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    Design and Fabrication of Centrifugal Microfluidic System to Measure Blood Factors

    , M.Sc. Thesis Sharif University of Technology Mahmoudi Arjmand, Ehsan (Author) ; Saadatmand, Maryam (Supervisor) ; Eghbal, Manochehr (Supervisor) ; Bakhtiari, Mohammad Reza (Co-Advisor)
    Diabetes mellitus is a global endemic that is rapidly increasing prevalence in both developing and developed countries. Recently, the American Diabetes Association has recommended the hemoglobin A1c as a possible substitute to fasting blood glucose for diagnosis of diabetes because it is an indicator of long-term glycemic control. Also, centrifugal microfluidics systems have a good potential to be used in the point of care testing systems. In this study, two centrifugal microfluidic discs were designed and manufactured in order to separately measure the hemoglobin and hemoglobin A1c in the whole blood. In the first part of the study, the hemoglobin measurement disc consists of two chambers... 

    Design and Fabrication of a Centrifugal Microfluidic System to Cell Lysis

    , M.Sc. Thesis Sharif University of Technology Khorrami Jahromi, Arash (Author) ; Saadatmand, Maryam (Supervisor) ; Eghbal, Manouchehr (Supervisor) ; Parsa Yeganeh, Laleh (Co-Supervisor)
    Cell lysis, as the first procedure of cell pretreatment, is a process that breaks cell membranes open thereby facilitating access to intracellular substances, such as DNA, proteins, and other components for further analysis to diagnose and treat diseases at early stages. Currently, there are several methods for cell lysis at macroscales. However, the time-consuming and expensive procedures as well as the large scal of the system are the main disadvantages of the systems. Recently, microfluidic systems have attracted considerable attention due to advantages associated with automation, integration and miniaturization of biomedical test protocols. Centrifugal microfluidics (Lab-on-a-Disc) is a... 

    Design and Fabrication of a Centrifugal Microfluidic System to DNA Extraction

    , M.Sc. Thesis Sharif University of Technology Fathi Ganje Lou, Ali (Author) ; Farhadi, Fathollah (Supervisor) ; Saadatmand, Maryam (Supervisor) ; Parsa Yeganeh, Laleh (Co-Supervisor)
    Deoxyribonucleic acid (DNA) extraction, as one of the most important steps in modern molecular diagnostics, is the process by which DNA is separated from intracellular materials like proteins, membranes, and other materials contained in the cell. Microfluidic technology enables sophisticated, time-consuming and costly experiments with minimal use of raw materials, time and cost and acceptable accuracy. The predominant advantages of centrifugal microfluidic systems are utilizing centrifugal force to generate propulsion without the need for a pump, and eliminating the need for experts to run the system. Various fluidic operations such as valving, mixing, metering, heating, and sample... 

    Mammogram image retrieval via sparse representation

    , Article 2011 1st Middle East Conference on Biomedical Engineering, MECBME 2011, Sharjah, 21 February 2011 through 24 February 2011 ; 2011 , Pages 63-66 ; 9781424470006 (ISBN) Siyahjani, F ; Ghaffari, A ; Fatemizadeh, E ; Sharif University of Technology
    In recent years there has been a great effort to enhance the computer-aided diagnosis systems, since proven similar pathologies, in the past, plays an important role in diagnosis of the current cases, content based medical image retrieval has been emerged. In this work we have designed a decision making machine in which utilizes sparse representation technique to preserve semantic category relevance among the retrieved images and the query image, this machine comprises optimized wavelets (adapted using lifting scheme) to extract appropriate visual features in order to grasp visual content of the images, afterwards by using some classical methods, Raw data vectors become applicable for sparse... 

    Parallel nonlinear analysis of weighted brain's gray and white matter images for Alzheimer's dementia diagnosis

    , Article 2010 Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC'10, 31 August 2010 through 4 September 2010, Buenos Aires ; 2010 , Pages 5573-5576 ; 9781424441235 (ISBN) Razavian, S. M. J ; Torabi, M ; Kim, K ; Sharif University of Technology
    In this study, we are proposing a novel nonlinear classification approach to discriminate between Alzheimer's Disease (AD) and a control group using T1-weighted and T2- weighted Magnetic Resonance Images (MRI's) of brain. Since T1-weighted images and T2-weighted images have inherent physical differences, obviously each of them has its own particular medical data and hence, we extracted some specific features from each. Then the variations of the relevant eigenvalues of the extracted features were tracked to pick up the most informative ones. The final features were assigned to two parallel systems to be nonlinearly categorized. Considering the fact that AD defects the white and gray regions... 

    A Vacuum arc diagnosis method for the high voltage power supply of vacuum tubes

    , Article 2019 International Vacuum Electronics Conference, IVEC 2019, 28 April 2019 through 1 May 2019 ; 2019 ; 9781538675342 (ISBN) Ayoubi, R ; Rahmanian, M ; Kaboli, S ; Sharif University of Technology
    Institute of Electrical and Electronics Engineers Inc  2019
    Vacuum tubes are widely used for various applications. These vacuum tubes are supplied by high voltage power supplies. The amount of delivered energy from the high voltage power supply to the vacuum tube is an important issue during the vacuum arc in the tube. The protection mechanism consists of a shunt crowbar which diverts the fault current from the tube to itself as a parallel path. Detection of the vacuum arc is crucial and only one sensor is usually employed to detect the vacuum arc. This characteristic intensifies the interference susceptibility of the vacuum arc diagnosis system in a noisy environment. As a result of the noise, the arc detection system can report false alarms. False... 

    A Fast vacuum arc detection method based on the neural network data fusion algorithm for the high-voltage dc power supply of vacuum tubes

    , Article IEEE Transactions on Plasma Science ; 2020 Ayoubi, R ; Kaboli, S ; Sharif University of Technology
    Institute of Electrical and Electronics Engineers Inc  2020
    Vacuum arc is one of the most important failure factors of the vacuum tubes. The amount of delivered energy from the high-voltage dc power supply to the vacuum tube is an important issue during the vacuum arc in the tube. Vacuum arc acts as a short-circuit fault (SCF) at the power supply output. The majority of converters use a single current sensor to measure only the converter output current for detecting the SCF. However, the sensor may provide unreliable data because of the noise effect. Application of a low-pass filter reduces the noise effect. Regarding the delay of the low-pass filter, the interval of arc detection increases and more energy is delivered to the tube. In this article, a... 

    A neuro-fuzzy approach to diagnosis of neonatal jaundice

    , Article 2006 1st Bio-Inspired Models of Network, Information and Computing Systems, BIONETICS, Madonna di Campiglio, 11 December 2006 through 13 December 2006 ; 2006 ; 1424404630 (ISBN); 9781424404636 (ISBN) Sohani, M ; Makki, B ; Sadati, N ; Kermani, K. K ; Riazati, A ; Sharif University of Technology
    This paper presents an approach that integrates clinical methods with Neuro-Fuzzy system in order to diagnose Neonatal Jaundice in newborns. First, a fuzzy logic system designed with medical rules to model the uncertainty that exists in medical diagnosis. Then a fuzzy neural network with an evolutionary learning helps the system to learn the new data gained from the patient and to help the fuzzy system to update itself in an online manner. By combining the aforementioned systems, the proposed approach can help physicians to diagnose jaundice with low risk cost associated with this disease. © 2006 IEEE  

    A trainable neural network ensemble for ECG beat classification

    , Article World Academy of Science, Engineering and Technology ; Volume 70 , 2010 , Pages 788-794 ; 2010376X (ISSN) Sajedin, A ; Zakernejad, S ; Faridi, S ; Javadi, M ; Ebrahimpour, R ; Sharif University of Technology
    This paper illustrates the use of a combined neural network model for classification of electrocardiogram (ECG) beats. We present a trainable neural network ensemble approach to develop customized electrocardiogram beat classifier in an effort to further improve the performance of ECG processing and to offer individualized health care. We process a three stage technique for detection of premature ventricular contraction (PVC) from normal beats and other heart diseases. This method includes a denoising, a feature extraction and a classification. At first we investigate the application of stationary wavelet transform (SWT) for noise reduction of the electrocardiogram (ECG) signals. Then...