpracování data z teplotních měření pro účely inverzní úlohy vedení tepla

Author

Luks, Tomáš, Komínek, Jan, Luks, Tomáš, and Komínek, Jan

Abstract

Táto bakalárska práca sa zaoberá digitálnymi filtrami a odstraňovaním šumu z teplotných meraní. Základným aparátom k správnemu pochopeniu vlastností filtrov je diskrétna Fourierova transformácia, ktorá je v práci objasnená na ilustračnom príklade. Ďalej sa práca venuje popisu lineárnych filtrov a návrhu základných typov vhodných k redukcií šumu. Analýzou dát z experimentu je navrhnutý adaptívny filter. Tento filter sa podrobí ďalšej analýze pomocou simulovaného procesu chladenia s umelým šumom a porovná sa s ostatnými konvenčnými filtrami. Jedným zrovnávacím kritériom je porovnanie tvaru krivky záznamu teploty so simulovanou. Druhým kritériom je rekonštruovaná okrajová podmienka, ktorá je výstupom inverznej úlohy vedenia tepla., This bachelor's thesis deals with digital filters and noise removal from temperature measurements. The basic concept for the proper understanding of properties of filters is the discrete Fourier transform, which is illustrated on a given example. Next, the thesis considers linear filters and the design of basic types for noise reduction. An adaptive filter is designed by analyzing experimental data. This filter is subjected to further analysis using a simulated cooling process disrupted with artificially added noise and will be compared to other conventional filters. One criterion is to compare the curve of the filtered temperature to the simulated one. The second criterion is the reconstructed boundary condition, which is the output of the inverse heat conduction task.

509. Zpracování data z teplotních měření pro účely inverzní úlohy vedení tepla

Author

Luks, Tomáš, Komínek, Jan, Luks, Tomáš, and Komínek, Jan

Abstract

Táto bakalárska práca sa zaoberá digitálnymi filtrami a odstraňovaním šumu z teplotných meraní. Základným aparátom k správnemu pochopeniu vlastností filtrov je diskrétna Fourierova transformácia, ktorá je v práci objasnená na ilustračnom príklade. Ďalej sa práca venuje popisu lineárnych filtrov a návrhu základných typov vhodných k redukcií šumu. Analýzou dát z experimentu je navrhnutý adaptívny filter. Tento filter sa podrobí ďalšej analýze pomocou simulovaného procesu chladenia s umelým šumom a porovná sa s ostatnými konvenčnými filtrami. Jedným zrovnávacím kritériom je porovnanie tvaru krivky záznamu teploty so simulovanou. Druhým kritériom je rekonštruovaná okrajová podmienka, ktorá je výstupom inverznej úlohy vedenia tepla., This bachelor's thesis deals with digital filters and noise removal from temperature measurements. The basic concept for the proper understanding of properties of filters is the discrete Fourier transform, which is illustrated on a given example. Next, the thesis considers linear filters and the design of basic types for noise reduction. An adaptive filter is designed by analyzing experimental data. This filter is subjected to further analysis using a simulated cooling process disrupted with artificially added noise and will be compared to other conventional filters. One criterion is to compare the curve of the filtered temperature to the simulated one. The second criterion is the reconstructed boundary condition, which is the output of the inverse heat conduction task.

510. Zpracování data z teplotních měření pro účely inverzní úlohy vedení tepla

Author

Luks, Tomáš, Komínek, Jan, Brachna, Róbert, Luks, Tomáš, Komínek, Jan, and Brachna, Róbert

Abstract

Táto bakalárska práca sa zaoberá digitálnymi filtrami a odstraňovaním šumu z teplotných meraní. Základným aparátom k správnemu pochopeniu vlastností filtrov je diskrétna Fourierova transformácia, ktorá je v práci objasnená na ilustračnom príklade. Ďalej sa práca venuje popisu lineárnych filtrov a návrhu základných typov vhodných k redukcií šumu. Analýzou dát z experimentu je navrhnutý adaptívny filter. Tento filter sa podrobí ďalšej analýze pomocou simulovaného procesu chladenia s umelým šumom a porovná sa s ostatnými konvenčnými filtrami. Jedným zrovnávacím kritériom je porovnanie tvaru krivky záznamu teploty so simulovanou. Druhým kritériom je rekonštruovaná okrajová podmienka, ktorá je výstupom inverznej úlohy vedenia tepla., This bachelor's thesis deals with digital filters and noise removal from temperature measurements. The basic concept for the proper understanding of properties of filters is the discrete Fourier transform, which is illustrated on a given example. Next, the thesis considers linear filters and the design of basic types for noise reduction. An adaptive filter is designed by analyzing experimental data. This filter is subjected to further analysis using a simulated cooling process disrupted with artificially added noise and will be compared to other conventional filters. One criterion is to compare the curve of the filtered temperature to the simulated one. The second criterion is the reconstructed boundary condition, which is the output of the inverse heat conduction task.

511. Simulation-based Anomaly Detection and Damage Localization: An application to Structural Health Monitoring

Author

Caterina Bigoni and Jan S. Hesthaven

Subjects
Computer science, Computational Mechanics, gaussian kernel, General Physics and Astronomy, laplace transforms, digital twin, parameter selection, model-reduction, Parametric statistics, Model order reduction, support, structural health monitoring, business.industry, Mechanical Engineering, crack detection, Pattern recognition, anomaly detection, Computer Science Applications, one-class classification, Support vector machine, Proactive maintenance, classification, Mechanics of Materials, Outlier, network, Probability distribution, Anomaly detection, numerical inversion, Structural health monitoring, Artificial intelligence, business, reduced order modeling
Abstract

We propose a simulation-based decision strategy for the proactive maintenance of complex structures with a particular application to structural health monitoring (SHM). The strategy is based on a data-driven approach which exploits an offline–online decomposition. A synthetic dataset is constructed offline by solving a parametric time-dependent partial differential equation for multiple input parameters, sampled from their probability distributions of natural variation. The collected time-signals, extracted at sensor locations, are used to train classifiers at such sensor locations, thus constructing multiple databases of healthy configurations. These datasets are then used to train one class Support Vector Machines (OC-SVMs) to detect anomalies. During the online stage, a new measurement, possibly obtained from a damaged configuration, is evaluated using the classifiers. Information on damage is provided in a hierarchical manner: first, using a binary feedback, the entire structure response is either classified as inlier (healthy) or outlier (damaged). Then, for the outliers, we exploit the outputs of multiple classifiers to retrieve information both on the severity and the spatial location of the damages. Because of the large number of signals needed to construct the datasets offline, a model order reduction strategy is implemented to reduce the computational burden. We apply this strategy to both 2D and 3D problems to mimic the vibrational behavior of complex structures under the effect of an active source and show the effectiveness of the approach for detecting and localizing cracks.

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