检索结果-内蒙古大学图书馆

Resource Optimization for LEO Constellation Networks: A Multi-satellite Cooperative Coverage Design

IEEE Transactions on Communications 2025年

作者： Ma, Xu Zhang, Haijun Song, Wei Lu, Yang Wu, Yuan Leung, Victor C.M University of Science and Technology Beijing Beijing Engineering and Technology Research Center for Convergence Networks and Ubiquitous Services Beijing100083 China China Electric Power Research Institute Co. Ltd Beijing102209 China University of Macau State Key Laboratory of Internet of Things for Smart City Macau China University of Macau Department of Computer and Information Science Macau China Shenzhen University Department of Computer Science and Software Engineering Shenzhen518061 China

With its low latency, high throughput, good deployment flexibility, and cost-effectiveness, the low earth orbit (LEO) constellation is regarded as a promising technology for seamless coverage. Unlike geosynchronous orbiting (GSO) satellites, the highly dynamic evolution of LEO constellation topology poses a significant challenge to the traditional scheme of allocating wireless resources. This paper proposes a multisatellite cooperative coverage resource allocation for the LEO constellation. A multi-objective optimization problem focusing on throughput and coverage time is proposed for the overall service quality of the LEO constellation. To solve the complex coupling between multi-domain resources, the optimization problem is decomposed into three key subproblems, which are the beam placement problem, the joint beam association with power allocation problem, and the beam hopping time slot allocation problem. For each subproblem, an adaptive algorithm is proposed that effectively exploits the payload of LEO satellites to ensure the coverage performance of the constellation network. Simulation results demonstrate that the proposed coverage scheme enables fast convergence, enhances network throughput utility, and guarantees the stability and fairness of the communication services. © 1972-2012 IEEE.

关键词： Multiobjective optimization

来源：评论

学校读者我要写书评

暂无评论

Two-Stage Inverse Design of Superchiral Dielectric Metasurfaces

Two-Stage Inverse Design of Superchiral Dielectric Metasurfa...

引用

International Review of Progress in Applied Computational Electromagnetics (ACES)

作者： Omer Yesilyurt Vahagn Mkhitaryan Jer-Shing Huang Ilya Shadrivov Alexander V. Kildishev Elmore Family School of Electrical and Computer Engineering Birck Nanotechnology Center and Purdue Quantum Science and Engineering Institute Purdue University West Lafayette IN USA Department of Energy (DOE) The Quantum Science Center (QSC) a National Quantum Information Science Research Center of the U.S. Oak Ridge TN USA Leibniz Institute of Photonic Technology Jena Germany ARC Centre of Excellence for Transformative Meta-Optical Systems (TMOS) Research School of Physics the Australian National University Canberra Australia

ISBN: (数字)9781733509671

ISBN: (纸本)9798350362978

Chirality is a fundamental property of asymmetry and is crucial in distinguishing molecular enantiomers, with profound implications across chemistry, biology, and materials science. Circular dichroism (CD) spectroscopy, which measures the differential absorption of left-handed (LCP) and right-handed (RCP) circularly polarized light, serves as a conventional method for identifying and separating chiral enantiomers. Nevertheless, due to the inherently weak chiral-optical interactions, the CD signals of numerous chiral molecules are minimal, typically spanning 10– 3 to 10– 6 within the ultraviolet spectrum. Superchiral metasurfaces, producing fields with enhanced optical chirality that surpasses the chirality of circularly polarized light, emerge as a solution to this challenge. Such metasurfaces, with enhanced interaction between light and chiral molecules, offer a significant increase in CD signal, underscoring the necessity for their advanced development for more accurate and sensitive analysis. This study presents a novel, two-stage inverse design methodology for superchiral metasurfaces with iterative optimization of the topology of a dielectric metasurface unit cell to enhance optical chiral density in the near field. In the first stage, a neural network-based optimizer works in tandem with a rigorous coupled wave analysis (RCWA) solver. In the second stage, adjoint gradients of the optical chirality density are derived from the first principles and calculated with a Finite Difference Time Domain (FDTD) scheme. Our results offer a new platform for high-sensitivity CD spectroscopy applications, allowing for fast, constrained optimization of the unit cells.

关键词： Spectroscopy Optical polarization Biomedical optical imaging Metasurfaces Optical network units Optical coupling Optical sensors

来源：评论

学校读者我要写书评

暂无评论

Mitigating machining damage: Advanced modelling of pumice loading effects in Kevlar fibre-pumice sandwich polymer composites at the AWJM zone

引用

Journal of Materials Research and Technology 2025年 37卷 1019-1028页

作者： Venkatesh Chenrayan A. Saravanakumar Kiran Shahapurkar S. Vaishnavi S. Selvam Chandru Manivannan Vineet Tirth Ali Algahtani Jana Petrů Muhammad Nasir Bashir Manzoore Elahi M. Soudagar Krishna Prakash Arunachalam H.M. Vidhya Centre of Excellence-Advanced Materials Synthesis (CoE-AMS) Department of Mechanical Engineering Alliance School of Applied Engineering Alliance University Bengaluru 562106 India AU-Sophisticated Testing and Instrumentation Centre (AU-STIC) Alliance University Bengaluru 562106 India Department of Computer Science Engineering PSG Institute of Technology and Applied Research Coimbatore India Department of Mechanical Engineering Coimbatore Institute of Technology Coimbatore India Department of Mechanical Engineering Dhirajlal Gandhi College of Technology Salem 63840: India Mechanical Engineering Department College of Engineering King Khalid University Abha 61421 Asir Kingdom of Saudi Arabia Centre for Engineering and Technology Innovations King Khalid University Abha 61421 Asir Kingdom of Saudi Arabia Research Center for Advanced Materials Science (RCAMS) King Khalid University Guraiger PO Box 9004 Abha 61413 Asir Kingdom of Saudi Arabia Department of Machining Assembly and Engineering Metrology Faculty of Mechanical Engi-neering VŠB Technical University of Ostrava Ostrava Czech Republic Department of Mechanical Engineering University of Malaya 50603 Kuala Lumpur Malaysia Multi-Scale Fluid Dynamics Lab Department of Mechanical Engineering Yonsei University Seoul 120-749 Republic of Korea Centre for Research Impact and Outcome Chitkara University Institute of Engineering and Technology Chitkara University Rajpura 140401 Punjab India Centre for Promotion of Research Graphic Era (Deemed to be University) Clement town Dehradun India Departamento de Ciencias de la Construcción Facultad de Ciencias de la Construcción Ordenamiento Territorial Universidad Tecnológica Metropolitana Santiago Chile Centre of Molecular Medicine and Diagnostics (COMManD) Saveetha Dental College and Hospitals Saveetha Institute of Medical and Technical Sciences Saveetha University Chennai 600 077 India

The development of varieties of fibre-reinforced polymer composite (FRP) has become a part of day-to-day life and is the core agenda of the manufacturing industries in new product development. Despite the wider applications, the machining of FRPs is encountering a greater challenge in overcoming the machining damage. It is the right proposal to deplete the prominent machining damages like kerf taper, delamination and surface roughness by introducing novel hybrid statistical and soft computing models. The novel Kevlar fiber woven mat-pumice particles reinforced sandwich is fabricated using open moulding and machined with Abrasive Water Jet Machining by following L9 orthogonal guidelines. The three different pumice compositions, standoff distance, abrasive flow rate and hydraulic pressure were considered the prime variables to influence the damages. The hybrid analysis results declare that trial No.3 is an optimal parameter, which comprises 100 (MPa) of hydraulic pressure, 2 mm of standoff distance, 300 (gm/min) of abrasive flow rate and 10 % of pumice particles to scale down the damages. A noticeable 1.69 %, 25.12 % and 40.71 % decrement in machining damages, along with the finding of a higher contribution of pumice content in minimizing the damages, would benefit the FRP industries to march towards the implementation of lean manufacturing and new product development (NPD).

关键词： Kevlar fibre Pumice Delamination Kerf taper Surface roughness Grey relational analysis (GRA) Machine learning (ML)

来源：评论

学校读者我要写书评

暂无评论

Collaborative Learning-Based Scheduling for Kubernetes-Oriented Edge-Cloud Network

arXiv

引用

arXiv 2023年

作者： Shen, Shihao Han, Yiwen Wang, Xiaofei Wang, Shiqiang Leung, Victor C.M. The College of Intelligence and Computing Tianjin University Tianjin300350 China IBM T. J. Watson Research Center Yorktown HeightsNY10598 United States The College of Computer Science and Software Engineering Shenzhen University Shenzhen518052 China The Department of Electrical and Computer Engineering The University of British Columbia VancouverV6T 1Z4 Canada

Kubernetes (k8s) has the potential to coordinate distributed edge resources and centralized cloud resources, but currently lacks a specialized scheduling framework for edge-cloud networks. Besides, the hierarchical distribution of heterogeneous resources makes the modeling and scheduling of k8soriented edge-cloud network particularly challenging. In this paper, we introduce KaiS, a learning-based scheduling framework for such edge-cloud network to improve the long-term throughput rate of request processing. First, we design a coordinated multiagent actor-critic algorithm to cater to decentralized request dispatch and dynamic dispatch spaces within the edge cluster. Second, for diverse system scales and structures, we use graph neural networks to embed system state information, and combine the embedding results with multiple policy networks to reduce the orchestration dimensionality by stepwise scheduling. Finally, we adopt a two-time-scale scheduling mechanism to harmonize request dispatch and service orchestration, and present the implementation design of deploying the above algorithms compatible with native k8s components. Experiments using real workload traces show that KaiS can successfully learn appropriate scheduling policies, irrespective of request arrival patterns and system scales. Moreover, KaiS can enhance the average system throughput rate by 15.9% while reducing scheduling cost by 38.4% compared to baselines. Copyright © 2023, The Authors. All rights reserved.

关键词： Reinforcement learning

来源：评论

学校读者我要写书评

暂无评论

Classification of Pancreatic Cystic Lesions Using ResNet Deep Learning Network in Confocal Laser Endomicroscopy Videos

引用

Procedia computer Science 2024年 234卷 357-363页

作者： Clara Lavita Angelina Chien-Ming Pan Tsung-Chun Lee Ming-Lun Han Pradermchai Kongkam Hsiu-Po Wang Chuan-Yu Chang Hsuan-Ting Chang Department of Electrical Engineering National Yunlin University of Science and Technology Yunlin Taiwan Department of Internal Medicine Taipei Medical University Shuang Ho Hospital New Taipei City Taiwan Department of Integrated Diagnostics and Therapeutics National Taiwan University Hospital Taipei Taiwan Gastrointestinal Endoscopy Excellence Center and Division of Gastroenterology Chulalongkorn University and King Chulalongkorn Memorial Hospital Thai Red Cross Society Bangkok Thailand Department of Internal Medicine National Taiwan University Hospital and College of Medicine National Taiwan University Taipei Taiwan Department of Computer Science and Information Engineering National Yunlin University of Science and Technology Yunlin Taiwan

Accurate classification of pancreatic cystic lesions is crucial to differentiate mucinous lesions of malignant potential. We utilized the ResNet-50 and ResNet-101 network to develop a model for classification of the pancreatic cystic lesions. A total of 50 videos, 13,425 images, from five types of pancreatic cystic lesions and utilize the image rotation and contrast reversal scheme for the training. We adopt a contrast limited adaptive histogram equalization method onto the test video. Our method can automatically classify the feature type and record the prediction results frame by frame. The method has been evaluated on 18 test videos and achieves an accuracy 94% overall.

关键词： Contrast Limited Adaptive Histogram Equalization Contrast Reversal Deep Learning Pancreatic Cystic Lesions ResNet-50 ResNet-101

来源：评论

学校读者我要写书评

暂无评论

A Contrastive Learning-based PPC-UNet for Colorectal Histopathology Whole Slide Image Segmentation

A Contrastive Learning-based PPC-UNet for Colorectal Histopa...

引用

2021 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2021

作者： Wang, Yuxuan Li, Xuechen Liu, Jingxin Shen, Linlin Sun, Kunming Wang, Suying AI Research Centre for Medical Image Analysis and Diagnosis Marshall Laboratory of Biomedical Engineering Shenzhen University School of Computer Science and Software Engineering Shenzhen China Xi'An Jiaotong-Liverpool University Histo Pathology Diagnostic Center Shanghai School of AI and Advanced Computing Suzhou China Histo Pathology Diagnostic Center Shanghai China Ningbo Diagnostic Pathology Center Department of Pathology Ningbo China

ISBN: (纸本)9781665401265

Colorectal cancer (CRC) is the third most common cancer and is usually diagnosed using colonoscopy and biopsy. Diagnosis of pathological biopsy requires professional knowledge and technology. computer-aided gland and lesion segmentation systems have been proposed to help pathologists in diagnosis of CRC. However, to the best of our knowledge, there has not been a literature work trying to segment different levels of intraepithelial neoplasia in CRC pathological image. To reduce such a research gap, in this paper, we firstly collect a colorectal cancer biopsy histopathology whole slide image (WSI) dataset, named Histo-CRC Biopsy dataset, for algorithm evaluation. We further propose a PPC-UNet network to segment high level, low level intraepithelial neoplasia and normal tissues. The proposed PPC-UNet consists of two modules i.e., a UNet-based network for segmentation, and a pixel-to-propagation consistency (PPC) contrastive learning-based network for UNet encoder pre-training. As the important feature can be learned from the unannotated data during pre-training, our approach can consistently improve the Dice of UNet by around 2% when different ratios of the training data are labeled. © 2021 IEEE.

关键词： Image segmentation

来源：评论

学校读者我要写书评

暂无评论

TCEIP: Text Condition Embedded Regression Network for Dental Implant Position Prediction

arXiv

引用

arXiv 2023年

作者： Yang, Xinquan Xie, Jinheng Li, Xuguang Li, Xuechen Li, Xin Shen, Linlin Deng, Yongqiang College of Computer Science and Software Engineering Shenzhen University Shenzhen China AI Research Center for Medical Image Analysis and Diagnosis Shenzhen University Shenzhen China National Engineering Laboratory for Big Data System Computing Technology Shenzhen University China Department of Stomatology Shenzhen University General Hospital Shenzhen China National University of Singapore Singapore

When deep neural network has been proposed to assist the dentist in designing the location of dental implant, most of them are targeting simple cases where only one missing tooth is available. As a result, literature works do not work well when there are multiple missing teeth and easily generate false predictions when the teeth are sparsely distributed. In this paper, we are trying to integrate a weak supervision text, the target region, to the implant position regression network, to address above issues. We propose a text condition embedded implant position regression network (TCEIP), to embed the text condition into the encoder-decoder framework for improvement of the regression performance. A cross-modal interaction that consists of cross-modal attention (CMA) and knowledge alignment module (KAM) is proposed to facilitate the interaction between features of images and texts. The CMA module performs a cross-attention between the image feature and the text condition, and the KAM mitigates the knowledge gap between the image feature and the image encoder of the CLIP. Extensive experiments on a dental implant dataset through five-fold cross-validation demonstrated that the proposed TCEIP achieves superior performance than existing methods. Copyright © 2023, The Authors. All rights reserved.

关键词： Signal encoding

来源：评论

学校读者我要写书评

暂无评论

Lessons Learned from Optimizing the Sunway Storage System for Higher Application I/O Performance

引用

Journal of computer Science & Technology 2020年第1期35卷 47-60页

作者： Qi Chen Kang Chen Zuo-Ning Chen Fellow CCF Wei Xue Xu Ji Bin Yang Department of Computer Science and Technology Beijing National Research Center for Information Science and Technology(BNRist)Tsinghua UniversityBeijing 100084China Chinese Academy of Engineering Beijing 100088China National Supercomputing Center in Wuxi Wuxi 214100China School of Software Shandong UniversityJinan 250101China

It is hard for applications to make full utilization of the peak bandwidth of the storage system in highperformance computers because of I/O interferences,storage resource misallocations and complex long I/O *** performed several studies to bridge this gap in the Sunway storage system,which serves the supercomputer Sunway *** locate these issues and connections between them,an end-to-end performance monitoring and diagnosis tool was developed to understand I/O behaviors of applications and the *** the help of the tool,we were about to find out the root causes of such performance barriers at the I/O forwarding layer and the parallel file system *** application-aware I/O forwarding allocation framework was used to address the I/O interferences and resource misallocations at the I/O forwarding layer.A performance-aware data placement mechanism was proposed to mitigate the impact of I/O interferences and performance variations of storage devices in the ***,applications obtained much better I/O *** the process,we also proposed a lightweight storage stack to shorten the I/O path of applications with N-N I/O *** paper summarizes these studies and presents the lessons learned from the process.

关键词： high performance computing I/O interference parallel file system performance optimization resource misallocation

来源：评论

学校读者我要写书评

暂无评论

TLDR: Traffic Light Detection using Fourier Domain Adaptation in Hostile WeatheR

arXiv

引用

arXiv 2024年

作者： Gakhar, Ishaan Guha, Aryesh Gupta, Aryaman Agarwal, Amit Toshniwal, Durga Verma, Ujjwal Department of Information and Communication Technology Manipal Institute of Technology Manipal Academy of Higher Education India Department of Electrical and Electronics Engineering Manipal Institute of Technology Manipal Academy of Higher Education India Department of Computer Science Engineering Manipal Institute of Technology Manipal Academy of Higher Education India Enterprise Analytics & Data Science Artificial Intelligence Center of Excellence Wells Fargo International Solutions Private Limited Center For Transportation Systems Indian Institute of Technology Roorkee India Manipal Institute of Technology Bengaluru Manipal Academy of Higher Education India

The scarcity of comprehensive datasets in the traffic light detection and recognition domain and the poor performance of state-of-the-art models under hostile weather conditions present significant challenges. To address these issues, this paper proposes a novel approach by merging two widely used datasets, LISA and S2TLD. The merged dataset is further processed to tackle class imbalance, a common problem in this domain. This merged dataset becomes our source domain. Synthetic rain and fog are added to the dataset to create our target domain. We employ Fourier Domain Adaptation (FDA) to create a final dataset with a minimized domain gap between the two datasets, helping the model trained on this final dataset adapt to rainy and foggy weather conditions. Additionally, we explore Semi-Supervised Learning (SSL) techniques to leverage the available data more effectively. Experimental results demonstrate that models trained on FDA-augmented images outperform those trained without FDA across confidence-dependent and independent metrics, like mAP50, mAP50-95, Precision, and Recall. The best-performing model, YOLOv8, achieved a Precision increase of 5.1860%, Recall increase of 14.8009%, mAP50 increase of 9.5074%, and mAP50- 95 increase of 19.5035%. On average, percentage increases of 7.6892% in Precision, 19.9069% in Recall, 15.8506% in mAP50, and 23.8099% in mAP50-95 were observed across all models, highlighting the effectiveness of FDA in mitigating the impact of adverse weather conditions on model performance. These improvements pave the way for real-world applications where reliable performance in challenging environmental conditions is critical. Impact Statement-This research addresses a critical challenge in autonomous driving systems-poor performance in adverse weather conditions-by introducing a novel method using Fourier Domain Adaptation (FDA). The FDA-enhanced models significantly improve the detection of traffic lights in rain and fog, which has broad implicatio

关键词： Rain

来源：评论

学校读者我要写书评

暂无评论

Offsite Evaluation of Localization Systems: Criteria, Systems, and Results From IPIN 2021 and 2022 Competitions

IEEE Journal on Indoor and Seamless Positioning and Navigati...

引用

IEEE Journal on Indoor and Seamless Positioning and Navigation 2024年 2卷 92-129页

作者： Potorti, Francesco Crivello, Antonino Lee, Soyeon Vladimirov, Blagovest Park, Sangjoon Chen, Yushi Wang, Long Chen, Runze Zhao, Fang Zhuge, Yue Luo, Haiyong Perez-Navarro, Antoni Jimenez, Antonio R. Wang, Han Liang, Hengyi De Cock, Cedric Plets, David Cui, Yan Xiong, Zhi Li, Xiaodong Ding, Yiming Franco, Fernando Javier Alvarez Polo, Fernando Jesus Aranda Rodriguez, Felipe Parralejo Moreira, Adriano Pendao, Cristiano Silva, Ivo Ortiz, Miguel Zhu, Ni Li, Ziyou Renaudin, Valerie Wei, Dongyan Ji, Xinchun Zhang, Wenchao Wang, Yan Ding, Longyang Kuang, Jian Zhang, Xiaobing Dou, Zhi Yang, Chaoqun Kram, Sebastian Stahlke, Maximilian Mutschler, Christopher Coene, Sander Li, Chenglong Venus, Alexander Leitinger, Erik Tertinek, Stefan Witrisal, Klaus Wang, Yi Wang, Shaobo Jin, Beihong Zhang, Fusang Su, Chang Wang, Zhi Li, Siheng Li, Xiaodong Li, Shitao Pan, Mengguan Zheng, Wang Luo, Kai Ma, Ziyao Gao, Yanbiao Chang, Jiaxing Ren, Hailong Guo, Wenfang Torres-Sospedra, Joaquin Pisa56124 Italy Electronics and Telecommunications Research Institute Daejeon34129 Korea Republic of Beijing University of Posts and Telecommunications School of Computer Science National Pilot Software Engineering School Beijing100876 China Chinese Academy of Sciences Beijing Key Laboratory of Mobile Computing and Pervasive Device Institute of Computing Technology Beijing100190 China Universitat Oberta de Catalunya Faculty of Computer Sciences Multimedia and Telecommunication Barcelona08035 Spain Arganda del Rey28500 Spain Huawei Technologies Company Ltd. Shenzhen100015 China IMEC-WAVES/Ghent University Department of Information Technology Gent9052 Belgium Nanjing University of Aeronautics and Astronautics College of Automation Nanjing210016 China University of Extremadura Badajoz06006 Spain University of Trás-os-Montes and Alto Douro Department of Engineering School of Sciences and Technology Vila Real5000-801 Portugal Universidade Do Minho Centro Algoritmi Guimarães4800-058 Portugal Ame Department of the University Gustave Eiffel Geoloc Laboratory Bouguenais44344 France Chinese Academy of Sciences Aerospace Information Research Institute Beijing100094 China Wuhan University Gnss Research Center Wuhan430072 China AutoNavi Software Company Ltd. China Fraunhofer Institute for Integrated Circuits Iis Fraunhofer Iis Nuremberg90411 Germany Erlangen91058 Germany Graz University of Technology Christian Doppler Laboratory for Location-Aware Electronic Systems Graz8010 Austria Institute of Software Chinese Academy of Sciences Beijing100190 China Purple Mountain Laboratories Pervasive Communication Research Center Nanjing210000 China Beijing University of Posts and Telecommunications Beijing100876 China

Indoor positioning is a thriving research area, which is slowly gaining market momentum. Its applications are mostly customized, ad hoc installations;ubiquitous applications analogous to Global Navigation Satellite System for outdoors are not available because of the lack of generic platforms, widely accepted standards and interoperability protocols. In this context, the indoor positioning and indoor navigation (IPIN) competition is the only long-term, technically sound initiative to monitor the state of the art of real systems by measuring their performance in a realistic environment. Most competing systems are pedestrian-oriented and based on the use of smartphones, but several competing tracks were set up, enabling comparison of an array of technologies. The two IPIN competitions described here include only off-site tracks. In contrast with on-site tracks where competitors bring their systems on-site - which were impossible to organize during 2021 and 2022 - in off-site tracks competitors download prerecorded data from multiple sensors and process them using the EvaalAPI, a real-time, web-based emulation interface. As usual with IPIN competitions, tracks were compliant with the EvAAL framework, ensuring consistency of the measurement procedure and reliability of results. The main contribution of this work is to show a compilation of possible indoor positioning scenarios and different indoor positioning solutions to the same problem. © 2023 CCBY.

关键词： Smartphones

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：