A Comparative Study Between Symmetrical and Asymmetrical Inverters

Inverters play a crucial role in modern power systems, converting direct current (DC) into alternating current(AC) for various applications. The choice between symmetrical and asymmetrical inverters can significantly impact system performance, efficiency, and cost. This paper presents a comprehensive comparative study of symmetrical and asymmetrical inverters, focusing on key parameters, design considerations, and their impact on system performance. Through extensive analysis and simulation, we aim to provide valuable insights for making informed decisions in selecting the appropriate inverter topology for their applications

DSP Based Digital Controller Design and Implementation for Energy Systems

This paper presents a comprehensive study on the design and implementation of DSP-based digital controllers for energy systems, with a specific focus on utilizing the TMS320F28335 microcontroller from Texas Instruments. Energy systems play a critical role in various domains and improving their control strategies using advanced digital signal processing (DSP) techniques is of utmost importance. The paper begins with an overview of energy systems and the significance of efficient control mechanisms. It then explores the fundamental concepts of DSP and highlights the relevance of using the TMS320F28335 microcontroller for digital control applications in energy systems. The microcontroller offers a powerful combination of performance, features, and flexibility, making it suitable for implementing complex control algorithms

The Impact of User Participation on the Success of Enterprise Resource Planning (ERP) Adoption in Bangladesh

The successful adoption of Enterprise Resource Planning (ERP) systems is crucial for organizations to enhance operational efficiency and gain a competitive edge. User participation has been recognized as a key factor in determining the success of ERP implementation. This study aims to investigate the impact of user participation on ERP adoption success in the context of Bangladesh. The specific objectives include assessing the relationship between user participation and work performance, understanding/proficiency, user-friendliness, and training/support. Additionally, the influence of organizational factors, such as organizational value, guidelines/procedures, and resource/support availability, on user participation is examined. The study also explores the impact of user participation on compatibility with existing organizational processes and alignment with strategic goals. The findings reveal that user participation significantly influences work performance, understanding/proficiency, user-friendliness, and training/support. Organizational factors and strategic alignment play important roles in facilitating user participation. The results emphasize the need to foster user participation, provide adequate training and support, promote organizational values, and align strategic goals for successful ERP adoption in Bangladesh. These insights contribute to a better understanding of the factors that drive ERP implementation success and provide guidance for organizations in Bangladesh and similar contexts

Enhancing Physical Layer Secrecy Performance for RIS-assisted RF-FSO Mixed Wireless System

Peer reviewedPublisher PD

Preparation and assessment of ionic liquid and few-layered graphene composites to enhance heat and mass transfer in adsorption cooling and desalination systems

Adsorption systems can utilise low-temperature renewable and waste heat sources, which have emerged as a feasible alternative to conventional water desalination and cooling systems. However, the material of poor heat and mass transfer performance stall their widespread utilisation. This article presents the development and investigation of new composites employing few-layered graphene platelets and ionic liquids, namely ethyl-methylimidazolium methane sulfonate ([EMIM][CH3SO3]) and Ethyl-methylimidazolium-chloride ([EMIM][Cl]) to address such challenges. The impact of the few-layered graphene platelets, thermal properties, water adsorption properties of the developed composites and their thermal diffusivity were experimentally investigated. Besides, the overall cyclic performance was studied experimentally at the material level and computationally at the component level by employing a previously validated 2D dynamic heat and mass transfer model. The experimental investigation indicated that pristine few-layered graphene has a surface area of 56.8978 m2/g and a relatively high thermal diffusivity of 22.23 mm2/s. The developed composites showed higher thermal diffusivity than the baseline adsorbent silica gel. The highest thermal diffusivity was 11.84 mm2/s for GP-CH3SO3-10, 394 times higher than silica gel. Water adsorption characteristics of the composites were carried out, and the Dubinin–Astakhov (D-A) model was employed to model the experimental isotherms with good accuracy. The cumulative advanced adsorption and thermal characteristics of the developed composites resulted in higher cyclic performance by up to 82 % and 85 % than that of the baseline silica gel

Recent Advances in Deep Learning Techniques for Face Recognition

In recent years, researchers have proposed many deep learning (DL) methods for various tasks, and particularly face recognition (FR) made an enormous leap using these techniques. Deep FR systems benefit from the hierarchical architecture of the DL methods to learn discriminative face representation. Therefore, DL techniques significantly improve state-of-the-art performance on FR systems and encourage diverse and efficient real-world applications. In this paper, we present a comprehensive analysis of various FR systems that leverage the different types of DL techniques, and for the study, we summarize 168 recent contributions from this area. We discuss the papers related to different algorithms, architectures, loss functions, activation functions, datasets, challenges, improvement ideas, current and future trends of DL-based FR systems. We provide a detailed discussion of various DL methods to understand the current state-of-the-art, and then we discuss various activation and loss functions for the methods. Additionally, we summarize different datasets used widely for FR tasks and discuss challenges related to illumination, expression, pose variations, and occlusion. Finally, we discuss improvement ideas, current and future trends of FR tasks.Comment: 32 pages and citation: M. T. H. Fuad et al., "Recent Advances in Deep Learning Techniques for Face Recognition," in IEEE Access, vol. 9, pp. 99112-99142, 2021, doi: 10.1109/ACCESS.2021.309613

Energy scenario : production, consumption and prospect of renewable energy in Australia

Australia is the world’s 9th largest energy producer, 17th largest consumer of non-renewable energy resources and ranks 18th on a per person energy consumption basis. Australia’s energy consumption is primarily composed of non-renewable energy resources (coal, oil, gas and related products), which represent 96% of total energy consumption. Renewables, the majority of which is bioenergy (wood and wood waste, biomass, and biogas) combined with clear energy namely wind, solar hot water, solar electricity, hydroelectricity account for the remaining 4% consumption. Australia’s renewable energy resources are largely undeveloped which can contribute directlyto the Australian economy. In this article, a review of literature on energy scenario is presented and discussed. Australia’s total energy production, consumption, storage and export (including renewable and non-renewable) data has been analyzed and discussed in this study. The main objective of the study is to analyze the prospect of renewable energy in Australia. This study concludes that Australian economy will grow faster if its undeveloped renewable energies can be used efficiently for electricity generation and transport sector

Tunable Multistate Terahertz Switch Based on Multilayered Graphene Metamaterial

We proposed plasmonic effect based narrow band tunable terahertz switches consisting of multilayered graphene metamaterial. Though several terahertz optical switches based on metamaterials were previously reported, these switches had complicated fabrication processes, limited tunability, and low modulation depths. We designed and simulated ingenious four and eight state terahertz optical switch designs that can be functional for multimode communication or imaging using the finite-difference time-domain simulation technique. The plasmonic bright modes and transparency regions of these structures were adjusted by varying the chemical potential of patterned graphene layers via applying voltage in different layers. The structures exhibited high modulation depth and modulation degree of frequency, low insertion loss, high spectral contrast ratio, narrow bandwidth, and high polarization sensitivity. Moreover, our proposed simple fabrication process will make these structures more feasible compared to previously reported terahertz switches. The calculated modulation depths were 98.81% and 98.71%, and maximum modulation degree of frequencies were ~61% and ~29.1% for four and eight state terahertz switches, respectively. The maximum transmittance in transparency regions between bright modes and the spectral contrast ratio were enumerated to be 95.9% and ~96%, respectively. The maximum insertion losses were quite low with values of 0.22 dB and 0.33 dB for four and eight state terahertz switches, respectively. Our findings will be beneficial in the development of ultra-thin graphene-based multistate photonic devices for digital switching, sensing in terahertz regime.Comment: 17 Pages, 8 Figure