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diagnosis
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A new fault detection method for modular multilevel converter semiconductor power switches
, Article 41st Annual Conference of the IEEE Industrial Electronics Society, 9 November 2015 through 12 November 2015 ; 2015 , Pages 50-55 ; 9781479917624 (ISBN) ; Shahbazi, M ; Zolghadri, M. R ; IEEE Industrial Electonics Society (IES) ; Sharif University of Technology
Institute of Electrical and Electronics Engineers Inc
Abstract
This paper proposes a new fault detection method for the modular multilevel converter (MMC) semiconductor power switches. While in common MMCs, the modules capacitor voltages are measured directly for control purposes, in this paper voltage measurement point changes to module output terminal improving fault diagnosis ability. Based on this measurement reconfiguration, a novel fault detection algorithm is designed for MMCs semiconductor power switches. The open circuit and short circuit faultsare detected based on unconformity between modules output voltage and switching signals. Simulations results confirm accurate and fast operation of the proposed algorithm in faulty module diagnosis....
Differentiation of inflammatory papulosquamous skin diseases based on skin biophysical and ultrasonographic properties: A decision tree model
, Article Indian Journal of Dermatology, Venereology and Leprology ; Volume 86, Issue 6 , 2020 , Pages 752- ; Yazdani, K ; Ahmad Nasrollahi, S ; Nazari, M ; Darooei, R ; Firooz, A ; Sharif University of Technology
Wolters Kluwer Medknow Publications
2020
Abstract
The biophysical and ultrasonographic properties of the skin change in papulosquamous diseases. Aims: To identify biophysical and ultrasonographic properties for the differentiation of five main groups of papulosquamous skin diseases. Methods: Fifteen biophysical and ultrasonographic parameters were measured by multiprobe adapter system and high-frequency ultrasonography in active lesions and normal control skin in patients with chronic eczema, psoriasis, lichen planus, pityriasis rosea and parapsoriasis/mycosis fungoides. Using histological diagnosis as a gold standard, a decision tree analysis was performed based on the mean percentage changes of these parameters [(lesion-control/control)...
Detection of single and dual incipient process faults using an improved artificial neural network
, Article Iranian Journal of Chemistry and Chemical Engineering ; Volume 24, Issue 3 , 2005 , Pages 59-66 ; 10219986 (ISSN) ; Shahrokhi, M ; Sharif University of Technology
2005
Abstract
Changes in the physicochemical conditions of process unit, even under control, may lead to what are generically referred to as faults. The cognition of causes is very important, because the system can be diagnosed and fault tolerated. In this article, we discuss and propose an artificial neural network that can detect the incipient and gradual faults either individually or mutually. The main feature of the proposed network is including the fault patterns in the input space. The scheme is examined through a sample unit with five probable occurring faults. The simulation results indicate that the proposed algorithm can detect both single and two simultaneous faults properly
An Approach for Cancer Diagnosis Based on Graph Modeling
, M.Sc. Thesis Sharif University of Technology ; Habibi, Jafar (Supervisor)
Abstract
Digital image analysis of histological datasets is a currently expanding field of research. Histological images are inherently complex in nature and contain a wide variety of visual information. Graph-based methods have recently gained immense popularity, as these methods can effectively describe tissue architecture and provide adequate numeric information for subsequent computer-based analysis. Graphs have the ability to represent spatial arrangements and neighborhood relationships of different tissue components, which are essential characteristics observed visually by pathologists during the investigation of specimens. In this thesis, we proposed an automatic approach for classification...
The Differential Diagnosis of Crohn's Disease and Celiac Disease Using Nuclear Magnetic Resonance Spectroscopy
, Article Applied Magnetic Resonance ; Volume 45, Issue 5 , May , 2014 , Pages 451-459 ; Kasmaee, L. M ; Sohrabzadeh, K ; Nejad, M. R ; Tafazzoli, M ; Oskouie, A. A ; Sharif University of Technology
Abstract
Crohn's disease and celiac disease belong to a group of autoimmune conditions that affect the digestive system, specifically the small intestine. They both attack the digestive tract and share many symptoms. Thus, the discovery of proper methods would be a major step toward differentiating celiac disease from Crohn's disease. The aim of this study was to search for the metabolic biomarkers to differentiate between these two diseases. Proton nuclear magnetic resonance spectroscopy (1H NMR) was employed as the metabolic profiling method to look for serum metabolites that differentiate between celiac disease and Crohn's disease. Classification of celiac disease and Crohn's disease was done...
An efficient fractal method for detection and diagnosis of breast masses in mammograms
, Article Journal of Digital Imaging ; Vol. 27, issue. 5 , 2014 , pp. 661-669 ; ISSN: 08971889 ; AhmadiNoubari, H ; Fatemizadeh, E ; Khalili, M ; Sharif University of Technology
Abstract
In this paper, we present an efficient fractal method for detection and diagnosis of mass lesion in mammogram which is one of the abnormalities in mammographic images. We used 110 images that were carefully selected by a radiologist, and their abnormalities were also confirmed by biopsy. These images included circumscribed benign, ill-defined, and spiculated malignant masses. Firstly, we discriminated lesions automatically using new fractal dimensions. The results which were examined by different types of breast density showed that the proposed method was able to yield quite satisfactory detection results. Secondly, noting that contours of masses playing the most important role in diagnosis...
Novel margin features for mammographic mass classification
, Article Proceedings - 2012 11th International Conference on Machine Learning and Applications, ICMLA 2012 ; Volume 2 , 2012 , Pages 139-144 ; 9780769549132 (ISBN) ; Zarghami, A ; Manzuri Shalmani, M. T ; Sharif University of Technology
2012
Abstract
Computer-Aided Diagnosis (CAD) systems are widely used for detection of various kinds of abnormalities in mammography images. Masses are one type of these abnormalities which are mostly characterized by their margin and shape. For classification of masses proper features are needed to be extracted. However, the number of well-known features for describing margin is much fewer than geometrical, shape, and textural ones. In addition, most of the existing margin features are highly dependent on segmentation accuracy. In this work, new features for describing margin of masses are presented which can handle inaccuracies in segmentation. These features are obtained from a set of waveforms by...
A Wavelet-packet-based approach for breast cancer classification
, Article Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS ; 2011 , Pages 5100-5103 ; 1557170X (ISSN) ; 9781424441211 (ISBN) ; Razavian, S. M. J ; Vaziri, R ; Vosoughi Vahdat, B ; Sharif University of Technology
Abstract
In this paper, a new approach for non-invasive diagnosis of breast diseases is tested on the region of the breast without undue influence from the background and medically unnecessary parts of the images. We applied Wavelet packet analysis on the two-dimensional histogram matrices of a large number of breast images to generate the filter banks, namely sub-images. Each of 1250 resulting sub-images are used for computation of 32 two-dimensional histogram matrices. Then informative statistical features (e.g. skewness and kurtosis) are extracted from each matrix. The independent features, using 5-fold cross-validation protocol, are considered as the input sets of supervised classification. We...
Failure detection and isolation in robotic manipulators using joint torque sensors
, Article Robotica ; Volume 28, Issue 4 , 2010 , Pages 549-561 ; 02635747 (ISSN) ; Aghili, F ; Sharif University of Technology
2010
Abstract
Reliability of any model-based failure detection and isolation (FDI) method depends on the amount of uncertainty in a system model. Recently, it has been shown that the use of joint torque sensing results in a simplified manipulator model that excludes hardly identifiable link dynamics and other nonlinearities such as friction, backlash, and flexibilities. In this paper, we show that the application of the simplified model in a fault detection algorithm increases reliability of fault monitoring system against modeling uncertainty. The proposed FDI filter is based on a smooth velocity observer of degree 2n where n stands for the number of manipulator joints. No velocity measurement and...
Coronary artery disease detection using computational intelligence methods
, Article Knowledge-Based Systems ; Volume 109 , 2016 , Pages 187-197 ; 09507051 (ISSN) ; Zangooei, M. H ; Hosseini, M. J ; Habibi, J ; Khosravi, A ; Roshanzamir, M ; Khozeimeh, F ; Sarrafzadegan, N ; Nahavandi, S ; Sharif University of Technology
Elsevier B.V
Abstract
Nowadays, cardiovascular diseases are very common and are one of the main causes of death worldwide. One major type of such diseases is the coronary artery disease (CAD). The best and most accurate method for the diagnosis of CAD is angiography, which has significant complications and costs. Researchers are, therefore, seeking novel modalities for CAD diagnosis via data mining methods. To that end, several algorithms and datasets have been developed. However, a few studies have considered the stenosis of each major coronary artery separately. We attempted to achieve a high rate of accuracy in the diagnosis of the stenosis of each major coronary artery. Analytical methods were used to...
Fetal R-wave detection from multichannel abdominal ECG recordings in low SNR
, Article Proceedings of the 31st Annual International Conference of the IEEE Engineering in Medicine and Biology Society: Engineering the Future of Biomedicine, EMBC 2009 ; 2009 , Pages 344-347 ; 1557170X (ISSN) ; Shamsollahi, M. B ; Sameni, R ; Sharif University of Technology
Abstract
Abdominal recordings of fetal ECG (fECG) have lower signal-to-noise ratio (SNR) as compared with invasive procedures. In this paper we have combined two previously proposed methods, one for extracting fECG, called piCA and the other, a transformation based on Hilbert transform to enhance the R-peaks. The combination of these methods seems to work well in situations of noisy data and fetal repositioning. Also a comparison is done by using ICA in order to extract the fetal signals. Performance of both methods is studied separately. Results show that applying the transformation on the components extracted with the use of piCA (after maternal ECG cancellation), had a very good performance. Also,...
Stress analysis of internal carotid artery with low stenosis level: the effect of material model and plaque geometry
, Article Journal of Mechanics in Medicine and Biology ; Volume 17, Issue 6 , 2017 ; 02195194 (ISSN) ; Ghorbannia Hassankiadeh, A ; Sharif University of Technology
Abstract
Stress concentration in carotid stenosis has been proven to assist plaque morphology in disease diagnosis and vulnerability. This work focuses on numerical analysis of stress and strain distribution in the cross-section of internal carotid artery using a 2D structure-only method. The influence of four different idealized plaque geometries (circle, ellipse, oval and wedge) is investigated. Numerical simulations are implemented utilizing linear elastic model along with four hyperelastic constitutive laws named neo-Hookean, Ogden, Yeoh and Mooney-Rivlin. Each case is compared to the real geometry. Results show significant strength of oval and wedged geometries in predicting stress and strain...
Novel aspects of application of cadmium telluride quantum dots nanostructures in radiation oncology
, Article Applied Physics A: Materials Science and Processing ; Volume 123, Issue 8 , 2017 ; 09478396 (ISSN) ; Zare, H ; Karimi, S ; Rahighi, R ; Feizi, S ; Sharif University of Technology
Springer Verlag
2017
Abstract
In the last two decades, quantum dots nanomaterials have garnered a great deal of scientific interest because of their unique properties. Quantum dots (QDs) are inorganic fluorescent nanocrystals in the size range between 1 and 20 nm. Due to their structural properties, they possess distinctive properties and behave in different way from crystals in macro scale, in many branches of human life. Cadmium telluride quantum dots (CdTe QDs) were labeled with 68Ga radio nuclide for fast in vivo targeting and coincidence imaging of tumors. Using instant paper chromatography, the physicochemical properties of the Cadmium telluride quantum dots labeled with 68Ga NPs (68Ga@ CdTe QDs) were found high...
COVID-19 diagnosis using capsule network and fuzzy c -means and mayfly optimization algorithm
, Article BioMed Research International ; Volume 2021 , 2021 ; 23146133 (ISSN) ; Salekshahrezaee, Z ; Mohammadi Tofigh, A ; Ghanavati, R ; Arandian, B ; Chapnevis, A ; Sharif University of Technology
Hindawi Limited
2021
Abstract
The COVID-19 epidemic is spreading day by day. Early diagnosis of this disease is essential to provide effective preventive and therapeutic measures. This process can be used by a computer-aided methodology to improve accuracy. In this study, a new and optimal method has been utilized for the diagnosis of COVID-19. Here, a method based on fuzzy C-ordered means (FCOM) along with an improved version of the enhanced capsule network (ECN) has been proposed for this purpose. The proposed ECN method is improved based on mayfly optimization (MFO) algorithm. The suggested technique is then implemented on the chest X-ray COVID-19 images from publicly available datasets. Simulation results are...
Design of a hybrid inertial and magnetophoretic microfluidic device for ctcs separation from blood
, Article Micromachines ; Volume 12, Issue 8 , 2021 ; 2072666X (ISSN) ; Shamloo, A ; Akbari, J ; Sharif University of Technology
MDPI AG
2021
Abstract
Circulating tumor cells (CTCs) isolation from a blood sample plays an important role in cancer diagnosis and treatment. Microfluidics offers a great potential for cancer cell separation from the blood. Among the microfluidic-based methods for CTC separation, the inertial method as a passive method and magnetic method as an active method are two efficient well-established methods. Here, we investigated the combination of these two methods to separate CTCs from a blood sample in a single chip. Firstly, numerical simulations were performed to analyze the fluid flow within the proposed channel, and the particle trajectories within the inertial cell separation unit were investigated to...
Analyzing Genetic Data With Data Mining Techniques
, M.Sc. Thesis Sharif University of Technology ; Abolhassani, Hassan (Supervisor)
Abstract
Gene expression using microarrays technology has special importance in biology studies especially in cancer researches. Using this technology we can assess expression level of several thousand genes simultaneously. One of the major applications of this technology is diseases’ diagnosis which cancers are the most important types of them. The problem in classifying microarray data is its high dimension; although number of samples hardly exceeds a hundred. This severe asymmetry and high dimensionality, results in reduction of accuracy, speed, stability and generalization of classification methods. Thus, one of the most important issues in cancer diagnosis is selection of related and useful...
Development of a Framework to Control and Model Based Fault Diagnosis of a Gas Transmission Network
, M.Sc. Thesis Sharif University of Technology ; Bozorgmehry, Ramin (Supervisor)
Abstract
In this project a framework for Model Based Fault Diagnosis (MBFD) in a Gas Transmission Network (GTN) was developed. A black-box linear state-space model was used to capture dynamic behavior of an industrial benchmark for GTN. A full fledge commercial network simulator were used to obtain the required data for process identification. In order to check the robustness of the model zero mean white noise was imposed on various output obtained by the commercial simulator. Kalman filter was used to estimate the states of the GTN. These estimated states along with the measured output (all obtained from the commercial simulator) are almost similar to their corresponding estimated signal. This shows...
Condition Monitoring and Fault Diagnosis of Rolling Element Bearing in Phase Space
, M.Sc. Thesis Sharif University of Technology ; Behzad, Mehdi (Supervisor)
Abstract
The failure in rolling element bearings as an important part of rotary machine can lead to machine breakdown.Consequently, bearings can reduce reliability of these components and therefore a maintenance strategy is essential to keep reliability in a desired level. The first and primitive strategy is called breakdown or unplanned maintenance. The next is preventive or planned maintenance. In this scheme, maintenance is done after a specified time period irrespective of machine health status. Out of place maintenance is the disadvantage of preventive maintenance. The most effective generation of maintenance strategy is condition based maintenance (CBM) which suggests maintenance decision based...
Synthesis of Graphene Quantum Dots for Biomedical Application
, M.Sc. Thesis Sharif University of Technology ; Sadrnezhaad, KHatiboleslam (Supervisor) ; Ahhadiaan, Mohammad Mehdi (Co-Advisor)
Abstract
Graphene quantum dots (GQDs) as a sort of carbon-based nanomaterials are applied in a multitude of exciting areas. They are effective fluorescent probe for many potential biological and medical applications. In comparison to conventional organic fluorescent probes (organic dyes), GQDs have substantial advantages, such as photostability, excellent solubility, low cytotoxicity and biocompatibility.
In this thesis, green fluorescent GQDs have been prepared via solvothermal method from graphite powder.Various analysis methods were utilized to characterization of the product. So, several experiments on GQDs in solution and in solid substrate at room temperature have been performed. The...
In this thesis, green fluorescent GQDs have been prepared via solvothermal method from graphite powder.Various analysis methods were utilized to characterization of the product. So, several experiments on GQDs in solution and in solid substrate at room temperature have been performed. The...
Fin failure diagnosis for non-linear supersonic air vehicle based on inertial sensors
, Article Advances in Aircraft and Spacecraft Science ; Volume 7, Issue 1 , 2020 , Pages 1-17 ; Fathi Jegarkandi, M ; Sharif University of Technology
Techno Press
2020
Abstract
In this paper, a new model-based Fault Detection and Diagnosis (FDD) method for an agile supersonic flight vehicle is presented. A nonlinear model, controlled by a classical closed loop controller and proportional navigation guidance in interception scenario, describes the behavior of the vehicle. The proposed FDD method employs the Inertial Navigation System (INS) data and nonlinear dynamic model of the vehicle to inform fins damage to the controller before leading to an undesired performance or mission failure. Broken, burnt, unactuated or not opened control surfaces cause a drastic change in aerodynamic coefficients and consequently in the dynamic model. Therefore, in addition to the...