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7th Optics Young Scientist Summit, OYSS 2024

作者： He, Ting Chang, Huan Gao, Ran Wang, Fei Guo, Dong Beijing Institute of Technology No.5 Zhongguancun South Street Haidian District Beijing100081 China National Key Laboratory of Science and Technology on Space-Born Intelligent Information Processing Beijing China

ISBN: (数字)9781510688377

ISBN: (纸本)9781510688360

Mode division multiplexing (MDM) optical fiber communication technology enhances bandwidth utilization and communication capacity to address the increasing demand for high-capacity data transmission in the era of rapid network traffic growth. For MDM optical fiber communication systems affected by various impairments, optical performance monitoring (OPM) can effectively characterize the impairments in received optical signals, directly reflecting the transmission signal state and channel conditions, and help ensure efficient and stable network operation. In this paper, we propose a multi-task convolutional neural network (MT-CNN) aided OPM method for MDM signals. The proposed MTCNN combines convolutional neural networks and a multi-task learning framework to extract the transmission link information and predict the optical signal-to-noise ratio (OSNR) of few-mode channels synchronously. Simulation results show that the proposed MT-CNN-based OPM scheme can achieve accurate OSNR performance evaluation for MDM fiber transmission signals. © 2025 SPIE.

关键词： Convolutional neural networks

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Mitigating Shortcut Learning via Smart Data Augmentation based on Large Language Model 31

Mitigating Shortcut Learning via Smart Data Augmentation bas...

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31st International Conference on Computational Linguistics, COLING 2025

作者： Sun, Xinyi Tan, Hongye Guo, Yaxin Qiang, Pengpeng Li, Ru Zhang, Hu School of Computer and Information Technology Shanxi University Taiyuan China Institute of Intelligent Information Processing Shanxi University Taiyuan China Key Laboratory of Computational Intelligence and Chinese Information Processing of Ministry of Education Shanxi University Taiyuan China

ISBN: (纸本)9798891761964

Data-driven pre-trained language models typically perform shortcut learning wherein they rely on the spurious correlations between the data and the ground truth. This reliance can undermine the robustness and generalization of the model. To address this issue, data augmentation emerges as a promising solution. By integrating anti-shortcut data to the training set, the models' shortcut-induced biases can be mitigated. However, existing methods encounter three challenges: (1) Manual definition of shortcuts is tailored to particular datasets, restricting generalization. (2) The inherent confirmation bias during model training hampers the effectiveness of data augmentation. (3) Insufficient exploration of the relationship between the model performance and the augmented data quantity may result in excessive data consumption. To tackle these challenges, we propose a method of Smart Data Augmentation based on Large Language Models (SAug-LLM). It leverages the LLMs to autonomously identify shortcuts and generate their anti-shortcut counterparts. In addition, the dual validation is employed to mitigate the confirmation bias during the model retraining. Furthermore, the data augmentation process is optimized to effectively rectify model biases while minimizing data consumption. We validate the effectiveness and generalization of our method through extensive experiments across various natural language processing tasks, demonstrating an average performance improvement of 5.61%. © 2025 Association for Computational Linguistics.

关键词： Data assimilation

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HairDiffusion: Vivid Multi-Colored Hair Editing via Latent Diffusion 38

HairDiffusion: Vivid Multi-Colored Hair Editing via Latent D...

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38th Conference on Neural information Processing Systems, NeurIPS 2024

作者： Zeng, Yu Zhang, Yang Liu, Jiachen Shen, Linlin Deng, Kaijun He, Weizhao Wang, Jinbao Computer Vision Institute School of Computer Science & Software Engineering Shenzhen University China Shenzhen Institute of Artificial Intelligence and Robotics for Society China National Engineering Laboratory for Big Data System Computing Technology Shenzhen University China Guangdong Provincial Key Laboratory of Intelligent Information Processing China

Hair editing is a critical image synthesis task that aims to edit hair color and hairstyle using text descriptions or reference images, while preserving irrelevant attributes (e.g., identity, background, cloth). Many existing methods are based on StyleGAN to address this task. However, due to the limited spatial distribution of StyleGAN, it struggles with multiple hair color editing and facial preservation. Considering the advancements in diffusion models, we utilize Latent Diffusion Models (LDMs) for hairstyle editing. Our approach introduces Multi-stage Hairstyle Blend (MHB), effectively separating control of hair color and hairstyle in diffusion latent space. Additionally, we train a warping module to align the hair color with the target region. To further enhance multi-color hairstyle editing, we fine-tuned a CLIP model using a multi-color hairstyle dataset. Our method not only tackles the complexity of multi-color hairstyles but also addresses the challenge of preserving original colors during diffusion editing. Extensive experiments showcase the superiority of our method in editing multi-color hairstyles while preserving facial attributes given textual descriptions and reference images. © 2024 Neural information processing systems foundation. All rights reserved.

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Medical image registration and its application in retinal images:a review

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Visual computing for Industry,Biomedicine,and Art 2024年第1期7卷 142-164页

作者： Qiushi Nie Xiaoqing Zhang Yan Hu Mingdao Gong Jiang Liu Research Institute of Trustworthy Autonomous Systems and Department of Computer Science and Engineering Southern University of Science and TechnologyShenzhen 518055China Center for High Performance Computing and Shenzhen Key Laboratory of Intelligent Bioinformatics Shenzhen Institute of Advanced TechnologyChinese Academy of SciencesShenzhen 518055China Singapore Eye Research Institute Singapore 169856Singapore State Key Laboratory of Ophthalmology Optometry and Visual ScienceEye HospitalWenzhou Medical UniversityWenzhou 325027China

Medical image registration is vital for disease diagnosis and treatment with its ability to merge diverse informa-tion of images,which may be captured under different times,angles,or *** several surveys have reviewed the development of medical image registration,they have not systematically summarized the existing med-ical image registration *** this end,a comprehensive review of these methods is provided from traditional and deep-learning-based perspectives,aiming to help audiences quickly understand the development of medical image *** particular,we review recent advances in retinal image registration,which has not attracted much *** addition,current challenges in retinal image registration are discussed and insights and prospects for future research provided.

关键词： Computer-aided diagnosis Medical image registration Deep learning Generative model Transformer Retina

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A large scale parallel fluid-structure interaction computing platform for simulating structural responses to a detonation shock

A large scale parallel fluid-structure interaction computing...

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作者： Zhang, Sen Guo, Xiao-Wei Li, Chao Liu, Yi Fan, Sijiang Zhao, Ran Yang, Canqun Institute for Quantum Information & State Key Laboratory of High Performance Computing College of Computer Science and Technology National University of Defense Technology Changsha China

Due to the intrinsic nature of multi-physics, it is prohibitively complex to design and implement a simulation software platform for study of structural responses to a detonation shock. In this article, a partitioned fluid-structure interaction computing platform is designed for parallel simulating structural responses to a detonation shock. The detonation and wave propagation are modeled in an open-source multi-component solver based on OpenFOAM and blastFoam, and the structural responses are simulated through the finite element library ***. To capture the interaction dynamics between the fluid and the structure, both solvers are adapted to preCICE. For improving the parallel performance of the computing platform, the inter-solver data is exchanged by peer-to-peer communications and the intermediate server in conventional multi-physics software is eliminated. Furthermore, the coupled solver with detonation support has been deployed on a computing cluster after considering the distributed data storage and load-balancing between solvers. The 3D numerical result of structural responses to a detonation shock is presented and analyzed. On 256 processor cores, the speedup ratio of the simulations for a detonation shock reach 178.0 with 5.1 million of mesh cells and the parallel efficiency achieve 69.5%. The results demonstrate good potential of massively parallel simulations. Overall, a general-purpose fluid-structure interaction software platform with detonation support is proposed by integrating open source codes. And this work has important practical significance for engineering application in fields of construction blasting, mining, and so forth. © 2021 John Wiley & Sons, Ltd.

关键词： Detonation

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Dynamic Task Scheduling for Coordinated Truck-Drone Parcel Delivery: A Hybrid Genetic Tabu Algorithm Approach 22

Dynamic Task Scheduling for Coordinated Truck-Drone Parcel D...

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22nd IEEE International Symposium on Parallel and Distributed Processing with Applications, ISPA 2024

作者： Li, Ruitai Yuan, Quan Liao, Tongxin Luo, Lijun Hu, Menglan Lai, Pan Zhang, Xiao South-Central Minzu University College of Computer Science China State Ethnic Affairs Commission Key Laboratory of Cyber-Physical Fusion Intelligent Computing China Huazhong University of Science and Technology School of Electronic Information and Communications China Hubei Key Laboratory of Smart Internet Technology China

ISBN: (纸本)9798331509712

With the rapid growth of the on-demand economy, logistics companies and merchants increasingly struggle to meet customer demands in dynamic and uncertain conditions. This paper studies the coordinated delivery of parcels by trucks and drones under such demands, proposing a Dynamic Task Scheduling Algorithm based on Hybrid Genetic Tabu algorithm (DTSAGT) for route optimization. Simulating dynamic customer demands with a Poisson distribution and statistical methods, the algorithm addresses timeliness issues due to variations in customer needs. It optimizes drone path planning and task allocation considering drone endurance and payload limits to minimize total delivery time. The algorithm includes three steps: initial solution construction, iterative optimization, and dynamic operations. Experimental results show that DTSAGT reduces the total service time by 15.05%, 34.13%, and 35.71% on average compared to the baseline algorithms. This paper's contribution is the combination of hybrid genetic and tabu search algorithms applied to dynamic task scheduling in truck-drone delivery, enhancing logistics efficiency. © 2024 IEEE.

关键词： Poisson distribution

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Online Dynamic Scaling of Microservices with Fair Probabilistic Routing 22

Online Dynamic Scaling of Microservices with Fair Probabilis...

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22nd IEEE International Symposium on Parallel and Distributed Processing with Applications, ISPA 2024

作者： Chen, Yang Lin, Shisheng Hu, Yi Wang, Liangyuan Hu, Menglan Lai, Pan Xie, Yuanai College of Computer Science South-Central Minzu University China Key Laboratory of Cyber-Physical Fusion Intelligent Computing State Ethnic Affairs Commission China School of Electronic Information and Communications Huazhong University of Science and Technology China Hubei Key Laboratory of Smart Internet Technology China

ISBN: (纸本)9798331509712

Microservice architecture, as an emerging network architecture, has gained widespread adoption in latency-sensitive applications within the realm of mobile edge computing (MEC). In MEC networks, these latency-sensitive applications necessitate the concurrent processing of numerous service requests, which are composed of microservices. The complex dependencies between microservices and frequent data communication between servers contribute to the intricacy of deploying and routing microservice instances within the network. Moreover, the dynamic and unpredictable nature of service request traffic significantly complicates the timeliness and efficiency of service deployment and request routing strategies. However, existing research predominantly focuses on static network environments and neglects the time-varying characteristics of service request traffic in realistic scenarios. Consequently, we address the joint optimization problem of service deployment and request routing in the presence of dynamic service request traffic. To model the inherent data dependencies and analyze service request response latency, we employ the open Jackson queuing network. We propose a fine-grained microservice dynamic scaling (FMDS) algorithm to capture the dynamic fluctuations in service request traffic within the network. This algorithm scales microservice instances based on the principle of equal proportional change, obtaining a service deployment scheme that minimizes costs while satisfying latency constraints. Furthermore, we introduce a recursive path search algorithm that explores the service deployment scheme to determine the node forwarding probability for the entire network, adhering to the principles of fair routing. Simulation results show that the proposed method effectively improves network latency stability by 75% and enhances the timeliness of the service deployment strategy. © 2024 IEEE.

关键词： microservice request routing service deployment services computing

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Degenerate polarization entangled photon source based on a single Ti-diffusion lithium niobate waveguide in a polarization Sagnac interferometer

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Chinese Physics B 2023年第8期32卷 69-73页

作者：孙宇孙昌伟周唯杨然端家晨龚彦晓徐平祝世宁 National Laboratory of Solid State Microstructures and School of Physics Nanjing UniversityNanjing 210093China NanZhi Institude of Advanced Optoelectronic Integration Nanjing 210018China Institute for Quantum Information and State Key Laboratory of High Performance Computing College of Computer Science and TechnologyNational University of Defense TechnologyChangsha 410073China

Combining a Ti-diffusion periodically poled lithium niobate(PPLN)waveguide with a Sagnac interferometer,two opposite directions type-II spontaneous parametric down conversions(SPDC)occur coherently and yield a high brightness,high stability polarization entanglement *** source produces degenerate photon pairs at 1540.4 nm with a brightness of B=(1.36±0.03)×10^(6) pairs/(s·nm·m W).We perform quantum state tomography to reconstruct the density matrix of the output state and obtain a fidelity of F=0.983±*** high brightness and phase stability of our waveguide source enable a wide range of quantum information experiments operating at a low pump power as well as hold the advantage in mass production which can promote the practical applications of quantum technologies.

关键词： polarization entanglement source Sagnac interferometer quantum information lithium niobate waveguide

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Disentangled latent factors for muti-cause treatment effect estimation 6

Disentangled latent factors for muti-cause treatment effect ...

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2024 6th International Conference on Artificial Intelligence Technologies and Applications, ICAITA 2024

作者： Zhao, Zhuoyue Wang, Haotian Xu, Liyang Wang, Qian Tang, Yuhua Department of Intelligent Data Science National University of Defense Technology Changsha410073 China Intelligent Game and Decision Lab. Academy of Military Science Beijing100071 China Institute for Quantum Information State Key Laboratory of High-Performance Computing College of Computer Science and Technology National University of Defense Technology Changsha410073 China

Existing methods estimate treatment effects from observational data and assume that covariates are all confounders. However, observed covariates may not directly represent confounding variables that influence both treatment and outcome. They always include variables that only affect the treatment or the outcome. In addition, for multi-dimensional binary treatments, disentangled methods are mainly designed for binary variables and ignore the impact of multi-cause treatment variables on the inference of latent factors. To address these two issues, based on variable decomposition and proxy inference, we propose the Disentangled Latent Factors for Multi-cause Treatment Estimation (DEMTE) algorithm. It utilizes an identifiable autoencoder to infer and disentangle latent factors based on the joint distribution of variables in observational data. DEMTE evaluates the treatment effect on the disentangled factors. Synthetic experiments and semi-synthetic experiments demonstrate the effectiveness of the inference and disentanglement techniques and our method achieves more accurate treatment effect estimation. © 2024 institute of Physics Publishing. All rights reserved.

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5G and UAV Integrated Three Dimensional Positioning Using Downlink PRS

5G and UAV Integrated Three Dimensional Positioning Using Do...

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2024 IEEE Global Communications Conference, GLOBECOM 2024

作者： Wang, Xunze Zhang, Ying Li, Yuliang Zhang, Tingting Harbin Institute of Technology School of Electronics and Information Engineering Shenzhen China Guangdong Provincial Key Laboratory of Space-Aerial Networking and Intelligent Sensing China Peng Cheng Laboratory Shenzhen China

ISBN: (纸本)9798350351255

The integration of unmanned aerial vehicles (UAVs) with 5G systems has revolutionized positioning technology, offering enhanced accuracy and reliability in challenging environments. We investigate the utilization of 5G downlink (DL) positioning reference signals (PRS) in conjunction with UAV assistance for 3-dimensional (3D) localization in urban macro environments. We introduce the generation of PRS and the corresponding frame structure, followed by their mapping for transmission via cyclic prefix orthogonal frequency division multiplexing (CP-OFDM). Subsequently, the user obtains the time difference of arrival (TDOA) by processing the PRS from each g-NodeB (gNB). An innovative UAV-assisted 3D localization method is then proposed, to address situations where the vertical localization accuracy is severely compromised. Finally, numerical results demonstrate that the proposed method enhances the horizontal localization accuracy by 47% and the vertical localization accuracy by 89%. Based on these findings, the optimal deployment of UAVs and gNBs selection strategy is also provided. © 2024 IEEE.

关键词： Time difference of arrival

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