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Noise-like pulse generation in erbium-doped fiber laser by hybrid mode-locking of graded index multimode fiber and nonlinear optical loop mirror

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Optical Fiber Technology 2025年 93卷

作者： Hikmat Maad Norita Mohd Yusoff Siti Barirah Ahmad Anas Makhfudzah Mokhtar Mohd Adzir Mahdi Zuraidah Zan Wireless and Photonics Networks Research Center of Excellence Department of Computer and Communication Systems Engineering Faculty of Engineering Universiti Putra Malaysia 43400 UPM Serdang Selangor Malaysia Institute of Nanoscience and Nanotechnology (ION2) Universiti Putra Malaysia 43400 Serdang Selangor Malaysia

The practical implementation of graded-index multimode fiber (GIMF) as a saturable absorber (SA) in mode-locked fiber lasers is limited by the requirement for extremely short fiber lengths, making its reproducibility and investigation difficult. In this work, we demonstrate stable noise-like pulse (NLP) generation using a hybrid mode-locked fiber laser that integrates a nonlinear optical loop mirror (NOLM) with a 32 m GIMF segment. Nonlinear multimode interference (NL-MMI) and nonlinear phase accumulation within the NOLM bidirectional-loop (bi-loop) were leveraged to enhance the saturable absorption characteristics. Comprehensive measurements comparing the nonlinear transmission behavior of GIMF alone and NOLM-GIMF structures confirmed a substantial improvement in modulation depth. NLP generation was systematically investigated across GIMF lengths from 30 m to 62.5 m, with optimal performance observed at 32 m, yielding a 3-dB bandwidth of 22.38 nm, spike width of 153.9 fs, and pedestal width of 61.73 ps. The obtained pulse is significantly shorter than previously reported NLP, which is typically reported in the nanosecond range for the 1.5 µm regime. Long-term stability testing over 300 min showed minimal spectral and temporal fluctuations, confirming robust operation. The proposed NOLM-GIMF design successfully overcomes the short-length constraint of GIMF-based SAs, offering a scalable and reliable solution for high-energy, broadband NLP fiber lasers in the 1.5 µm regime. This work advances mode-locked fiber laser technology by improving stability and scalability for ultrafast photonics applications.

关键词： Hybrid mode-locked fiber laser Erbium-doped fiber Nonlinear optical loop mirror Figure-of-eight Nonlinear multimode interference Graded index multimode fiber and noise-like pulse

Effect of Coulomb carrier drag and terahertz plasma instability in p+-p-i-n-n+ graphene tunneling transistor structures

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arXiv 2021年

作者： Ryzhii, V. Ryzhii, M. Satou, A. Otsuji, T. Mitin, V. Shur, M.S. Research Institute of Electrical Communication Tohoku University Sendai980-8577 Japan Institute of Ultra High Frequency Semiconductor Electronics of RAS Moscow117105 Russia Department of Computer Science and Engineering University of Aizu Aizu-Wakamatsu965-8580 Japan Department of Electrical Engineering University at Buffalo SUNY BuffaloNY14260 United States Department of Electrical Computer and Systems Engineering Rensselaer Polytechnic Institute TroyNY12180 United States

We evaluate the influence of the Coulomb drag of the electrons and holes in the gated n- and p-regions by the ballistic electrons and holes generated in the depleted i-region due to the interband tunneling on the current-voltage characteristics and impedance of the p+-p-i-n-n+ graphene tunneling transistor structures (GTTSs). The drag leads to a current amplification in the gated n- and p-regions and a positive feedback between the amplified dragged current and the injected tunneling current. A sufficiently strong drag can result in the negative real part of the GTTS impedance enabling the plasma instability and the self-excitation of the plasma oscillations in the terahertz (THz) frequency range. This effect might be used for the generation of the THz radiation. © 2021, CC BY.

关键词： Graphene

A new non-negative matrix co-factorisation approach for noisy neonatal chest sound separation

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arXiv 2021年

作者： Grooby, Ethan He, Jinyuan Fattahi, Davood Zhou, Lindsay King, Arrabella Ramanathan, Ashwin Malhotra, Atul Dumont, Guy A. Marzbanrad, Faezeh Department of Electrical and Computer Systems Engineering Monash University MelbourneVIC Australia Monash Newborn Monash Children's Hospital and Department of Paediatrics Monash University Melbourne Australia Department of Electrical and Computer Engineering University British Columbia VancouverBC Canada Children's Hospital Research Institute VancouverBC Canada

Obtaining high quality heart and lung sounds enables clinicians to accurately assess a newborns cardiorespiratory health and provide timely care. However, noisy chest sound recordings are common, hindering timely and accurate assessment. A new Non-negative Matrix Co-Factorisation based approach is proposed to separate noisy chest sound recordings into heart, lung and noise components to address this problem. This method is achieved through training with 20 high quality heart and lung sounds, in parallel with separating the sounds of the noisy recording. The method was tested on 68 10-second noisy recordings containing both heart and lung sounds and compared to the current state of the art Non-negative Matrix Factorisation methods. Results show significant improvements in heart and lung sound quality scores respectively, and improved accuracy of 3.6bpm and 1.2bpm in heart and breathing rate estimation respectively, when compared to existing methods. Copyright © 2021, The Authors. All rights reserved.

关键词： Heart

Graph based Cooperative Localization for Connected and Semi-Autonomous Vehicles

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Graph based Cooperative Localization for Connected and Semi-...

IEEE International Workshop on computer-Aided Modeling, Analysis, and Design of Communication Links and Networks, CAMAD

作者： Nikos Piperigkos Aris S. Lalos Kostas Berberidis Computer Engineering & Informatics Department University of Patras Greece Industrial Systems Institute Athena Research Center Patras Greece

ISBN: (数字)9781728163390

ISBN: (纸本)9781728163406

Cooperative Real-time Localization is expected to play a crucial role in various applications in the field of Connected and Semi-Autonomous vehicles (CAVs), such as collision avoidance/warning, cooperative adaptive cruise control, etc. Future 5G wireless systems are expected to enable cost-effective Vehicle-to-Everything (V2X) systems, allowing CAVs to share the measured data with other entities of the network. Typical measurement models usually deployed for this problem, are absolute position from Global Positioning System (GPS), relative distance to neighboring vehicles and relative angle or azimuth angle, extracted from Light Detection and Ranging (LIDAR) or Radio Detection and Ranging (RADAR) sensors. In this paper, we provide a cooperative localization approach that performs multi modal-fusion between the interconnected vehicles, by representing a fleet of connected cars as an undirected graph, encoding each vehicle position relative to its neighboring vehicles. This method is based on the so called Laplacian Processing, a Graph Signal Processing tool, that allows to capture intrinsic geometry of the undirected graph of vehicles rather than their absolute position on global coordinate system, significantly outperforming current state of the art approaches, in terms of localization mean square and maximum absolute error and computational complexity.

关键词： Position measurement Global Positioning System Laplace equations Vehicular ad hoc networks Atmospheric measurements Particle measurements Fuses

Adaptive Memory Networks with Self-supervised Learning for Unsupervised Anomaly Detection

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arXiv 2022年

作者： Zhang, Yuxin Wang, Jindong Chen, Yiqiang Yu, Han Qin, Tao Global Energy Interconnection Development and Cooperation Organization Xicheng District Beijing China Beijing Key Laboratory of Mobile Computing and Pervasive Device Institute of Computing Technology Chinese Academy of Sciences Beijing China University of Chinese Academy of Sciences Beijing China Microsoft Research Beijing China The School of Computer Science and Engineering Nanyang Technological University Singapore Singapore

Unsupervised anomaly detection aims to build models to effectively detect unseen anomalies by only training on the normal data. Although previous reconstruction-based methods have made fruitful progress, their generalization ability is limited due to two critical challenges. First, the training dataset only contains normal patterns, which limits the model generalization ability. Second, the feature representations learned by existing models often lack representativeness which hampers the ability to preserve the diversity of normal patterns. In this paper, we propose a novel approach called Adaptive Memory Network with Self-supervised Learning (AMSL) to address these challenges and enhance the generalization ability in unsupervised anomaly detection. Based on the convolutional autoencoder structure, AMSL incorporates a self-supervised learning module to learn general normal patterns and an adaptive memory fusion module to learn rich feature representations. Experiments on four public multivariate time series datasets demonstrate that AMSL significantly improves the performance compared to other state-of-the-art methods. Specifically, on the largest CAP sleep stage detection dataset with 900 million samples, AMSL outperforms the second-best baseline by 4%+ in both accuracy and F1 score. Apart from the enhanced generalization ability, AMSL is also more robust against input noise. © 2022, CC BY.

关键词： Time series

S-shaped current-voltage characteristics of n+-i-n-n+ graphene field-effect transistors due to the Coulomb drag of quasi-equilibrium electrons by ballistic electrons

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arXiv 2021年

We demonstrate that the injection of the ballistic electrons into the two-dimensional electron plasma in lateral n+-i-n-n+ graphene field-effect transistors (G-FET) might lead to a substantial Coulomb drag of the quasi-equilibrium electrons due the violation of the Galilean and Lorentz invariance in the systems with a linear electron dispersion. This effect can result in the S-shaped current-voltage characteristics (IVs). The resulting negative differential conductivity enables the hysteresis effects and current filamentation that can be used for the implementation of voltage switching devices. Due to a strong nonlinearity of the IVs, the G-FETs can be used for an effective frequency multiplication and detection of terahertz radiation. © 2021, CC BY.

关键词： Electrons

SNE-RoadSeg+: Rethinking depth-normal translation and deep supervision for freespace detection

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arXiv 2021年

作者： Wang, Hengli Fan, Rui Cai, Peide Liu, Ming The Department of Electronic and Computer Engineering The Hong Kong University of Science and Technology Clear Water Bay Kowloon Hong Kong The College of Electronic and Information Engineering Tongji University Shanghai201804 China Shanghai Research Institute for Intelligent Autonomous Systems Shanghai201210 China

Freespace detection is a fundamental component of autonomous driving perception. Recently, deep convolutional neural networks (DCNNs) have achieved impressive performance for this task. In particular, SNE-RoadSeg, our previously proposed method based on a surface normal estimator (SNE) and a data-fusion DCNN (RoadSeg), has achieved impressive performance in freespace detection. However, SNE-RoadSeg is computationally intensive, and it is difficult to execute in real time. To address this problem, we introduce SNE-RoadSeg+, an upgraded version of SNE-RoadSeg. SNE-RoadSeg+ consists of 1) SNE+, a module for more accurate surface normal estimation, and 2) RoadSeg+, a data-fusion DCNN that can greatly minimize the trade-off between accuracy and efficiency with the use of deep supervision. Extensive experimental results have demonstrated the effectiveness of our SNE+ for surface normal estimation and the superior performance of our SNE-RoadSeg+ over all other freespace detection approaches. Specifically, our SNE-RoadSeg+ runs in real time, and meanwhile, achieves the state-of-the-art performance on the KITTI road benchmark. Our project page is at https://***/ sne-roadseg-plus. Copyright © 2021, The Authors. All rights reserved.

关键词： Deep neural networks

An integrated decision support framework for exploring the barriers and potential application scenarios in metaverse hospitality

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Journal of Industrial Information Integration 2025年 45卷

作者： Wu, Qun Tan, Weiqi Zhou, Ligang Deveci, Muhammet Pamucar, Dragan Pedrycz, Witold School of Mathematical Sciences Anhui University Hefei230601 China Anhui University Center for Applied Mathematics Anhui University Hefei Anhui230601 China Department of Industrial Engineering Turkish Naval Academy National Defence University Istanbul34942 Tuzla Turkey Royal School of Mines Imperial College London LondonSW7 2AZ United Kingdom Department of Information Technologies Western Caspian University Baku1001 Azerbaijan Faculty of Organizational Sciences University of Belgrade Belgrade11000 Serbia Department of Electrical and Computer Engineering University of Alberta Edmonton ABT6G 2R3 Canada Systems Research Institute Polish Academy of Sciences Warsaw00-901 Poland

The global hospitality industry is undergoing a profound transformation, primarily driven by the internet era within the context of Industry 4.0 and the continuous evolution of the metaverse. The metaverse offers limitless possibilities for creating immersive and personalized accommodation experiences by closely integrating the virtual with the real world. It also provides a new perspective and mindset for guiding the hospitality industry to rethink and redesign service models and business processes. Although the metaverse application in the hospitality industry has already made significant progress, this process still faces numerous barriers, and the specific application scenarios of the metaverse hospitality industry (MHI) remain unclear. This study aims to develop an integrated decision support framework for exploring the barriers and potential application scenarios in metaverse hospitality. First, the interval type-2 fuzzy sets (IT2FSs) is introduced to quantify the complex and uncertain information in the decision-making procedure. Second, the IT2F-BWM with the IT2F weighted averaging (IT2FWA) operator is proposed to calculate the barriers’ weights considering the group opinions. Third, the IT2FWA operator and IT2F-ExpTODIM method are incorporated to prioritize the potential application scenarios in MHI. Finally, a case study on the prioritization of barriers and application scenarios in MHI is utilized to test the effectiveness and practicality of the presented framework. Results show that the technology barrier (0.5217) and the interaction technology (0.2483) have the highest levels among the main and sub-main barrier hierarchies, respectively. The findings of this article may enrich the theories of uncertain decision-making methods and provide instructive suggestions for the operation and management of metaverse hospitality practice. © 2025 Elsevier Inc.

关键词： IT2F-BWM IT2F-ExpTODIM Metaverse hospitality Multi-criteria decision-making

Trust-aware service function chain embedding: A path-based approach

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arXiv 2020年

作者： Torkzaban, Nariman Baras, John S. Department of Electrical and Computer Engineering Institute for Systems Research University of Maryland College ParkMD20742 United States

With the emergence of network function virtualization (NFV), and software-defined networking (SDN), the realization and implementation of service function chains (SFCs) have become much easier. An SFC is an ordered set of interconnected virtual network functions (VNFs). NFV allows for decoupling the network functions from proprietary hardware realizing a software-based implementation of VNFs on commodity hardware, and SDN decouples the network control from its forwarding logic allowing for a more flexible and programmable traffic routing among the VNFs. The SFC embedding problem (i.e. placement of SFCs on a shared substrate and establishing the corresponding traffic routes between the VNFs), has been extensively studied in the literature. In this paper, we extend a previous work on trust-aware service chain embedding with generalizing the role of trust by incorporating the trustworthiness of the service network links and substrate network paths into the SFC embedding decision process. We first introduce and formulate the path-based trust-aware service chain embedding problem as a mixed integer-linear program (MILP), and then provide an approximate model based on selecting k− shortest candidate substrate paths for hosting each virtual link, to reduce the complexity of the model. We validate the performance of our methods through simulations and conduct a discussion on evaluating the methods and some operation trade-offs. Copyright © 2020, The Authors. All rights reserved.

关键词： Network function virtualization