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Multiband highly sensitive metamaterial-based THz absorber for edible oil adulteration sensing

Optik 2024年 307卷

作者： Anowarul Haque, S.M. Sohayeb Hossain, Md Alqahtani, Abdulrahman Islam, Mohammad Tariqul Moniruzzaman, Md. Samsuzzaman, Md. Dept. of Electrical Electronic and Systems Engineering Faculty of Engineering and Built Environment Universiti Kebangsaan Malaysia Selangor Bangi43600 Malaysia Dept. of Electrical and Electronic Engineering Mymensingh Engineering College Bangladesh Department of Biomedical Technology College of Applied Medical Sciences in Al-Kharj Prince Sattam Bin Ab-dulaziz University Al-Kharj11942 Saudi Arabia Department of Medical Equipment Technology College of Applied Medical Science Majmaah University Majmaah City11952 Saudi Arabia Dept. of Electrical and Electronic Engineering College of Engineering and Technology International University of Business Agriculture and Technology Dhaka Uttara1230 Bangladesh Dept. of Computer and Communication Engineering Faculty of Computer Science and Engineering Patuakhali Science and Technology University Bangladesh Faculty of Graduate Studies Daffodil International University Daffodil Smart City Birulia Dhaka Savar1216 Bangladesh

A terahertz (THz) wave technology is very appealing for applications in detection in biomedicine, biological spectroscopy, material characterization, detection, imaging, sensing, and other convenient applications. Metamaterials (MMs) are artificial structures that have structures in a regular periodic arrangement and don't exist in nature. By utilizing a proposed terahertz metamaterial absorber, a broad spectrum of adulterated lubricants can be detected. It is an efficient detection process that enables the development of a THz detection approach by making use of the metamaterial as a sensor. The proposed terahertz absorber is analyzed and optimized using the CST Microwave Studio 2019 software. The article proposed a multiband THz metamaterial absorber with a unit size of 70 µm. According to the demonstrated results, we can achieve five narrow absorption peaks with perfect absorption within the frequency range between (0.2–4.2) Terahertz. Also, the result shows that, the average absorbance of 99.07% at the resonance frequencies of 0.56, 1.42, 2.676, 3.14, and 3.89 THz. The E (electric) and H (magnetic)-field distributions on the resonator at different resonance frequencies were also analyzed as well as. The recommended metamaterial absorber has a good sensing capability at different resonant frequencies, with refractive index sensitivities of 80 GHz/RIU, 240 GHz/RIU, 480 GHz/RIU, 480 GHz/RIU, and 520 GHz/RIU obtained by modifying the refractive index of the sample holder or the analytic layer, respectively. As a result, the proposed detector has a high refractive index sensitivity, high Q-factor, and high FOM, making it suitable for detecting oil adulteration. © 2024 Elsevier GmbH

关键词： Metamaterials

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Artificial Neural Network-Based Inverter Control and MPPT for Enhanced Performance of Hybrid Microgrids With PV and Battery Storage

Artificial Neural Network-Based Inverter Control and MPPT fo...

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International Renewable Energy Congress

作者： Z. Rajab M. Elrashid M. Elhashane J. Gómez-Romero A. Khalil Seliman A F. Mohamed Electrical and Electronic Department Faculty if Engineering Benghazi University. Department of Computer Science and Artificial Intelligence University of Granada. DTU Engineering Technology Technical University of Denmark Denmark Electrical Department Faculty of Engineering Omar Al-Mukhtar University Libya Authority of Natural Science Research and Technology Tripoli Libya

ISBN: (数字)9798331516772

ISBN: (纸本)9798331516789

Today's power system network has become more complex, with greater responsibilities and challenges in providing a secure, reliable, and high-quality energy supply to communities. A smaller entity of the electrical network, known as a Microgrid (MG), has become more popular in recent times to enhance the reliability and security of energy supply during any energy crisis in the utility network. Microgrids (MG) can provide clean energy through renewable resources such as photovoltaic (PV) systems, wind, and energy storage, offering an effective solution for power supply in both remote and urban residential communities. To ensure the stable operation of a standalone microgrid based on a photovoltaic system, it is essential to implement various mechanisms and control strategies simultaneously for optimal efficiency. This paper introduces a complete model of a hybrid microgrid consisting of a PV source, an Artificial Neural Network (ANN)-based Maximum Power Point Tracking (MPPT) system, a storage unit, a DC to AC converter with an ANN controller, and both DC and AC loads. The performance of the controller under various ambient conditions and load variations is tested. The ANN controller demonstrates good performance in different situations.

关键词： Maximum power point trackers Photovoltaic systems Wind Wind energy Power supplies Microgrids Artificial neural networks Power system reliability Reliability Security

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MorphText: Deep Morphology Regularized Accurate Arbitrary-shape Scene Text Detection

arXiv

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arXiv 2024年

作者： Xu, Chengpei Jia, Wenjing Wang, Ruomei Luo, Xiaonan He, Xiangjian Faculty of Engineering and IT University of Technology Sydney Australia The Department of Computer Science University of Nottingham Ningbo China School of Data and Computer Science National Engineering Research Center of Digital Life Sun Yat-sen University China The School of Computer Science and Information Security Guilin University of Electronic Technology China

Bottom-up text detection methods play an important role in arbitrary-shape scene text detection but there are two restrictions preventing them from achieving their great potential, i.e., 1) the accumulation of false text segment detections, which affects subsequent processing, and 2) the difficulty of building reliable connections between text segments. Targeting these two problems, we propose a novel approach, named "MorphText", to capture the regularity of texts by embedding deep morphology for arbitrary-shape text detection. Towards this end, two deep morphological modules are designed to regularize text segments and determine the linkage between them. First, a Deep Morphological Opening (DMOP) module is constructed to remove false text segment detections generated in the feature extraction process. Then, a Deep Morphological Closing (DMCL) module is proposed to allow text instances of various shapes to stretch their morphology along their most significant orientation while deriving their connections. Extensive experiments conducted on four challenging benchmark datasets (CTW1500, Total-Text, MSRA-TD500 and ICDAR2017) demonstrate that our proposed MorphText outperforms both top-down and bottom-up state-of-the-art arbitrary-shape scene text detection approaches. Copyright © 2024, The Authors. All rights reserved.

关键词： Morphology

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Scenario-Oriented Multi-Cut Generalized Benders Decomposition-Based Distributed OPF for AC/DC Hybrid Grids

Scenario-Oriented Multi-Cut Generalized Benders Decompositio...

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IEEE PES Innovative Smart Grid Technologies Conference Europe (ISGT Europe)

作者： Hai-Xiao Li Hakan Ergun Dirk Van Hertem Aleksandra Lekic Faculty of Electrical Engineering Mathematics & Computer Science Delft University of Technology Delft The Netherlands School of Electrical and Electronic Engineering Chongqing University of Technology Chongqing China Electa Department of Electrical Engineering KU Leuven Leuven Belgium Etch-EnergyVille Genk

ISBN: (数字)9798350390421

ISBN: (纸本)9798350390438

In this paper, a distributed optimal power flow (OPF) for the AC/DC hybrid grid, composed of the AC grid, renewable energy system (RES), and voltage source converter (VSC)-based multi-terminal DC (MTDC) grid, is presented. Firstly, we apply a series of linear approximations/convex relaxations to construct a mixed-integer convex AC/DC OPF model. To address the uncertainties from RESs, we then illustrate scenario-oriented decision making for the constructed AC/DC OPF model. Additionally, we verify that considering all possible scenarios can be replaced by a small set of extreme scenarios if the OPF model is (mixed-integer) convex. Furthermore, we develop a scenario-oriented multi-cut generalized Benders decomposition to achieve more efficient distributed problem solving for the constructed AC/DC OPF model. Finally, numerical results are provided to validate the effectiveness of our constructed AC/DC OPF model and our developed distributed problem-solving approach.

关键词： Renewable energy sources Uncertainty Decision making Europe Hybrid power systems Numerical models Smart grids Problem-solving Power conversion Load flow

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Machine Learning based Beamwidth Adaptation for mmWave Vehicular Communications 16

Machine Learning based Beamwidth Adaptation for mmWave Vehic...

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16th IEEE Malaysia International Conference on Communication, MICC 2023

作者： Manic, Setinder Foh, Chuan Heng Kose, Abdulkadir Lee, Haeyoung Leow, Chee Yen Chatzimisios, Periklis Moessner, Klaus Suthaputchakun, Chakkaphong University of Surrey 5GIC & 6GIC Guildford United Kingdom Abdullah Gul University Department of Computer Engineering Kayseri Turkey School of Physics Engineering and Computer Science University of Hertfordshire Hatfield United Kingdom Universiti Teknologi Malaysia Wireless Communication Centre Johor Malaysia International Hellenic University Department of Information and Electronic Systems Engineering Thessaloniki Greece Technical University Faculty of Electronics and Information Technology Chemnitz Germany Bangkok University Electrical and Computer Engineering Department Khlong Nueng Thailand

ISBN: (纸本)9798350304343

The incorporation of mmWave technology in vehicular networks has unlocked a realm of possibilities, propelling the advancement of autonomous vehicles, enhancing interconnectedness, and facilitating communication for intelligent transportation systems (ITS). Despite these strides in connectivity, challenges such as high path-loss have arisen, impacting existing beam management procedures. This work aims to address this issue by improving beam management techniques, specifically focusing on enhancing the service time between vehicles and base stations through adaptive mmWave beamwidth adjustments, accomplished using a Contextual Multi-Armed Bandit Algorithm. By leveraging various conditions to train the ML agent of the Contextual Multi-Armed Bandit Algorithm, it seeks to learn about vehicle mobility profiles and optimize the usage of different antenna beamwidth settings to maximize seamless connection time. The extensive simulation results showcase the effectiveness of an adaptive beamwidth for mobility profiles, extending the connection time a vehicle experiences with a base station when compared to the existing strategies. © 2023 IEEE.

关键词： Base stations

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Energy Efficient Trajectory Optimization and Resource Allocation for HAP-Assisted UAV Wireless Networks

Energy Efficient Trajectory Optimization and Resource Alloca...

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IEEE Conference on Global Communications (GLOBECOM)

作者： Hui Zhao Zheng Chang School of Computer Science and Engineering University of Electronic Science and Technology of China Chengdu China Faculty of Information Technology University of Jyväskylä Jyväskylä Finland

In this paper, we propose an energy efficiency (EE) optimization scheme for data collection in high altitude platform (HAP)-assisted unmanned aerial vehicle (UAV) network. The HAP acts as the aerial base station (ABS) to assist UAV and sensing devices (SDs) establishing direct uplink data transmission, i.e., device-to-UAV (D2U) communication. Our goal is to operate the UAV in an energy-efficient manner for cyclic data collection by dynamically clustering the target area and optimizing sink SD selection and transmit power in D2U communications. An optimization problem is formulated that maximizes the throughput-energy utility. Aiming at addressing the formulated problem, we propose a dynamic clustering algorithm based on Affinity Propagation (AP) to determine sink SDs for D2U communications, and a centralized reinforcement learning algorithm based on Proximal Policy Optimization (PPO) to obtain the optimal UAV trajectory and sink SDs' transmit power. Simulation results demonstrate that the proposed scheme has advantages in EE compared with other schemes.

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Multi-agent Deep Reinforcement Learning-based Trajectory Design for UAV-aided Edge Computing System

Multi-agent Deep Reinforcement Learning-based Trajectory Des...

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IEEE Conference on Wireless Communications and Networking

作者： Gengyuan Lu Zheng Chang School of Computer Science and Engineering University of Electronic Science and Technology of China Chengdu China Faculty of Information Technology University of Jyväskylä Jyväskylä Finland

The unmanned aerial vehicle (UAV)-aided communication system is able to extend the coverage of the cellular network and provide flexible connectivity to the ground users. Recently, in order to achieve the ambitious goal of ubiquitous computing and intelligence, UAV-aided mobile edge computing (MEC) system also attracts significant research interests. In this work, we investigate the trajectory design for a multi-UAV-aided MEC system to maximize the defined quality of experience (QoE) and service fairness of multiple ground user equipments (UEs). Since the practical communication environment is complex and time-varying, it is challenging for the multiple UAVs to dynamically make autonomous decisions. Meanwhile, the centralized decision-making scheme may also have a certain degree of transmission delay and affect efficiency of the considered system. Therefore, bearing in mind these challenges, in order to solve the formulated problem, we propose a multi-agent deep reinforcement learning algorithm using Multi-Agent Deep Deterministic Policy Gradient (MADDPG) to design UAV’s trajectory via optimizing the flying angle and distance. The simulation results show that our proposed solution outperforms the traditional algorithms.

关键词： Deep learning Multi-access edge computing Simulation Heuristic algorithms Decision making Reinforcement learning Ubiquitous computing

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Joint Sensing and Computation Offloading for Wireless Powered Mobile Edge Computing System

Joint Sensing and Computation Offloading for Wireless Powere...

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IEEE Conference on Global Communications (GLOBECOM)

作者： Wenxin Wu Zheng Chang School of Computer Science and Engineering University of Electronic Science and Technology of China Chengdu China Faculty of Information Technology University of Jyväskylä Jyväskylä Finland

Mobile-edge computing (MEC) and wireless power transfer (WPT) are promising paradigms in the Internet of Things (IoT) era to alleviate limitations of energy and computation capacity of wireless devices (WDs). In this paper, we consider a wireless-powered MEC in which one hybrid access point (HAP) with a stable energy supply and computation capacity coordinates with a set of WDs with WPT and sensing capabilities. In the considered model, WDs first harvest RF energy transmitted by HAP and then sense data with stored energy for multiple sensing tasks. With MEC, WDs can execute tasks locally or offload data to HAP. To minimize the average latency, we formulate a joint sensing and processing optimization problem in a wireless powered-MEC system under energy and successful sensing probability constraints. This NP-hard problem can be decoupled into three subproblems. Then, we adopt an alternating algorithm to iteratively solve the WPT time, sensing time, and offloading policy subproblems. Simulation results demonstrate the effectiveness of our proposed joint optimization algorithm.

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Development of Boost Converter System with Solar Charging Controller for Electrical Equipment

Development of Boost Converter System with Solar Charging Co...

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IEEE International Conference on engineering Technologies and Applied Sciences (ICETAS)

作者： Babul Salam Ibrahim Dur Muhammad Soomro Sharman Sundarajoo Mohd Fakhrul Shahirin Electrical and Computer Engineering Department Gulf University for Science & Technology Kuwait Faculty of Electrical and Electronic Engineering Universiti Tun Hussein onn Malaysia Johor Malaysia

There are numerous DC to DC energy alteration utilizations where the origin voltage needs to be transformed to a larger resulting voltage. Boost converters utilization includes energy equipment for semiconductor manufacturing supplies, ultrasound instruments, X-ray devices, solar systems, and mercury ion motors. Notably, this type of converter is used to step up the photovoltaic generator's voltage to the required load voltage in solar systems. Hence, this study's principal interest is to form and compose a boost converter and a solar charging controller circuit. This system aims to change the uncontrolled input of DC to a regulated output of DC with the wanted level of voltage. There are three critical procedures involved to produce a boost converter. The first process was to design. Next was to simulate, and the final process was to construct the boost converter and a solar charging controller circuit. The operational frequency was configured at 20 kHz, and a duty cycle of 50% was employed. In this study, the OrCAD PSpice, Multisim, and Proteus software environments were used to simulate the develop the circuit to obtain results. Every parameter value was obtained from the hardware. The values obtained were compared with the calculation, simulation, and hardware results from the boost converter circuit as a validation procedure.

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Comparator Design Resistance Mitigation by using Cadence Virtuoso Tools in 45 Nanometer Process technology

Comparator Design Resistance Mitigation by using Cadence Vir...

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IEEE International Conference on Sensors and Nanotechnology

作者： Michelle Ang Syn Yi Razaidi Hussin Fakhrul Zaman Rokhani Faculty of Electronic Engineering Technology University Malaysia Perlis Arau Malaysia Department of Computer and Communications System Engineering University Putra Malaysia UPM Serdang Malaysia

This paper presents the resistance mitigation techniques for comparator design. Resistance plays an important role to semiconductor field. If resistance value higher than the design specification value, this might cause the electronic device burning and destroy. This project implements the techniques to mitigate resistance for the comparator design layout which are using multiple metal layers for routing, routing track improvement, increase metal width, increase number of vias and using higher metal layer for routing by using Cadence Virtuoso tools in 45 nanometer process technology. Based on the result, the total percentage for resistance mitigation for using multiple metal layers for routing is 73.66%, routing track improvement is 67.67%, increase metal width is 51.74%, increase number of vias is 50% and using higher metal layer for routing is 18.79%.

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