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Survey of Spectral Amplitude Coding Optical Code Division Multiple Access Families

Journal of Lightwave technology 2025年

作者： Ullah, Rahat Ullah, Sibghat Ali, Aitizaz Jianxin, Ren Alwageed, Hathal Salamah Yaya, Mao Qi, Zhipeng Yu, Yongyi Imtiaz, Waqas A. Khan, Maqbool School of Physics and Optoelectronics Nanjing University of Information Science and Technology China Jiangsu Key Laboratory for Optoelectronic Detection of Atmosphere and Ocean Nanjing University of Information Science Technology Nanjing210044 China Jiangsu International Joint Laboratory on Meteorological Photonics and Optoelectronic Detection Nanjing University of Information Science Technology Nanjing210044 China School of Electronics Science and Technology Southeast University China School of Technology NSF Group Asia Pacific University Malaysia Saudi Arabia College of Computer Science Jouf University Saudi Arabia Electrical Engineering Department University of Engineering and Technology Peshawar Pakistan Pak-Austra Fachhochschule Haripur Pakistan

Quest for high capacity communication have led the research community to explore a plethora of technologies. Among these, optical code division multiple access (OCDMA) technique stands tall with support for high data rate connectivity in terms of data, reach and the number of subscribers. The development of OCDMA based networks started with the design and implementation of one dimensional (1D) codes, which provides effective correlation properties to reduce the effect of interference due to multiple users (MAI) and phase-induced-intensity-noise (PIIN) in order to provide the required system capacity. Several families of codes have been developed to determine the most suitable combination between code length, weight against the auto- and cross-correlation property respectively. This survey paper will analyze the most commonly used families of codes from spectral amplitude coding (SAC) based OCDMA systems names Double Weight (DW) codes, Diagonal codes , zero cross-correlation (ZCC) codes, and hybrid codes in terms of different performance parameters and identify the most suitable combination of code length (L), code weight (w), and cross-correlation (λC) to be utilized for next generation communication applications that can provide high capacity and cardinality. © 1983-2012 IEEE.

关键词： Passive optical networks

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Plasmon-assisted channel-tunable bistable states in a monolayer MoS2 nanoresonator coupled to a metallic nanoshell

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Optics Express 2025年第11期33卷 23568-23578页

作者： Jian-Bo Li Hong-Mei Gong Yu-Xiang Peng Si Xiao Jin-Bo Hu Lin-Wen Long Department of Physics Hunan Province Key Laboratory of Materials Surface & Interface Science and Technology Central South University of Forestry and Technology Changsha 410004 China jbli_opt@*** jbli_opt@*** School of Optical and Electronic Information & Jiangsu/Suzhou Key Laboratory of Biophotonics & International Joint Metacenter for Advanced Photonics and Electronics Suzhou City University Suzhou 215104 China hmgong@*** School of Physics Hunan Key Laboratory of Super microstructure and Ultrafast Process Central South University Changsha 410083 China sixiao@*** College of Materials and Energy Central South University of Forestry and Technology Changsha 410004 China

We study how to obtain the channel-tunable bistable states in a coupled system consisting of a monolayer MoS 2 nanomechanical resonator (NR) and a metallic nanoshell (MNS) beyond the dipole approximation. The MNS is constructed by a metallic core and a dielectric shell. The calculated results show that the linear absorption spectrum exhibits some new features, such as three-phonon resonance, Rayleigh resonance, and ac-Stark resonance. In a strong exciton-plasmon coupling regime, the absorption peak and amplification peak in the absorption spectrum can be greatly enhanced by adjusting the exciton-phonon coupling strength. Especially, we plot the bistability phase diagrams in the system’s parameter space and highlight the strong dependency of the lower (upper) bistable threshold on the pumping intensity, the MNS-NR distance, and the dielectric shell thickness. The ratio of linear absorption in the upper and lower stable states can reach 42. For a given MNS with a fixed shell thickness, it is easy to achieve single-channel or dual-channel bistable states by only adjusting the exciton-phonon coupling strength via modulation of the length of the MoS 2 nanosheet along the NR axis. The findings obtained here are very useful for extensive applications such as optical memory cells and channel-tunable bistable switches.

关键词： Absorption spectroscopy Light propagation Metal nanoparticles Nonlinear absorption Optical properties Slow light

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Rethinking Object Saliency Ranking: A Novel Whole-flow processing Paradigm

arXiv

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arXiv 2023年

作者： Song, Mengke Li, Linfeng Wu, Dunquan Song, Wenfeng Chen, Chenglizhao China University of Petroleum China Shandong Provincial Key Laboratory for Distributed Computer Software Novel Technology China Jiangsu Key Laboratory of Image and Video Understanding for Social Safety China Qingdao University China Beijing Information Science and Technology University China

Existing salient object detection methods are capable of predicting binary maps that highlight visually salient regions. However, these methods are limited in their ability to differentiate the relative importance of multiple objects and the relationships among them, which can lead to errors and reduced accuracy in downstream tasks that depend on the relative importance of multiple objects. To conquer, this paper proposes a new paradigm for saliency ranking, which aims to completely focus on ranking salient objects by their "importance order". While previous works have shown promising performance, they still face ill-posed problems. First, the saliency ranking ground truth (GT) orders generation methods are unreasonable since determining the correct ranking order is not well-defined, resulting in false alarms. Second, training a ranking model remains challenging because most saliency ranking methods follow the multi-task paradigm, leading to conflicts and trade-offs among different tasks. Third, existing regression-based saliency ranking methods are complex for saliency ranking models due to their reliance on instance mask-based saliency ranking orders. These methods require a significant amount of data to perform accurately and can be challenging to implement effectively. To solve these problems, this paper conducts an in-depth analysis of the causes and proposes a whole-flow processing paradigm of saliency ranking task from the perspective of "GT data generation", "network structure design" and "training protocol". The proposed approach outperforms existing state-of-the-art methods on the widely-used SALICON set, as demonstrated by extensive experiments with fair and reasonable comparisons. The saliency ranking task is still in its infancy, and our proposed unified framework can serve as a fundamental strategy to guide future work. The code and data will be available at https://***/MengkeSong/Saliency-Ranking-Paradigm. Copyright © 2023, The Authors. All rig

关键词： Economic and social effects

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A Critical Review of Large Language Model on Software Engineering: An Example from ChatGPT and Automated Program Repair

arXiv

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arXiv 2023年

作者： Zhang, Quanjun Zhang, Tongke Zhai, Juan Fang, Chunrong Yu, Bowen Sun, Weisong Chen, Zhenyu State Key Laboratory for Novel Software Technology Nanjing University Jiangsu Nanjing China Manning College of Information & Computer Sciences University of Massachusetts AmherstMA United States

Large Language Models (LLMs) have been gaining increasing attention and demonstrated promising performance across a variety of Software Engineering (SE) tasks, such as Automated Program Repair (APR), code summarization, and code completion. For example, ChatGPT, the latest black-box LLM, has been investigated by numerous recent research studies and has shown impressive performance in various tasks. However, there exists a potential risk of data leakage since these LLMs are usually close-sourced with unknown specific training details, e.g., pre-training datasets. In this paper, we seek to review the bug-fixing capabilities of ChatGPT on a clean APR benchmark with different research objectives. We first introduce EvalGPTFix, a new benchmark with buggy and the corresponding fixed programs from competitive programming problems starting from 2023, after the training cutoff point of ChatGPT. The results on EvalGPTFix show that ChatGPT is able to fix 109 out of 151 buggy programs using the basic prompt within 35 independent rounds, outperforming state-of-the-art LLMs CodeT5 and PLBART by 27.5% and 62.4% prediction accuracy. We also investigate the impact of three types of prompts, i.e., problem description, error feedback, and bug localization, leading to additional 34 fixed bugs. Besides, we provide additional discussion from the interactive nature of ChatGPT to illustrate the capacity of a dialog-based repair workflow with 9 additional fixed bugs. Overall, our experiments demonstrate that ChatGPT is able to fix a total of 143 bugs in EvalGPTFix, indicating the potential of ChatGPT in repairing real-world buggy programs. Inspired by the findings, we further pinpoint various challenges and opportunities for advanced SE study equipped with such LLMs (e.g., ChatGPT) in the near future. More importantly, our work calls for more research on the reevaluation of the achievements obtained by existing black-box LLMs across various SE tasks, not limited to ChatGPT on APR. © 2023, C

关键词： Repair

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3DSS-Mamba: 3D-Spectral-Spatial Mamba for Hyperspectral Image Classification

arXiv

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arXiv 2024年

作者： He, Yan Tu, Bing Liu, Bo Li, Jun Plaza, Antonio The Institute of Optics and Electronics The Jiangsu Key Laboratory for Optoelectronic Detection of Atmosphere and Ocean The Jiangsu International Joint Laboratory on Meteorological Photonics and Optoelectronic Detection Nanjing University of Information Science and Technology Jiangsu Nanjing210044 China The Faculty of Computer Science China University of Geosciences Wuhan430074 China The Hyperspectral Computing Laboratory Department of Technology of Computers and Communications Escuela Politecnica University of Extremadura C¨ceres 10003 Spain

Hyperspectral image (HSI) classification constitutes the fundamental research in remote sensing fields. Convolutional Neural Networks (CNNs) and Transformers have demonstrated impressive capability in capturing spectral-spatial contextual dependencies. However, these architectures suffer from limited receptive fields and quadratic computational complexity, respectively. Fortunately, recent Mamba architectures built upon the State Space Model integrate the advantages of long-range sequence modeling and linear computational efficiency, exhibiting substantial potential in low-dimensional scenarios. Motivated by this, we propose a novel 3D-Spectral-Spatial Mamba (3DSS-Mamba) framework for HSI classification, allowing for global spectral-spatial relationship modeling with greater computational efficiency. Technically, a spectral-spatial token generation (SSTG) module is designed to convert the HSI cube into a set of 3D spectral-spatial tokens. To overcome the limitations of traditional Mamba, which is confined to modeling causal sequences and inadaptable to high-dimensional scenarios, a 3D-Spectral-Spatial Selective Scanning (3DSS) mechanism is introduced, which performs pixel-wise selective scanning on 3D hyperspectral tokens along the spectral and spatial dimensions. Five scanning routes are constructed to investigate the impact of dimension prioritization. The 3DSS scanning mechanism combined with conventional mapping operations forms the 3D-spectral-spatial mamba block (3DMB), enabling the extraction of global spectral-spatial semantic representations. Experimental results and analysis demonstrate that the proposed method outperforms the state-of-the-art methods on HSI classification benchmarks. Copyright © 2024, The Authors. All rights reserved.

关键词： Hyperspectral imaging

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IGroupSS-Mamba: Interval Group Spatial-Spectral Mamba for Hyperspectral Image Classification

arXiv

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arXiv 2024年

作者： He, Yan Tu, Bing Jiang, Puzhao Liu, Bo Li, Jun Plaza, Antonio The Institute of Optics and Electronics The Jiangsu Key Laboratory for Optoelectronic Detection of Atmosphere and Ocean The Jiangsu International Joint Laboratory on Meteorological Photonics and Optoelectronic Detection Nanjing University of Information Science and Technology Jiangsu Nanjing210044 China The Faculty of Computer Science China University of Geosciences Wuhan430074 China The Hyperspectral Computing Laboratory Department of Technology of Computers and Communications Escuela Politecnica University of Extremadura Cáceres‎10003 Spain

Hyperspectral image (HSI) classification has garnered substantial attention in remote sensing fields. Recent Mamba architectures built upon the Selective State Space Models (S6) have demonstrated enormous potential in long-range sequence modeling. However, the high dimensionality of hyperspectral data and information redundancy pose challenges to the application of Mamba in HSI classification, suffering from suboptimal performance and computational efficiency. In light of this, this paper investigates a lightweight Interval Group Spatial-Spectral Mamba framework (IGroupSS-Mamba) for HSI classification, which allows for multi-directional and multi-scale global spatial-spectral information extraction in a grouping and hierarchical manner. Technically, an Interval Group S6 Mechanism (IGSM) is developed as the core component, which partitions high-dimensional features into multiple non-overlapping groups at intervals, and then integrates a unidirectional S6 for each group with a specific scanning direction to achieve non-redundant sequence modeling. Compared to conventional applying multi-directional scanning to all bands, this grouping strategy leverages the complementary strengths of different scanning directions while decreasing computational costs. To adequately capture the spatial-spectral contextual information, an Interval Group Spatial-Spectral Block (IGSSB) is introduced, in which two IGSM-based spatial and spectral operators are cascaded to characterize the global spatial-spectral relationship along the spatial and spectral dimensions, respectively. IGroupSS-Mamba is constructed as a hierarchical structure stacked by multiple IGSSB blocks, integrating a pixel aggregation-based downsampling strategy for multiscale spatial-spectral semantic learning from shallow to deep stages. Extensive experiments demonstrate that IGroupSS-Mamba significantly outperforms the state-of-the-art methods in classification accuracy and achieves lower model parameters and floating po

关键词： Hyperspectral imaging

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Fault Detection of Nonlinear Dynamic Non-Stationary processes Under Stochastic Operating Modes Using Multi-Batch Differentiation Transformation With Kernel CCA

SSRN

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SSRN 2025年

作者： Feng, Liwei Tian, Bin Cui, Zhenhao Zhao, Chenhao Li, Yuan College of Science Shenyang University of Chemical Technology Shenyang110142 China College of Computer Science and Technology Shenyang University of Chemical Technology Shenyang110142 China College of Information Engineering Shenyang University of Chemical Technology Shenyang110142 China Key Laboratory of Intelligent Technology for Chemical Process Industry of Liaoning Province Shenyang110142 China

Nonlinear multi-batch dynamic non-stationary processes under stochastic operating conditions have characteristics such as inter-batch variability, nonlinearity and dynamic non-stationarity. Due to the influence of process characteristics, the traditional single-batch fault detection methods do not extract features in a comprehensive way, the multi-batch methods have large modeling bias, and they are difficult to extract the non-stationary feature information. The methods of Multi-batch Weighted Differentiation (MWD), Multi Standard Score (M-score), and Model Control Limit Averaging (MCLA) are proposed, and they are combined with KCCA to obtain the Multi-batch Difference Transformation with Kernel Canonical Correlation Analysis fault detection method (MDT-KCCA). MDT-KCCA is capable of adapting to the data differences of multi-batch with stochastic operating conditions, and extracting the feature information in dynamic non-stationary processes to establish an effective and stable monitoring model. Numerical simulation and penicillin fermentation monitoring experiments show that MDT-KCCA outperforms many comparative methods. © 2025, The Authors. All rights reserved.

关键词： Batch data processing

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Structural balance and evolution of cooperation in a population with hybrid interactions

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Physical Review E 2025年第4期111卷 044309-044309页

作者： Liming Zhang Lan Zhang Shun Gao Changwei Huang Qionglin Dai Jiangsu Key Laboratory of Educational Intelligent Technology School of Computer Science and Technology Jiangsu Normal University Xuzhou 221116 China School of Information Xi'an University of Finance and Economics Xi'an Shaanxi 710100 China School of Science Beijing University of Posts and Telecommunications Beijing 100876 People's Republic of China Blockchain and Distributed Ledger Technologies Faculty of Business Economics and Informatics University of Zurich Zurich 8050 Switzerland School of Computer Electronics and Information Guangxi University Nanning 530004 People's Republic of China

This study explores the evolution of cooperation in populations with mixed pairwise and three-body interactions, investigating the impact of higher-order interaction density ρ and individual interaction preference α. Our results reveal that sparse higher-order interactions markedly boost cooperation, exhibiting two critical phase transitions as ρ changes. These transitions underscore the delicate equilibrium needed for optimal cooperation, as excessive higher-order interactions can diminish returns. The preference parameter α significantly influences cooperation sustainability, with intermediate values maximizing cooperative outcomes, particularly when the temptation to defect r is not strong. Crucially, our findings demonstrate that hybrid social dilemmas structurally encode emergent cooperation pathways that are unattainable within homogeneous interaction frameworks, emphasizing the importance of modeling mixed interactions to capture real-world complexity. These insights offer valuable guidance for designing systems aimed at promoting cooperative behavior across social, ecological, and artificial domains.

关键词： Anthropogenic

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Variational Disentangled Graph Auto-Encoders for Link Prediction

arXiv

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arXiv 2023年

作者： Fu, Jun Zhang, Xiaojuan Li, Shuang Chen, Dali The State Key Laboratory of Synthetical Automation for Process Industries Northeastern University Shenyang China School of Computer Science and Technology Beijing Institute of Technology Beijing China The College of Information Science and Engineering Northeastern University Shenyang China

With the explosion of graph-structured data, link prediction has emerged as an increasingly important task. Embedding methods for link prediction utilize neural networks to generate node embeddings, which are subsequently employed to predict links between nodes. However, the existing embedding methods typically take a holistic strategy to learn node embeddings and ignore the entanglement of latent factors. As a result, entangled embeddings fail to effectively capture the underlying information and are vulnerable to irrelevant information, leading to unconvincing and uninterpretable link prediction results. To address these challenges, this paper proposes a novel framework with two variants, the disentangled graph auto-encoder (DGAE) and the variational disentangled graph auto-encoder (VDGAE). Our work provides a pioneering effort to apply the disentanglement strategy to link prediction. The proposed framework infers the latent factors that cause edges in the graph and disentangles the representation into multiple channels corresponding to unique latent factors, which contributes to improving the performance of link prediction. To further encourage the embeddings to capture mutually exclusive latent factors, we introduce mutual information regularization to enhance the independence among different channels. Extensive experiments on various real-world benchmarks demonstrate that our proposed methods achieve state-of-the-art results compared to a variety of strong baselines on link prediction tasks. Qualitative analysis on the synthetic dataset also illustrates that the proposed methods can capture distinct latent factors that cause links, providing empirical evidence that our models are able to explain the results of link prediction to some extent. All code will be made publicly available upon publication of the paper. Copyright © 2023, The Authors. All rights reserved.

关键词： Embeddings

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An Improvement of Coherent Semantic Attention for Image Inpainting 1

引用

6th International Conference on Artificial Intelligence and Security,ICAIS 2020

作者： Wang, Weiqing Gu, Enming Fang, Wei School of Computer & Software Jiangsu Engineering Center of Network Monitoring Nanjing University of Information Science and Technology Nanjing China State Key Laboratory for Novel Software Technology Nanjing University Nanjing China Jiangsu Key Laboratory of Computer Information Process Technology SooChow University Suzhou China

ISBN: (数字)9789811580833

ISBN: (纸本)9789811580826

In some image restoration algorithms of the past, they often do not consider the continuity between pixels, and the internal features of the hole region. The mapping to the image semantically does not take into account the continuity of the feature, resulting in the color of the fault. Or the deformation of the edge contour of the image. In some of the current popular algorithms and models, we can clearly see the color faults and artificial repair traces from their repair results. These discontinuities are mainly because these methods ignore the semantic relevance and feature continuity of the hole region. Therefore, if we want to get a better image repair effect. We have to improve on semantic relevance and feature continuity. We validated the effectiveness of our proposed method in image restoration tasks on the CelebA and Places2 datasets, and our results yielded a better visual experience in some images than existing methods. © 2020, Springer Nature Singapore Pte Ltd.

关键词： Semantics

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