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Asia Communications and Photonics Conference and Exhibition (ACP)

作者： Jiaxin Yan Xiaotian Sun Xiaoxiao Dai Weiqi Lu Qi Yang Jing Zhang Yuanxiang Wang Kun Qiu Key Lab. of Optical Fiber Sensing and Communications University of Electronic Science and Technology of China Chengdu China School of Optical and Electronic Information Huazhong University of Science and Technology Wuhan China School of Cyber Science and Engineering Huazhong University of Science and Technology Wuhan China

This paper proposes a synchronization method for transmitter parallel channels based on FPGA by measuring BER. In the experiment, we can realize the synchronization of 2-parallel channels with a bit rate of 25 Gbps.

关键词： Transmitters Bit rate Asia Delays Synchronization Field programmable gate arrays Photonics

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Optimization of Low-carbon Dispatching for Microgrid Based on Improved Particle Swarm Optimization

Optimization of Low-carbon Dispatching for Microgrid Based o...

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IEEE Conference on Energy Internet and Energy system Integration (EI2)

作者： Huan Yang Dongsheng Cai Olusola Bamisile Jian Li Zhenyuan Zhang Qi Huang School of Nuclear Technology and Automation Engineering Chengdu University of Technology Chengdu China Sichuan Provincial Key Lab of Power System Wide-Area Measurement and Control University of Electronic Science and Technology of China Chengdu China

In the context of carbon neutrality, the power industry is becoming the main battlefield of carbon emission reduction. However, the low-carbon transformation of energy structure is a complex long-term task, it needs to be analyzed in combination with the actual situation. This paper is based on the microgrid in the grid connection mode, considering microgrid power output and carbon emission constraints. An optimal model is proposed to reduce carbon emission cost, the optimal economic operation, and build a low-carbon scheduling model of a microgrid system. In this paper, the improved multi-objective particle swarm optimization algorithm is used to solve the problem. Finally, the simulation results verify the effectiveness of the model and the superiority of the improved algorithm.

关键词： Job shop scheduling Costs Wind energy Heuristic algorithms Optimal scheduling Microgrids system integration

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Coarse-to-Fine Latent Diffusion for Pose-Guided Person Image Synthesis

Coarse-to-Fine Latent Diffusion for Pose-Guided Person Image...

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Conference on Computer Vision and Pattern Recognition (CVPR)

作者： Yanzuo Lu Manlin Zhang Andy J Ma Xiaohua Xie Jianhuang Lai School of Computer Science and Engineering Sun Yat-sen University Guangzhou China Guangdong Province Key Laboratory of Information Security Technology China Key Laboratory of Machine Intelligence and Advanced Computing Ministry of Education China Pazhou Lab (HuangPu) Guangzhou China

ISBN: (数字)9798350353006

ISBN: (纸本)9798350353013

Diffusion model is a promising approach to image generation and has been employed for Pose-Guided Person Image Synthesis (PGPIS) with competitive performance. While existing methods simply align the person appearance to the target pose, they are prone to overfitting due to the lack of a high-level semantic understanding on the source person image. In this paper, we propose a novel Coarse-to-Fine Latent Diffusion (CFLD) method for PGPIS. In the absence of image-caption pairs and textual prompts, we de-velop a novel training paradigm purely based on images to control the generation process of a pre-trained text-to-image diffusion model. A perception-refined decoder is designed to progressively refine a set of learnable queries and extract semantic understanding of person images as a coarse-grained prompt. This allows for the decoupling of fine-grained appearance and pose information controls at different stages, and thus circumventing the potential over-fitting problem. To generate more realistic texture details, a hybrid- granularity attention module is proposed to encode multi-scale fine-grained appearance features as bias terms to augment the coarse-grained prompt. Both quantitative and qualitative experimental results on the DeepFashion benchmark demonstrate the superiority of our method over the state of the arts for PGPIS. Code is available at https://***/YanzuoLu/CFLD.

关键词： Training Image synthesis Semantics Text to image Process control Diffusion models Generators

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Fast and accurate extraction of ultra-high quality factor from cavity ring-down measurement

arXiv

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arXiv 2024年

作者： Yang, Yanping Liu, Shihan Geng, Yong Wen, Huashun Zhou, Heng Key Lab of Optical Fiber Sensing and Communication Networks School of Information and Communication Engineering University of Electronic Science and Technology of China Chengdu611731 China State Key Laboratory on Integrated Optoelectronics Institute of Semiconductors Chinese Acacmy of Sciences Beijing100083 China

Cavity ring-down is an essential test to measure ultra-high quality factor (UHQ) optical cavities, which is, however, frequently misinterpreted due to lacking of a specified analysis guideline. Here we clarify the basic property of cavity ring down and present a step-by-step method that enables extraction of the overall quality factor, as well as the intrinsic loss and coupling state of UHQ cavities with better fidelity and simplicity than prior schemes. Our work can facilitate acurrate design and characterization of UHQ cavities for ultra-low noise lasers, high finesse reference cavities, and ultra-narrow optical filters. Copyright © 2024, The Authors. All rights reserved.

关键词： Extraction

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An Intelligent Recognition Algorithm for Urban Utility Tunnel Surface Intrusion via Spatio-temporal-spectral Joint information Extraction with FPN Network

An Intelligent Recognition Algorithm for Urban Utility Tunne...

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Asia Communications and Photonics Conference and Exhibition (ACP)

作者： Tao He Zhijun Yan Shixiong Zhang Deming Liu Hao Li Qizhen Sun Hubei Key Laboratory of Distributed System Security Hubei Engineering Research Center on Big Data Security School of Cyber Science and Engineering Huazhong University of Science and Technology Wuhan P. R. China School of Optical and Electronic Information Huazhong University of Science and Technology Wuhan P. R. China

An intelligent recognition algorithm for utility tunnel surface intrusion based on spatio-temporal-spectral joint information extraction with FPN network is proposed. Finally, the average recognition accuracy of 93.8%... 详细信息

关键词： Target recognition Neural networks Asia information retrieval Feature extraction Safety Monitoring

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Channel Treatment for Internet Addiction with Puskesmas Application: Design Approach with Usability Heuristics

Channel Treatment for Internet Addiction with Puskesmas Appl...

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2021 International Conference Advancement in Data science, E-learning and information systems, ICADEIS 2021

作者： Lubis, Muharman Handayani, Dini Oktarina Adrian, Qadhli Jafar Gustiarani, Anastassya Madjid, Cheta Kusuma Nurhas, Irawan Telkom University Information System Department Bandung Indonesia Tailor University Innovation Technology Department Selangor Malaysia Universitas Teknokrat Indonesia Computer Engineering and Science Department Bandar Lampung Indonesia Institute of Positive Computing Hochschule Ruhr West University of Applied Science Mülheim Germany

ISBN: (纸本)9781665437097

Developed since 1968, Puskesmas is the most important healthcare facility and is at the forefront of providing basic healthcare services at the community level. Basically, its role is very important and should be one of the keys to Indonesia's success in improving the health and nutritional status of the community. Meanwhile, Internet addiction become potential threat to the community that might be more dangerous compare to drug and sex addiction in term of social consequences. This study offer the integrated solution through usability heuristics design for the purpose of redesigning current apps after the identification of business process in several Puskesmas in the Bandung. It also want to increase the quality of service in order to provide proper communication between health workers and patients. In evaluation phase, the 4 criteria was used to generate sketches in relation to contextual settings. Then, the mockups will be assessed with 12 transaction features to ensure the readiness of its financial management before the application launching. © 2021 IEEE.

关键词： Quality of service

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A Mars Multi-terrain Simulator Using a Modular Terrain Construction Framework

A Mars Multi-terrain Simulator Using a Modular Terrain Const...

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On-Line Conference (ONCON), Industrial Electronics Society Annual

作者： Yun Jiang Meibao Yao Bo Zheng Tao Hu Tao Cao Xueming Xiao Intelligent Robotics Lab (IRL) School of Artificial Intelligence Jilin University Changchun China Engineering Research Center of Knowledge-Driven Human-Machine Intelligence Ministry of Education China Shanghai Aerospace Control Technology Institute Shanghai China CVIR Lab Changchun University of Science and Technology Changchun China Key Lab of Optoelectronic Measurement and Optical Information Transmission Technology

Mars exploration tasks are inseparable from the support of robotic equipment. More comprehensive environmental awareness capabilities can improve the efficiency of robots on the surface of Mars. Artificial neural networks have emerged as pivotal tools in enhancing the perceptual capabilities of robots. The cornerstone of effective neural network training lies in the availability of high-quality data. Regrettably, the unstructured terrains, particularly the Martian landscape, lack real-world datasets with high-quality annotations. To overcome this challenge, using simulators to generate large amounts of high-quality data for researchers is a good option. Nonetheless, the creation of these simulators requires complex details such as ground texture characteristics and rock distribution, which increases research costs. In response, we introduce a novel approach – the modular terrain construction framework and construct a Mars multi-terrain simulator based on it. This innovative simulator not only simplifies the simulation process but also grants users the flexibility to alter it to their specific research needs. One of the standout features of our simulator is its capacity to generate rich metadata, such as semantic and depth, which can be used seamlessly for a multitude of downstream applications. To validate the reliability of the data produced by our simulator, we have assessed its performance on a semantic segmentation task.

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A Reinforcement Learning Based Approach to Identify Resource Bottlenecks for Multiple Services Interactions in Cloud Computing Environments 16th

A Reinforcement Learning Based Approach to Identify Resource...

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16th EAI International Conference on Collaborative Computing: Networking, Applications, and Worksharing, CollaborateCom 2020

作者： Xu, Lingxiao Xu, Minxian Semmes, Richard Li, Hui Mu, Hong Gui, Shuangquan Tian, Wenhong Wu, Kui Buyya, Rajkumar School of Software and Information Engineering University of Electronic Science and Technology of China Chengdu China Shenzhen Institutes of Advanced Technology Chinese Academy of Sciences Shenzhen China Co. Ltd. Chengdu China Department of Computer Science University of Victoria Victoria Canada CLOUDS Lab School of Computing and Information Systems University of Melbourne Melbourne Australia

ISBN: (纸本)9783030675394

Cloud service providers are provisioning resources including a variety of virtual machine instances to support customers that migrate their services to the cloud. From the customers’ perspective, selecting the appropriate amount of resources is tightly coupled with performance and cost. By identifying the potential resource bottlenecks in the early stage of the service deployment process, resource planning can be significantly optimized. However, due to the unpredictable workloads and heterogeneous resources, it is difficult to identify resource bottlenecks that can degrade system performance. To support system non-functional requirements (NFR) in a better manner, we propose a reinforcement learning based approach to support the NFR management of system concerning the multiple services interactions scenario by identifying the potential resource bottleneck and optimizing the demanded resources. The proposed approach can predict the resource bottleneck for multiple services interactions, e.g. bottleneck in CPU or overloads in specific service, and provide guidance for resource planning. We modeled and simulated the proposed approach using an extended version of the CloudSim toolkit. Comprehensive evaluations with realistic use case from Siemens Digital Industries Software’s MindSphere Solution on AliCloud show that our proposed approach can achieve high accuracy in terms of performance metrics, such as response time, queries per second (QPS), and resource usage. © 2021, ICST Institute for Computer sciences, Social Informatics and Telecommunications engineering.

关键词： Reinforcement learning

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Protocols and Trade-Offs of Quantum State Purification

arXiv

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arXiv 2024年

作者： Yao, Hongshun Chen, Yu-Ao Huang, Erdong Chen, Kaichu Fu, Honghao Wang, Xin Guangdong511453 China Concordia Institute for Information Systems Engineering Concordia University QuebecH3G 1M8 Canada Computer Science and Artificial Intelligence Lab Massachusetts Institute of Technology MA02139 United States

Quantum state purification is crucial in quantum communication and computation, aiming to recover a purified state from multiple copies of an unknown noisy state. This work introduces a general state purification framework designed to achieve the highest fidelity with a specified probability and characterize the associated trade-offs. For i.i.d. quantum states under depolarizing noise, our framework can replicate the purification protocol proposed by [Barenco et al., SIAM Journal on Computing, 26(5), 1997] and further provide exact formulas for the purification fidelity and probability with explicit trade-offs. We prove the protocols' optimality for two copies of noisy states with any dimension and confirm its optimality for higher numbers of copies and dimensions through numerical analysis. Our methodological approach paves the way for proving the protocol's optimality in more general scenarios and leads to optimal protocols for other noise models. Furthermore, we present a systematic implementation method via block encoding and parameterized quantum circuits, providing explicit circuits for purifying three-copy and four-copy states under depolarizing noise. Finally, we estimate the sample complexity and generalize the protocol to a recursive form, demonstrating its practicality for quantum computers with limited memory. © 2024, CC BY.

关键词： Quantum computers

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Distributed Online Convex Optimization with Time-Varying Constraints: Tighter Cumulative Constraint Violation Bounds under Slater's Condition

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IEEE Transactions on Automatic Control 2025年

作者： Yi, Xinlei Li, Xiuxian Yang, Tao Xie, Lihua Hong, Yiguang Chai, Tianyou Johansson, Karl H. National Key Laboratory of Autonomous Intelligent Unmanned Systems Shanghai Institute of Intelligent Science and Technology China Ministry of Education Frontiers Science Center for Intelligent Autonomous Systems China Massachusetts Institute of Technology Lab for Information & Decision Systems CambridgeMA02139 United States Northeastern University State Key Laboratory of Synthetical Automation for Process Industries Shenyang110819 China Nanyang Technological University School of Electrical and Electronic Engineering 50 Nanyang Avenue 639798 Singapore Kth Royal Institute of Technology Division of Decision and Control Systems School of Electrical Engineering and Computer Science Sweden Digital Futures Stockholm10044 Sweden

This paper considers distributed online convex optimization with time-varying constraints. In this setting, a network of agents makes decisions at each round, and then only a portion of the loss function and a coordinate block of the constraint function are privately revealed to each agent. The loss and constraint functions are convex and can vary arbitrarily across rounds. The agents collaborate to minimize static network regret and network cumulative constraint violation. A novel distributed online algorithm with a vanishing stepsize is proposed and it achieves an O(Tmax {c,1-c}) static network regret bound and an O(T1-c/2) network cumulative constraint violation bound, where T is the number of rounds and c∈ (0,1) is a user-defined trade-off parameter. When Slater's condition holds (i.e, there is a point that strictly satisfies the inequality constraints), the network cumulative constraint violation bound is reduced to O(T1-c). Moreover, if the loss functions are strongly convex, then static network regret bound is reduced to O(log (T)), and the network cumulative constraint violation bound is reduced to O(√log (T)T) and O(log (T)) without and with Slater's condition, respectively. To the best of our knowledge, this paper is the first to achieve tighter (network) cumulative constraint violation bounds for (distributed) online convex optimization with time-varying constraints under Slater's condition. Finally, the theoretical results are verified through numerical simulations. © 1963-2012 IEEE.

关键词： Convex optimization

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