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Bipolar alternate mark inversion encoding (BAMI) scheme for performance signature of optical transceiver systems under thermal effects

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Journal of Optical Communications 2024年第0期45卷 s1511-s1524页

作者： Rashed, Ahmed Nabih Zaki Kumar, Manoharan Ranjith Pugazhenthi, Revathi Prabu, Ramachandran Thandaiah Ahammad, Shaik Hasane Hossain, Md. Amzad Electronics and Electrical Communications Engineering Department Menoufia University Faculty of Electronic Engineering Menouf32951 Egypt Department of Mathematics Amrita School of Engineering Amrita Vishwa Vidyapeetham Chennai India Department of Computer Science and Engineering C. Abdul Hakeem College of Engineering and Technology Melvisharam Vellore India Department of ECE Saveetha School of Engineering SIMATS Chennai India Department of ECE Koneru Lakshmaiah Education Foundation Andhra Pradesh Vaddeswaram522302 India Institute of Theoretical Electrical Engineering Faculty of Electrical Engineering and Information Technology Ruhr University Bochum Bochum44801 Germany Department of Electrical and Electronic Engineering Jashore University of Science and Technology Jashore7408 Bangladesh

This study has clarified the bipolar alternate mark inversion encoding scheme for performance signature of optical transceiver systems under thermal effects. The light power through optical fiber channel variations with spectral wavelength at various temperature variations are clarified. The total electrical power through PIN receiver at various temperature variations are demonstrated. The electrical power amplitude, max Q Factor and min BER through PIN receiver at different temperature variations are clarified in details. Electrical and optical signal per noise ratio with laser bias current at various ambient temperatures are demonstrated. The total optical/electrical power and maximum quality signal with laser bias current at various temperature variations. © 2023 Walter de Gruyter GmbH, Berlin/Boston.

关键词： Single mode fibers

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Intelligent Reflecting Surface Enabled Sensing: Cramér-Rao Lower Bound optimization

Intelligent Reflecting Surface Enabled Sensing: Cramér-Rao ...

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2022 IEEE GLOBECOM Workshops, GC Wkshps 2022

作者： Song, Xianxin Xu, Jie Liu, Fan Han, Tony Xiao Eldar, Yonina C. School of Science and Engineering Future Network of Intelligence Institute Guangdong Provincial Key Laboratory of Future Networks of Intelligence China Southern University of Science and Technology Department of Electrical and Electronic Engineering China Wireless Technology Lab 2012 Laboratories Huawei China Weizmann Institute of Science Faculty of Mathematics and Computer Science Israel

ISBN: (纸本)9781665459754

This paper investigates intelligent reflecting surface (IRS) enabled non-line-of-sight (NLoS) wireless sensing, in which an IRS is deployed to assist an access point (AP) to sense a target in its NLoS region. It is assumed that the AP is equipped with multiple antennas and the IRS is equipped with a uniform linear array. The AP aims to estimate the target's direction-of-arrival (DoA) with respect to the IRS, based on the echo signals from the AP-IRS-target-IRS-AP link. Under this setup, we jointly design the transmit beamforming at the AP and the reflective beamforming at the IRS to minimize the CramérRao lower bound (CRLB) on estimation error. Towards this end, we first obtain the CRLB expression for estimating the DoA in closed form. Next, we optimize the joint beamforming design to minimize the CRLB, via alternating optimization, semi-definite relaxation, and successive convex approximation. Numerical results show that the proposed design based on CRLB minimization achieves improved sensing performance in terms of mean squared error, as compared to the traditional schemes with signal-to-noise ratio maximization and separate beamforming. © 2022 IEEE.

关键词： Beamforming

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Experimental demonstration of a flexible-grid 1×(2×3)mode-and wavelength-selective switch using silicon microring resonators and counter-tapered couplers

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Chinese Optics Letters 2024年第1期22卷 52-58页

作者：孔德军鲁昊汪鹏君符强戴世勋陈伟伟王栎沣张波豪马凌霄李军戴庭舸杨建义 Faculty of Electrical Engineering and Computer Science Ningbo UniversityNingbo 315211China College of Electrical and Electronic Engineering Wenzhou UniversityWenzhou 325035China College of Science and Technology Ningbo UniversityNingbo 315300China Laboratory of Infrared Materials and Devices The Research Institute of Advanced TechnologiesNingbo UniversityNingbo 315211China Department of Information Science and Electronics Engineering and Cyrus Tang Center for Sensor Materials and Applications Zhejiang UniversityHangzhou 310027China

A flexible-grid 1×(2×3)mode-and wavelength-selective switch which comprises counter-tapered couplers and silicon microring resonators has been proposed,optimized,and demonstrated experimentally in this *** carefully thermally tuning phase shifters and silicon microring resonators,mode and wavelength signals can be independently and flexibly conveyed to any one of the output ports,and different bandwidths can be generated as *** particle swarm optimization algorithm and finite difference time-domain method are employed to optimize structural parameters of the twomode(de)multiplexer and crossing *** bandwidth-tunable wavelength-selective optical router composed of12 microring resonators is studied by taking advantage of the transfer matrix *** results show that,for the fabricated module,cross talk less than-10.18 dB,an extinction ratio larger than 17.41 d B,an in-band ripple lower than0.79 dB,and a 3-dB bandwidth changing from 0.38 to 1.05 nm are obtained,as the wavelength-channel spacing is 0.40 *** corresponding response time is measured to be 13.64μs.

关键词： integrated optics optical waveguide mode-and wavelength-selective switch

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Security & Privacy Issues in IoT Using Blockchain and ML 7

Security & Privacy Issues in IoT Using Blockchain and ML

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7th International Conference on Image Information Processing, ICIIP 2023

作者： Muhammad, Muna Sajid, Ahthasham Chhabra, Gunjan Taherdoost, Hamed Khan, Inam Ullah Kaushik, Keshav Balochistan University of Information Technology Engineering And Management Sciences Balochistan Pakistan Capital University of Science And Technology Faculty of Computing Islamabad Pakistan Graphic Era Hill University Department of Cse Uttarakhand Dehradun India University Canada West Q Minded | Quark Minded Tehnology Inc. Vancouver Canada Department of Electronic Engineering Islamabad Campus Pakistan University of Petroleum And Energy Studies School of Computer Science Dehradun India

ISBN: (纸本)9798350371406

As Internet of Things (IoT) devices are being involved in abundant applications, security, and privacy of the IoT users have been of more concern. The security threats are rapidly growing making the solutions of security and privacy not inadequate. Thereby, each thing on the internet can be a point of target for hackers. Accordingly, ML algorithms are utilized for producing accurate outputs by using large and complex databases in which the produced outputs could be used in the prediction and detection of weaknesses in IoT systems. Additionally, BC methods are also being used for providing security and privacy solutions in IoT networks. Many existing studies have been carried out on BC techniques or ML algorithms or both. Though, these existing studies focus on either providing privacy or security issues by using BC techniques or ML algorithms, therefore, give rise to need for aa combined survey on solutions made recently which address both privacy and security issues by using BC techniques and ML algorithms. In this paper, we give a summarized survey of research works that happened in the last four years by addressing privacy and security issues by using BC techniques and ML algorithms in IoT networks. Different literatures have been categorized on privacy and security of BC techniques and ML algorithms in IoT. Then at last, some research challenges and future works are highlighted by using BC techniques and ML algorithms for addressing security and privacy issues in IoT networks. © 2023 IEEE.

关键词： Blockchain

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Non-contact Breathing Patterns Recognition with FMCW Radar by Processing Temporal Information using Transformer Network

Non-contact Breathing Patterns Recognition with FMCW Radar b...

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Asia-Pacific Conference on Microwave

作者： Cries Avian Jenq-Shiou Leu Erfansyah Ali Nur Achmad Sulistyo Putro Hang Song Jun-Ichi Takada Setya Widyawan Prakosa Ariana Tulus Purnomo Department of Electronic and Computer Engineering National Taiwan University of Science and Technology Taipei Taiwan School of Electrical Engineering Telkom University Bandung Indonesia Department of Computer Science and Electronics Faculty of Mathematics and Natural Sciences Universitas Gadjah Mada Yogyakarta Indonesia Department of Transdisciplinary Science and Engineering Tokyo Insitute of Technology Tokyo Japan Faculty of Engineering and Technology Sampoerna University Jakarta Indonesia

This paper proposed non-contact monitoring by classifying breathing patterns using a frequency-modulated continuous wave (FMCW) radar sensor. First, the data were from the subject to conducting breathing pattern: normal, quick, hold, deep, deep quick. Second, we extract the breath wave patterns by employing several block preprocessing and extracting its temporal information that was not investigated by our previous work. Then, to distinguish those five breath wave conditions, the designated Transformer architecture is proposed. Finally, we compared our previous work and demonstrated that our model could enhance accuracy and attained 98.6% of F1-Scores.

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Perovskite materials for highly efficient Photo(electro)catalytic water splitting: A mini-review

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Nano Materials Science 2024年

作者： Li, Shuoren Wu, Hao Yan, Chang Guangdong Guangzhou511400 China Faculty of Innovation Engineering Macau University of Science and Technology Taipa999078 China Guangdong-Hong Kong Joint Laboratory for Carbon Neutrality Jiangmen Laboratory of Carbon Science and Technology Guangdong Province Jiangmen529199 China Department of Electronic and Computer Engineering The Hong Kong University of Science and Technology 999077 Hong Kong

Sustainable and clean hydrogen development has been considered a mainstream trend in contemporary energy research. Heterogenous photo(electro)catalysis is a promising approach to producing hydrogen in an environmentally friendly manner. Perovskites have emerged as an inexpensive, earth-abundant, and easily fabricated semiconductor material for photo(electro)catalysis. However, some of their shortcomings have limited the wide range of applications. In this mini-review, we present the fundamentals and applications of various perovskites for photo(electro)catalytic water splitting. In addition, we summarize advanced strategies for photo(electro)catalytic water splitting based on perovskites, focusing on the following approaches: intrinsic modulation of perovskites, functionalization of perovskites, and design of perovskite tandem systems. In summary, we point out the challenges and potential applications for perovskite solar water splitting and systematically describe various strategies to improve the photo(electro)catalysis performance of perovskites, illustrating the potential of using perovskites as key materials for solar water splitting. © 2024 Chongqing University

关键词： Perovskite

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Secrecy Analysis for MISO Broadcast Systems with Regularized Zero-Forcing Precoding

arXiv

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arXiv 2023年

作者： Zhang, Xin Song, Shenghui Eldar, Yonina C. The Department of Electronic and Computer Engineering The Hong Kong University of Science and Technology Hong Kong The Faculty of Math and CS Weizmann Institute of Science Rehovot7610001 Israel

As an effective way to enhance the physical layer security (PLS) for the broadcast channel (BC), regularized zero-forcing (RZF) precoding has attracted much attention. However, the reliability performance, i.e., secrecy outage probability (SOP), of RZF is not well investigated in the literature. In this paper, we characterize the secrecy performance of RZF precoding in the large multiple-input single-output (MISO) broadcast system. For this purpose, we first consider a central limit theorem (CLT) for the joint distribution of the users’ signal-to-interference-plus-noise ratio (SINR) and the eavesdropper’s (Eve’s) signal-to-noise ratio (ESNR) by leveraging random matrix theory (RMT). The result is then utilized to obtain a closed-form approximation for the ergodic secrecy rate (ESR) and SOP of three typical scenarios: the case with only external Eves, the case with only internal Eves, and that with both. The derived results are then used to evaluate the percentage of users in secrecy outage and the required number of transmit antennas to achieve a positive secrecy rate. It is shown that, with equally-capable Eves, the secrecy loss caused by external Eves is higher than that caused by internal Eves. Numerical simulations validate the accuracy of the theoretical results. Copyright © 2023, The Authors. All rights reserved.

关键词： Signal to noise ratio

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An Enhanced Haar Cascade Face Detection Schema for Gender Recognition

An Enhanced Haar Cascade Face Detection Schema for Gender Re...

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2023 International Conference on Smart Computing and Application, ICSCA 2023

作者： Sridhar, Psvs Chithaluru, Premkumar Kumar, Sunil Cheikhrouhou, Omar Hamam, Habib Computer Science and Engineering Andhra Pradesh Vaddeswaram India Department of Computer Science and Engineering Hyderabad India School of Computer Science University of Petroleum and Energy Studies Dehradun India National School of Engineers of Sfax University of Sfax Ces Laboratory Sfax3038 Tunisia University de Moncton Faculty of Engineering MonctonNBE1A3E9 Canada International Institute of Technology and Management Commune d'Akanda Libreville Gabon School of Electrical Engineering University of Johannesburg Department of Electrical and Electronic Engineering Science Johannesburg2006 South Africa Spectrum of Knowledge Production and Skills Development Sfax Tunisia

ISBN: (纸本)9798350347050

Gender identification software is becoming increasingly popular in the age of machine-to-machine interactions, as the need for person-aligned, effective, and ethical systems become more apparent. In this age of machine-to-machine interactions, automated gender identification software is becoming more popular. The bulk of the systems for gender identification that were examined used either textual or audiovisual data as input to determine their gender. Many different approaches to automatically detect gender based on traits gathered from people's bodies and/or behaviors have been suggested, and there are simply too many to include here. The accuracy of automated gender identification, on the other hand, has always been a topic of worry or a source of criticism. Initial face identification is accomplished by the use of the Haar Cascade face detection method, which is based on the Viola-J ones face recognition algorithm. Facial characteristics such as the eyes, mouth, and nose are then identified. Second, using the Viola-Jones face detection algorithm, the faces and facial characteristics such as the eyes, mouth, and nose are recognized, and the results are shown. In order to increase the accuracy of gender identification, adaptive filters are employed to reduce the amount of noise present before the detection process is carried out. The facial qualities that have been gathered are utilized as input or test data for the neural network, which is subsequently trained on these characteristics. It is intended that the neural network acquires the features of the genders and then functions as a classifier when it comes to detecting them. Instead of saying it another way, a neural network known as Keras is used for feature extraction and gender identification, which is free and open-source software. © 2023 IEEE.

关键词： Feature extraction

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Improved Human Detection Algorithm by Indoor W-Band FMCW RADAR using K-means Technique 9

Improved Human Detection Algorithm by Indoor W-Band FMCW RAD...

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9th International Electrical engineering Congress, iEECON 2021

作者： Worasutr, Aman Worasawate, Denchai Pongthavornkamol, Tiwat Fukawa, Kazuhiko Kasetsart University Faculty of Engineering Department of Electrical Engineering Bangkok Thailand National Electronic and Computer Technology Center Location and Automatic Identification System Research Team Pathum Thani Thailand Tokyo Institute of Technology Department of Communications and Computer Engineering Tokyo Japan

ISBN: (纸本)9781728195841

This paper proposes the improved indoor human detection algorithm from data provided by W-Band FMCW radar by using k-mean technique. The data provided by the radar contain both humans and nun-human objects. To identify non-human objects, the obtained data are filtered by the velocity and RCS of the detected objects. The K-means algorithm is applied to the filtered dataset to estimate the positions of humans. The estimated positions of humans are much closed to the actual ones. © 2021 IEEE.

关键词： K-means clustering

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Robust Three-Dimensional Near-Field Source Localization Method Based on Deep Feature Fusion Extraction Network

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IEEE Transactions on Cognitive Communications and Networking 2025年

作者： Chen, Hua Zhang, Wanjun Teng, Liping Liu, Wei Yang, Songjie Yuen, Chau Ningbo University Faculty of Electrical Engineering and Computer Science Ningbo315211 China Nantong University School of Information Science and Technology Nantong226019 China The Hong Kong Polytechnic University Department of Electrical and Electronic Engineering Hong Kong Hong Kong University of Electronic Science and Technology of China National Key Laboratory of Wireless Communications Chengdu610054 China Nanyang Technological University School of Electrical and Electronics Engineering Singapore639798 Singapore

A deep learning (DL) based approach for near-field (NF) source localization is introduced to enhance the accuracy and robustness in both direction of arrival (DOA) and range estimation. The received data is first preprocessed by leveraging temporal and spatial correlation of the incident signals and symmetry of the employed cross array. This preprocessing step achieves parameter decoupling, reduces mutual interference between different features and simplifies the model training process. Next, a feature fusion extraction network (FFEN) is proposed, which mainly consists of a feature fusion network (FFN) and a feature extraction network (FEN). Adopting a multiple-input-multiple-output (MIMO) model structure, FFEN transforms the NF parameter estimation problem into a multi-task learning problem. The network adopts a dual-branch strategy for processing input data, which enables the extraction and learning of diverse parameter features from the data stream, thereby acquiring comprehensive information of all parameters of interest. Utilizing residual connections and introducing attention mechanisms allows the network to focus on important features within the input data, avoiding issues like gradient vanishing and network degradation, and subsequently, the three branches output labels for different parameters separately. This design ensures the network's efficiency and accuracy when dealing with complex multi-task learning problems. Experimental results demonstrate that the proposed method achieves high-precision parameter estimation with good generalization capabilities, and it also outperforms traditional model-driven approaches. © 2015 IEEE.

关键词： Multi-task learning

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