Showing 6 results for Rahman
H. Rahmanian, S. H Sedighy, M. Khalaj Amirhosseini,
Volume 11, Issue 1 (March 2015)
Abstract
A method for design and implementation of a compact via-less Composite
Right/Left-Handed Transmission Line (CRLH TL) is presented. By introducing a new
circuit model, the CRLH transmission line behavior is studied versus the parameters
variations to achieve the desired characteristic impedance and electrical length. Then a
compact quarter wavelength CRLH transmission line with 70 Ω characteristic impedance is
designed as an example. Finally a very compact four way Wilkinson power divider and a
rat-race coupler are designed and fabricated by using this type of CRLH TL which exhibit
about 75% and 80% compactness, respectively.
J. Rahmani Fard,
Volume 16, Issue 1 (March 2020)
Abstract
By combining the field-weakening control principle of a new axial flux-switching permanent-magnet motor (AFFSSPM) with the space vector pulse width modulation (SVPWM) and maximum torque per voltage (MTPV) control principle, a novel field-weakening control strategy for AFFSSPM is proposed in this paper. In the first stage of the field-weakening, the difference between the reference voltage updated by the current regulator and the saturated voltage output with SVPWM is used for field-weakening control, which modifies the direct axis of stator current. This method makes full use of the DC bus voltage, and can naturally smooth transition. In the second stage of the field weakening, the principle of MTPV control is used for field-weakening control, and then, being linearized. Compared with the traditional method, this method solves the problem of depth weakening of AFFSSPM. Between the two stages, the turning speed is used for the switch condition to achieve a smooth transition. The effectiveness and correctness of the proposed field-weakening control method and calculation method were verified with simulation results. Moreover, the dSPACE semi-physical simulation experimental platform for the hardware design and software design is used, and the semi-physical simulation experiment is carried out. The results show the accuracy and effectiveness of the proposed scheme.
S. A. Rahman, S. Birhan, E. D. Mitiku, G. T. Aduye, P. Somasundaram,
Volume 17, Issue 4 (December 2021)
Abstract
Aim of this paper is to attain the highest voltage sag and swell compensation using a direct converter-based DVR topology. The projected DVR topology consists of a direct converter with bidirectional switches, a multi winding transformer with three primary windings and secondary winding and a series transformer. When voltage swell occurs in a phase, the same phase voltage can be utilized to mitigate the swell as huge voltage exists in the phase where swell has occurred. So it is possible to mitigate an infinite amount of swell. In all the DVR topologies, the converter is only used to synthesize the compensating voltage. The range of voltage sag mitigation depends upon the magnitude of input voltage available for the converter. If this input voltage of the direct converter is increased, then the range of voltage compensation could also be increased. Input voltage of the direct converter is increased using the multi winding transformer. The direct converter is synthesizing the compensating voltage. This compensating voltage is injected in series with the supply voltage through the series transformer and the sag is mitigated. In this proposed topology, the input voltage for the direct converter is increased by adding the three phase voltages using a multi winding transformer. Thus the voltage sag compensating range of this topology is increased to 68% and the swell compensating range is 500%. Ordinary PWM technique has been used to synthesize the PWM pulses for the direct converter and the THD of the compensated load voltage is less than 5%. This topology is simulated using MATLAB Simulink and the results are shown for authentication.
Pravat Biswal, Veera Venkata Subrahmanya Kumar Bhajana, Pavel Drabek,
Volume 18, Issue 4 (December 2022)
Abstract
This paper proposes two new soft-switching transformerless converters with high voltage conversion ratio. These proposed converters achieve soft-switching each with a single auxiliary resonant cell. The merit of these converters is reduced switching losses with lesser number of devices. The main switching devices are turned off with zero current switching (ZCS). Apart from the soft-switching feature, the voltage conversion ratio is increased in comparison with the existing topologies. The operating principles and the simulation results on 12V/200V/500W converter system are presented in this paper.
A. Y. Abdulrahman, O. S. Zakariyya, A. S. Afolabi, A.t. Ajiboye,
Volume 19, Issue 3 (September 2023)
Abstract
Abstract: Rain attenuation prediction models are inevitably deployed to provide rough estimates of the actual measured attenuation due to severe scarcity in most of the tropical and equatorial climates. The results of rain attenuation measurements over a 14.8 GHz terrestrial microwave link and slant-path attenuation in vertically polarized signals propagating at 10.982 GHz in a tropical Malaysian climate were reported in this study. The experimental results including the path adjustment factors were compared with the predictions of some selected rain attenuation models. The relative errors in the path length adjustment factors (PLAFs) are in the range -0.3370 – 2.6272, while those of the slant path adjustment factors (SPAFs) are -0.9252 – +0.2923. Moreso, the charts of PLAFs and SPAFs at 0.01% of the time were also presented because they are the most commonly used availability by the telecommunications service providers. This study will allow the radio engineer to select the most suitable prediction models for the particular region under study, thereby ensuring adequate radio planning for improved service delivery especially in the tropical climates due to their peculiarity.
𝐒𝐢𝐫𝐚𝐣𝐮𝐬 𝐒𝐚𝐥𝐞𝐡𝐢𝐧, Shakila Rahman, 𝐌𝐨𝐡𝐚𝐦𝐦𝐚𝐝 𝐍𝐮𝐫, 𝐀𝐡𝐦𝐚𝐝 𝐀𝐬𝐢𝐟, 𝐌𝐨𝐡𝐚𝐦𝐦𝐚𝐝 𝐁𝐢𝐧 𝐇𝐚𝐫𝐮𝐧, Jia Uddin,
Volume 20, Issue 4 (December (Special Issue on ADLEEE) 2024)
Abstract
Abnormal activity detection is crucial for video surveillance and security systems, aiming to identify behaviors that deviate from normal patterns and may indicate threats or incidents such as theft, vandalism, accidents, and aggression. Timely recognition of these activities enhances public safety across various environments, including transportation hubs, public spaces, workplaces, and homes. In this study, we focus on detecting violent and non-violent activities of humans using a YOLOv9-based deep learning model considering the above issues. A diverse dataset has been built of 9,341 images from various platforms, and then the dataset has been pre-processed, i.e., augmentation, resizing, and annotating. After pre-processing, the proposed model has been trained which demonstrated strong performance, achieving an F1 score of 95% during training for 150 epochs. It was also trained for 200 epochs, but early stopping was applied at 148 epochs as there was no significant improvement in the results. Finally, the results of the YOLOv9-based model have been analyzed with other baseline models (YOLOv5, YOLOv7, YOLOv8, and YOLOv10) and it performed better compared with others.
