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Wide-band high performance optical modulator based on a stack of graphene and h-BN layers with plasmonic edge mode

Optical and Quantum Electronics 2025年第2期57卷 1-23页

作者： Karimkhani, Hossein Karim, Mohammad Ataul Faculty of Electrical and Computer Engineering University of Tabriz Tabriz Iran Department of Electrical and Computer Engineering University of Massachusetts DartmouthMA02747 United States

Modulation depth and its associated loss pose a significant challenge in electro-optical telecommunication systems. Optimal modulators strive to enhance modulation depth while minimizing loss rates. We propose a high-performance electro-optical hybrid plasmonic modulator based on graphene, hexagonal Boron Nitride (h-BN), and Molybdenum Disulfide (MoS2) layers. The substrate of the proposed modulator is SiO2 on a Silicon wafer, where Ag layers are embedded in the SiO2 layer and on top of the structure. Graphene layers at the edge of the upper and lower Ag layers and h-BN in between them create a waveguide capable of transmitting input light through the structure. Graphene and MoS2 layers increase the amount of light interaction increasing, in turn, modulation depth. The edge mode in the graphene layers confines light properly and increases the electrical field intensity in a narrow gap. The modulator’s performance is examined using a three-dimensional finite-difference time-domain (FDTD) method. The structure’s modulation depth, for a range of temperature, ranges between 40.54 dB/μm and 42.05 dB/μm. The maximum loss is estimated to be 5.723 dB/μm at 1.3 μm for 0.65 eV chemical potential, which yields a figure of merit (FoM) of 12.5 and extinction ratio (ER) of 99.51 dB. The equivalent circuit for the modulator is investigated in terms of parameters such as energy consumption and modulation bandwidth. The modulator demonstrates an impressively low energy consumption per bit, underscoring its efficiency and practicality. The modulator’s characteristics primarily arise from utilizing a thin layer of h-BN instead of thick dielectric layers. Unlike the previously examined configurations, applying voltage through the graphene layers substantially diminishes the insertion loss. © The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2025.

关键词： Silicon wafers

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Liberty: An Economy, Three Fold Collaboration, and Virtualization-aware Resource Management Approach for Multiverse Based Application Execution Over 6G Enhanced Networks

IAENG International Journal of Computer Science

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IAENG International Journal of computer Science 2024年第11期51卷 1804-1844页

作者： Chowdhury, Mahfuzulhoq Computer Science and Engineering Department Chittagong University of Engineering and Technology Chittagong4349 Bangladesh

Metaverse-based virtual worlds can provide users with an immersive digital experience by utilizing extended reality, IoT, 6G communication, and computing technology. Unlike the multiverse, in which users can access one virtual environment-based activity at a time, metaverse applications allow users to engage in different virtual environment-based activities simultaneously. Previous research did not look at three-fold collaboration, time-criticality, economy, energy, and network function virtualization (NFV)-aware resource management for multiverse, metaverse, and non-metaverse applications concurrently. To conquer these issues, this article proposes a three-fold collaboration (usage of host, neighbor user, and service provider-owned resources), time-criticality, NFV, energy, economy, and service delivery delay-aware resource management scheme for multiverse, metaverse, and non-metaverse application execution over 6G networks, taking into account heterogeneous physical and digital workers, NFV, communication resources, application arrival, and deadline. Experimental results show that the proposed liberty scheme outperforms existing methods by at least 22.67% economic cost, 31.28% energy expenditure cost, 44.11% service provider profit, and 8.83% task completion ratio gain. © (2024), (International Association of Engineers). All rights reserved.

关键词： Network function virtualization

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On the Coverage of Cognitive mmWave Networks With Directional Sensing and Communication

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IEEE Transactions on Wireless Communications 2024年第10期23卷 14215-14231页

作者： Tripathi, Shuchi Gupta, Abhishek K. Amuru, SaiDhiraj The Department of Electrical Engineering Indian Institute of Technology Kanpur Kanpur208016 India The Department of Electrical Engineering Indian Institute of Technology Hyderabad Hyderabad502285 India

Millimeter-waves’ propagation characteristics create opportunities for spatio-temporal spectrum sharing in a variety of contexts, including cognitive spectrum sharing (CSS). However, CSS with omnidirectional sensing is not efficient at mmWave frequencies due to their directional transmission, as this limits secondary networks’ ability to access the spectrum. This inspired us to create an analytical approach using stochastic geometry to examine the implications of directional sensing in millimeter-wave (mmWave) CSS. We explore a cognitive network where multiple secondary transmitter-receiver pairs coexist with multiple primary transmitter-receiver pairs. The positions of the secondary transmitters are modelled using a Poisson point process with corresponding secondary receivers located around them. A threshold on directional transmission is imposed on each secondary transmitter to limit its interference at the primary receiver. We derive the medium-access-probability of a secondary user along with the fraction of the secondary transmitters active at a time-instant. To understand cognition’s feasibility, we derive the primary and secondary links’ coverage probabilities. We provide various design insights. For example, we investigate the interference-threshold’s optimal value while ensuring both link’s coverage and its dependence on various parameters. We find that directionality improves both links’ performance. Further, allowing location-aware secondary-directionality can help achieve similar coverage for all secondary links. © 2002-2012 IEEE.

关键词： Directive antennas

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Room-temperature waveguide-integrated photodetector using bolometric effect for mid-infrared spectroscopy applications

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光：科学与应用（英文版） 2025年第5期14卷 1300-1311页

作者： Joonsup Shim Jinha Lim Inki Kim Jaeyong Jeong Bong Ho Kim Seong Kwang Kim Dae-Myeong Geum SangHyeon Kim School of Electrical Engineering Korea Advanced Institute of Science and Technology(KAIST)291 Daehak-RoYuseong-GuDaejeon 34141Republic of Korea Department of Electrical & Computer Engineering Inha University100Inha-roMichuhol-guIncheon 22212Republic of Korea

Waveguide-integrated mid-infrared(MIR)photodetectors are pivotal components for the development of molecular spectroscopy applications,leveraging mature photonic integrated circuit(PIC)*** various strategies,critical challenges still remain in achieving broadband photoresponse,cooling-free operation,and large-scale complementary-metal-oxide-semiconductor(CMOS)-compatible *** leap beyond these limitations,the bolometric effect-a thermal detection mechanism-is introduced into the waveguide *** importantly,we pursue a free-carrier absorption(FCA)process in germanium(Ge)to create an efficient light-absorbing medium,providing a pragmatic solution for full coverage of the MIR spectrum without incorporating exotic materials into ***,we present an uncooled waveguide-integrated photodetector based on a Ge-on-insulator(Ge-OI)PIC architecture,which exploits the bolometric effect combined with ***,our device exhibits a broadband responsivity of 28.35％/mW across 4030-4360 nm(and potentially beyond),challenging the state of the art,while achieving a noise-equivalent power of 4.03×10-7W/Hz0.5 at 4180 *** further demonstrate label-free sensing of gaseous carbon dioxide(CO2)using our integrated photodetector and sensing waveguide on a single *** approach to room-temperature waveguide-integrated MIR photodetection,harnessing bolometry with FCA in Ge,not only facilitates the realization of fully integrated lab-on-a-chip systems with wavelength flexibility but also provides a blueprint for MIR PICs with CMOS-foundry-compatibility.

关键词： applications temperature integrated room bolometric effect mid-infrared photodetector spectroscopy using

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Blockchain-based rumor detection approach for COVID-19

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Journal of Ambient Intelligence and Humanized Computing 2024年第1期15卷 435-449页

作者： Rani, Poonam Jain, Vibha Shokeen, Jyoti Balyan, Arnav Department of Computer Engineering Netaji Subhas University of Technology Delhi India Department of Computer Science and Engineering University Institute of Engineering and Technology Maharshi Dayanand University Haryana Rohtak India

The ubiquity of handheld devices and easy access to the Internet help users get easy and quick updates from social media. Generally, people share information with their friends and groups without inspecting the posts’ veracity, which causes false information propagation in the network. Moreover, detecting false news and rumors in such a massive load of unstructured information is a very tedious task. Results, many literature papers explored different machine learning and deep learning approaches to detect the presence of rumors on social media networks. Although detection of misleading news and rumors is not sufficient, therefore, we have proposed a model for the detection and prevention of transmitted rumors in this paper. In this paper, we use blockchain technology to verify the credibility of information and design a framework with four layers: network layer, blockchain layer, machine layer, and device layer, to prevent the propagation of rumors in the network. We also use deep learning techniques to identify the anomalies in the network. The Bi-directional Long Short Term Memory (Bi-LSTM) model is used to prevent the introduction of new rumors by continuously monitoring incoming messages in the network. The experimental results demonstrate that the proposed Bi-LSTM model outperforms state-of-the-art machine learning methods and recent baseline work. Performance is compared over different metrics such as accuracy, precision, recall, f1-score, and specificity. Experiment results show that our Bi-LSTM model outperforms all the other approaches and achieved 99.63 % accuracy. Additionally, the probability of incorrect detection is significantly low with only 0.13% false positive. © The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature 2022.

关键词： COVID-19

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Power quality improvement in renewable energy integrated grid: a review

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International Journal of Power and Energy Conversion 2024年第4期15卷 352-375页

作者： Lolamo, Mathewos Kumar, Rajan Sharma, Veena Department of Electrical Engineering National Institute of Technology Himachal Pradesh Hamirpur177005 India Department of Electrical Engineering National Institute of Technology Chhattisgarh Raipur India

Incorporating renewable energy sources (RES), like wind and solar energy, is crucial for combating climate change and promoting sustainability. However, it introduces challenges to power quality (PQ) in distribution systems due to RES output variability, including voltage and frequency fluctuations and harmonics. Distributed flexible alternating current transmission system (DFACTS) devices, like unified power quality conditioner and distributed static compensator, effectively mitigate these challenges when appropriately controlled. Integrating energy storage systems (ESSs) like battery ESS with these devices and controlling them efficiently using traditional, AI-based, or adaptive control algorithms further enhances the mitigation performance of PQ in RES-connected grids. This review highlights PQ issues, categorisation, and mitigation strategies. It also highlights improving PQ in RES-integrated grids by enhancing DFACTS device performance through ESS combination and effective control. This review synthesises PQ enhancement strategies in RES-integrated grids from existing literature to support future research. Copyright © 2024 Inderscience Enterprises Ltd.

关键词： control technique DFACTS devices energy storage system power quality renewable energy source

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iLIAC: An approach of identifying dissimilar groups on unstructured numerical image dataset using improved agglomerative clustering technique

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Multimedia Tools and Applications 2024年第39期83卷 86359-86381页

作者： S, Sreedhar Kumar Ahmed, Syed Thouheed Fathima, Afifa Salsabil Mathivanan, Sandeep Kumar Jayagopal, Prabhu Saif, Abdu Gupta, Sachin Kumar Sinha, Garima Department of Computer Science and Engineering School of Engineering and Technology CMR University Karnataka Bengaluru India Department of Electrical Engineering Indian Institute of Technology Hyderabad Telangana Kandi India School of Computer Science and Engineering REVA University Bangalore India School of Computer Science and Engineering Galgotias University Uttar Pradesh Greater Noida203201 India School of Computer Science Engineering and Information Systems Vellore Institute of Technology Tamil Nadu Vellore632014 India Department of Communication and Computer Engineering Faculty of Engineering and IT Taiz University Taiz Yemen Katra India Department of Computer Science Engineering Jain University Bangalore India

Unstructured Numerical Image Dataset Separation (UNIDS) method employing an enhanced unsupervised clustering technique. The objective is to delineate an optimal number of distinct groups within the input grayscale (G-S) image content, utilizing the improved limited iteration agglomerative clustering (iLIAC) clustering technique for the separation and enhancement of picture elements. The UNIDS method is structured into two primary stages: partitioning and validation. In the partitioning stage, the UNIDS method identifies an appropriate number of discrete clusters within the grayscale image using the iLIAC technique, eliminating the need for predetermined procedures. Subsequently, the method evaluates the similarity and deviation among data elements within the same group in the resultant image dataset. Additionally, it assesses the proximity and inters severance among clusters in the outcome of the image dataset through the partitioning process. Empirical results indicate that the UNIDS system excels in the spontaneous identification of an optimal number of discrete clusters within the input G-S image. The system demonstrates superior thickness, reduced deviation among data elements within the same cluster, increased inter-separation, and diminished inter-closeness between cluster elements. Furthermore, empirical analysis establishes the superior performance of the UNIDS approach compared to existing clustering techniques. © The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2024.

关键词： Iterative methods

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DDSS: Driver decision support system based on the driver behaviour prediction to avoid accidents in intelligent transport system

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International Journal of Cognitive Computing in engineering 2024年第1期5卷 1-13页

作者： S, Balasubramani D, John Aravindhar Renjith, P.N. Ramesh, K. Department of Computer Science and Engineering Koneru Lakshmaiah Education Foundation Andhra Pradesh Vaddeswaram India Department of Computer Science and Engineering Hindustan Institute of Technology and Science Chennai India School of Computer Science and Engineering Vellore Institute of Technology Chennai India Department of Computer Science and Engineering Sri Krishna College of Engineering and Technology Coimbatore India

Accidents caused by drivers who exhibit unusual behavior are putting road safety at ever-greater risk. When one or more vehicle nodes behave in this way, it can put other nodes in danger and result in potentially catastrophic accidents. In order to anticipate and handle unusual driving behavior in Intelligent Transportation Systems (ITS), this research presents a unique Driver Decision Support System (DDSS). A reliable driving behavior prediction system is used by the suggested DDSS to categorize drivers as displaying normal or abnormal behavior. In order to prevent accidents in ITS scenarios, the system reliably detects anomalous driving patterns and advises nearby vehicles to change lanes or alter speed. The driver behavior prediction algorithm efficiently groups drivers into behavior categories using the K-Means clustering method. In order to evaluate the algorithm's efficacy, a comparative analysis is conducted by comparing its outcomes against those of Support Vector Machines (SVMs), Decision Trees, K-Nearest Neighbours (KNN), Logistic Regression, and Naïve Bayes. The integration of the Driver Decision Support System into the Intelligent Transportation System infrastructure serves to augment endeavours in accident prevention. Monitoring and analysis of driver behavior enable timely interventions, promoting safer driving practices and reducing accident risks. This research helps to create a more effective transportation system by reducing the number of accidents brought on by reckless driving. Because of its novel method to anticipating and controlling driver behavior, the proposed DDSS has promise for improving road safety and preventing accidents. The efficacy and the dependability of the driver behavior prediction algorithm are confirmed by the experimental assessment. © 2023

关键词： K-means clustering

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Multiple-Masks Error Correction Code Transformer for Short Block Codes

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IEEE Journal on Selected Areas in Communications 2025年第7期43卷 2518-2529页

作者： Park, Seong-Joon Kwak, Hee-Youl Kim, Sang-Hyo Kim, Sunghwan Kim, Yongjune No, Jong-Seon Institute of Artificial Intelligence Pohang37673 Korea Republic of University of Ulsan Department of Electrical Electronic and Computer Engineering Ulsan44610 Korea Republic of Sungkyunkwan University Department of Electrical and Computer Engineering Suwon16419 Korea Republic of Kyonggi University School of Electronic Engineering Suwon16227 Korea Republic of Department of Electrical Engineering Pohang37673 Korea Republic of Yonsei University Institute for Convergence Research and Education in Advanced Technology Seoul03722 Korea Republic of Seoul National University Department of Electrical and Computer Engineering Seoul08826 Korea Republic of

With the broadening applications of deep learning, neural decoders have emerged as a key research focus, specifically aimed at improving the decoding performance of conventional decoding algorithms. In particular, error correction code transformer (ECCT), which utilizes the transformer architecture, has achieved state-of-the-art performance among neural network-based decoders. We present three technical contributions to significantly enhance the performance of ECCT. First, we propose a novel transformer architecture of ECCT, termed the multiple-masks ECCT (MM ECCT). We employ multiple masked self-attention blocks with different mask matrices in a parallel manner to learn diverse relationships among the codeword bits. Second, we discover that constructing mask matrices based on systematic parity check matrices (PCMs) can make the attention maps sparse, which not only enhances the decoding performance but also reduces computational complexity. Finally, we propose using complementary mask matrices derived from cyclic permutations of the systematic PCM. These complementary mask matrices are specifically designed to enhance the decoding of cyclic codes. Our extensive simulation results show that the proposed MM ECCT architecture with carefully designed mask matrices outperforms the original ECCT by a large margin, achieving state-of-the-art decoding performance among neural decoders. The source code is available at https://***/iil-postech/mm-ecct. © 1983-2012 IEEE.

关键词： Decoding

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Liquid lens based holographic camera for real 3D scene hologram acquisition using end-to-end physical model-driven network

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Light(Science & Applications) 2024年第3期13卷 488-497页

作者： Di Wang Zhao-Song Li Yi Zheng You-Ran Zhao Chao Liu Jin-Bo Xu Yi-Wei Zheng Qian Huang Chen-Liang Chang Da-Wei Zhang Song-Lin Zhuang Qiong-Hua Wang School of Instrumentation and Optoelectronic Engineering Beihang UniversityBeijing 100191China School of Optical-Electrical and Computer Engineering University of Shanghai for Science and TechnologyShanghai 200093China

With the development of artificial intelligence,neural network provides unique opportunities for holography,such as high fidelity and dynamic *** to obtain real 3D scene and generate high fidelity hologram in real time is an urgent ***,we propose a liquid lens based holographic camera for real 3D scene hologram acquisition using an end-to-end physical model-driven network(EEPMD-Net).As the core component of the liquid camera,the first 10 mm large aperture electrowetting-based liquid lens is proposed by using specially fabricated *** design of the liquid camera ensures that the multi-layers of the real 3D scene can be obtained quickly and with great imaging *** EEPMD-Net takes the information of real 3D scene as the input,and uses two new structures of encoder and decoder networks to realize low-noise phase *** comparing the intensity information between the reconstructed image after depth fusion and the target scene,the composite loss function is constructed for phase optimization,and the high-fidelity training of hologram with true depth of the 3D scene is realized for the first *** holographic camera achieves the high-fidelity and fast generation of the hologram of the real 3D scene,and the reconstructed experiment proves that the holographic image has the advantage of low *** proposed holographic camera is unique and can be used in 3D display,measurement,encryption and other fields.

关键词： calculation solution holographic

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