Showing 7 results for Mohsen
F. Mohseni-Kolagar, H. Miar-Naimi,
Volume 7, Issue 3 (September 2011)
Abstract
Due to the nonlinear nature of the Bang-Bang phase-locked loops (BBPLLs), its
transient analysis is very difficult. In this paper, new equations are proposed for expression
of transient behavior of the second order BBPLLs to phase step input. This approach gives
new insights into the transient behavior of BBPLLs. Approximating transient response to
reasonable specific waveform the loop transient time characteristics such as locking time,
peak time, rise time and over shoot are derived with acceptable accuracy. The validity of
the resulted equations is verified through simulations using MATLAB SIMULINK.
Simulation results show the high accuracy of the proposed method to model BBPLLs
behavior.
O. Mahmoudi Mehr, M. R. Mohammadi, M. Soryani,
Volume 19, Issue 3 (September 2023)
Abstract
Speckle noise is an inherent artifact appearing in medical images that significantly lowers the quality and accuracy of diagnosis and treatment. Therefore, speckle reduction is considered as an essential step before processing and analyzing the ultrasound images. In this paper, we propose an ultrasound speckle reduction method based on speckle noise model estimation using a deep learning architecture called “speckle noise-based inception convolutional denoising neural network" (SNICDNN). Regarding the complicated nature of speckle noise, an inception module is added to the first layer to boost the power of feature extraction. Reconstruction of the despeckled image is performed by introducing a mathematical method based on solving a quadratic equation and applying an image-based inception convolutional denoising autoencoder (IICDAE). The results of various quantitative and qualitative evaluations on real ultrasound images demonstrate that SNICDNN outperforms the state-of-the-art methods for ultrasound despeckling. SNICDNN achieves 0.4579 dB and 0.0100 additional gains on average for PSNR and SSIM, respectively, compared to other methods. Denoising ultrasound based on its noise model estimation is not only a novel approach in comparison to traditional denoising autoencoder models but also due to the fact that it uses mathematical solutions to recover denoised images, SNICDNN shows a greater power in ultrasound despeckling.
Abolfazl Karimiyan Abdar, Ali Esteki, Mohsen Sheikh Hassani,
Volume 20, Issue 1 (March 2024)
Abstract
The impact of cognitive tasks on human movement is of practical significance; we hereby aim to demonstrate that a significant relationship exists between the dual task’s cognitive demand and the disruption caused in hand movement, with the hope to extend this experiment to subjects with disorders (MS, CP, stroke patients) in future studies. By doing so, we hope to be able to develop a metric for evaluating their disease levels using our method and minimize clinical interventions. While previous research has predominantly focused on lower body activities, this study explores the effect of dual tasks on hand movements in healthy individuals.
A simulated finger-to-nose test combined with a standard reverse counting task, featuring four difficulty levels, was conducted. Utilizing SVM and decision tree classifiers, we analyzed various features to discern the impact of cognitive tasks on hand movements, including completed cycles and idle time at markers. Our findings reveal that features such as entropy and kurtosis effectively distinguish between task difficulty levels and hand movement disruption. The classifiers achieved accuracies of 70% and 74% for decision tree and SVM, respectively. We hope extending this research to diseased subjects could potentially provide a more accurate assessment of disease severity through the measurement of hand movements during cognitive tasks, offering a non-clinical alternative for disease evaluation.
Aws Alazawi, Huda Jameel, Mohammed Mohsen,
Volume 20, Issue 2 (June 2024)
Abstract
This study explores the use of distortion product otoacoustic emission (DPOAE) as a hearing screening modality for newborns and adults with hearing impairment. The goal is to improve cochlear response by developing digital filter characteristics to make it consistent for specialists to make accurate diagnoses. To accomplish this, the proposed system consists of a DPOAE ER-10C as stimulation and cochlear response probe, a digital signal processor, an oscilloscope, PC, and audio cables. Real-time distortion product frequency components were extracted using a signal processor of TMS320C6713. To validate the system, a senior medical physicist at Baghdad Medical City in Iraq conducted a study with five hearing-normal volunteers ages 38 and 55 at the center for hearing and communication. The results showed an ability to extract distortion product components in real-time implementation, with the superiority of shape parameters greater than 0.5. In addition, the quantization of filter coefficients was compared for both floating-point arithmetic and fixed-point arithmetic. Noisy environment-based noise reduction techniques have to be investigated by considering the implementation of robust digital signal processing techniques. Finally, the proposed system would contribute to advancements in hearing screening and treatment for those with hearing impairment.
Saeed Hasanzadeh, Seyed Mohsen Salehi, Mohammad Javad Saadatmandfar,
Volume 20, Issue 3 (September 2024)
Abstract
Various forms of distributed generation (DG), such as photovoltaic (PV) systems, play a crucial role in advancing a more sustainable future, driven by economic factors and environmental policies implemented by governments. DC-DC converters are essential for harnessing power from solar cells, as they maintain a constant output voltage despite fluctuations in input voltage. Typically, step-up converters are employed to raise output voltage levels, though they often apply the same voltage to an active switch as the output voltage, which can be limiting. To effectively integrate distributed generation sources with the utility grid, high-voltage gain step-up converters are necessary since these sources typically operate at low voltage levels. This study presents an enhanced design of non-isolated DC-DC converters with high voltage gain tailored for photovoltaic (PV) applications. The proposed architecture achieves a quadratic increase in output voltage gain, which alleviates voltage stress on the active switch. Our converter design features a quadratic boost converter complemented by a voltage-boosting cell, facilitating significant voltage amplification. This topology benefits from employing an active switch while minimizing the number of inductors required, resulting in a more compact circuit design. Furthermore, the proposed architecture shares characteristics with recently published topologies regarding passive component utilization, voltage gain, and other relevant parameters. To validate our findings, we conducted mathematical analyses and simulations, with results corroborated by experimental data from laboratory prototype tests.
Nabiollah Ramezani, Mohsen Shahnazdoost Kilvaei,
Volume 21, Issue 1 (March 2025)
Abstract
In this paper, a novel method is presented that can accurately estimate the Thevenin equivalent circuit parameters of an external power system by RTUs. The presented method is based on the simultaneous measurements of the desired points in the boundary system, which includes the bus voltage amplitude, the current amplitude of the boundary transmission lines, as well as active and reactive power, and is continuously active until the Thevenin equivalent circuit model would be available online. The practical application of the proposed method is related to online monitoring and control of wide-area power systems as well as their development design. Also, the innovation of the method is the accurate estimation of the Thevenin equivalent circuit model from part of the power network where information is not available. In the proposed method, an additional measurement and the least squares method are used to eliminate measurement errors in order to accurately estimate the parameters of the equivalent circuit model. In order to avoid providing the wrong equivalent circuit model due to external system changes, a method is presented that can track the correct system changes to continuously monitor the disturbances. The proposed method performance has been implemented and validated by DigSILENT software.
Mohammadreza Alizadeh Aliabadi, Mohsen Karimi, Zahra Karimi, Mehrdad Soheili Fard,
Volume 21, Issue 1 (March 2025)
Abstract
Photoplethysmography (PPG) signals provide a non-invasive means of monitoring cardiovascular status during physical exercise; however, they are prone to noise, especially motion artifacts (MA). For specific telemedicine applications, compression is necessary for tasks such as PPG signal generation and secure data transmission. In this study, the investigation focused on determining whether it is better to perform compression before or after noise removal by applying a noise removal method and various compression methods. To achieve the aim, the study explored a subspace-based denoising method called "Maximum Uncorrelated PPG Denoising." Additionally, signal compression methods were examined in nine distinct steps. Compression quality is evaluated using various criteria, such as compression rate (CR) and Percentage Root Mean Square Difference (PRD). The results showed that regardless of the type of compression method, it is better not to remove noise before the compression process because doing so reduces CR and increases PRD.
