检索结果-内蒙古大学图书馆

您好，读者！请登录

内蒙古大学图书馆

首页
概况
党建
资源
服务
科研支持
- 论文收录引用证明
- 科技查新
知识产权
档案馆
帮助

咨询与建议

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

您的常用邮箱：*

您的手机号码：*

问题描述：

当前已输入0个字，您还可以输入200个字

全部搜索
期刊论文
图书
学位论文
标准
纸本馆藏
外文资源发现
数据库导航
超星发现

高级检索

时间限定

出版年份：

文献类型

图书期刊文献学位论文多媒体

馆藏选择

电子馆藏纸本馆藏

核心期刊

全部期刊 SCI 收录期刊 SSCI 收录期刊 EI 收录期刊 CSCD 收录期刊 CSSCI 收录期刊

语言

中文英文

文献类型

期刊文献图书学位论文标准纸本馆藏

帮助

文字说明：

T=题名（书名、题名），A=作者（责任者），K=主题词，P=出版物名称，PU=出版社名称，O=机构（作者单位、学位授予单位、专利申请人），L=中图分类号，C=学科分类号，U=全部字段，Y=年（出版发行年、学位年度、标准发布年）

检索规则说明：

AND代表“并且”；OR代表“或者”；NOT代表“不包含”；(注意必须大写,运算符两边需空一格)

检索范例：

范例一：(K=图书馆学 OR K=情报学) AND A=范并思 AND Y=1982-2016
范例二：P=计算机应用与软件 AND (U=C++ OR U=Basic) NOT K=Visual AND Y=2011-2016

分类表

所选分类

>> <<

限定检索结果

文献类型

2,235 篇 会议
56 篇 期刊文献
3 册 图书
1 篇 学位论文

馆藏范围

2,295 篇 电子文献
0 种 纸本馆藏

日期分布

学科分类号

1,651 篇 工学
- 1,194 篇 计算机科学与技术...
- 704 篇 电气工程
- 507 篇 软件工程
- 478 篇 信息与通信工程
- 191 篇 控制科学与工程
- 101 篇 电子科学与技术（可...
- 44 篇 航空宇航科学与技...
- 43 篇 机械工程
- 31 篇 生物工程
- 30 篇 石油与天然气工程
- 30 篇 交通运输工程
- 25 篇 仪器科学与技术
- 25 篇 动力工程及工程热...
- 21 篇 建筑学
- 20 篇 生物医学工程（可授...
- 19 篇 土木工程
- 18 篇 光学工程
- 17 篇 材料科学与工程（可...
265 篇 理学
- 133 篇 数学
- 78 篇 物理学
- 43 篇 系统科学
- 40 篇 生物学
- 17 篇 统计学（可授理学、...
187 篇 管理学
- 152 篇 管理科学与工程(可...
- 56 篇 工商管理
- 36 篇 图书情报与档案管...
75 篇 医学
- 51 篇 基础医学(可授医学...
- 33 篇 临床医学
27 篇 经济学
- 27 篇 应用经济学
25 篇 教育学
- 24 篇 教育学
15 篇 法学
8 篇 军事学
3 篇 农学
2 篇 文学
1 篇 艺术学

主题

171 篇 computer archite...
167 篇 programming
90 篇 hardware
86 篇 network architec...
80 篇 linear programmi...
71 篇 neural networks
68 篇 protocols
64 篇 network topology
63 篇 optimization
58 篇 computational mo...
52 篇 deep learning
52 篇 computer network...
51 篇 cloud computing
50 篇 routing
46 篇 network-on-chip
45 篇 application soft...
42 篇 switches
42 篇 dynamic programm...
40 篇 throughput
40 篇 parallel program...

机构

7 篇 univ calif berke...
6 篇 xidian univ stat...
5 篇 natl res univ hi...
5 篇 deakin univ sch ...
5 篇 swiss fed inst t...
5 篇 mit cambridge ma...
5 篇 tsinghua univ pe...
5 篇 southeast univ n...
5 篇 dalian univ tech...
5 篇 russian acad sci...
4 篇 pg demidov yaros...
4 篇 georgia inst tec...
4 篇 univ chinese aca...
4 篇 shanghai jiao to...
4 篇 peking universit...
4 篇 pacific northwes...
4 篇 univ calif san d...
4 篇 kings coll londo...
3 篇 columbia univers...
3 篇 univ estadual ca...

作者

10 篇 carle georg
6 篇 magedanz thomas
6 篇 emmerich paul
5 篇 zhao bo
5 篇 benini luca
5 篇 georg carle
4 篇 zhang tao
4 篇 wang lei
4 篇 garcia jordi
4 篇 dongarra jack
4 篇 hoefler torsten
4 篇 li tao
4 篇 turdakov denis
4 篇 luca foschini
4 篇 kellerer wolfgan...
4 篇 vetter jeffrey s...
4 篇 liu derong
4 篇 chatha karam s.
4 篇 li ming
3 篇 blum niklas

语言

2,186 篇 英文
97 篇 其他
11 篇 中文
1 篇 西班牙文
1 篇 土耳其文

检索条件"任意字段=IEEE Conference on Open Architectures and Network Programming"

共 2295 条记录，以下是801-810 订阅

全选清除本页清除全部题录导出标记到"检索档案"

详细简洁

排序：

AdvRush: Searching for Adversarially Robust Neural architectures

AdvRush: Searching for Adversarially Robust Neural Architect...

引用

International conference on Computer Vision (ICCV)

作者： Jisoo Mok Byunggook Na Hyeokjun Choe Sungroh Yoon Seoul National University Seoul South Korea ASRI INMC ISRC and Institute of Engineering Research Seoul National University

ISBN: (纸本)9781665428132

Deep neural networks continue to awe the world with their remarkable performance. Their predictions, however, are prone to be corrupted by adversarial examples that are imperceptible to humans. Current efforts to improve the robustness of neural networks against adversarial examples are focused on developing robust training methods, which update the weights of a neural network in a more robust direction. In this work, we take a step beyond training of the weight parameters and consider the problem of designing an adversarially robust neural architecture with high intrinsic robustness. We propose AdvRush, a novel adversarial robustness-aware neural architecture search algorithm, based upon a finding that independent of the training method, the intrinsic robustness of a neural network can be represented with the smoothness of its input loss landscape. Through a regularizer that favors a candidate architecture with a smoother input loss landscape, AdvRush successfully discovers an adversarially robust neural architecture. Along with a comprehensive theoretical motivation for AdvRush, we conduct an extensive amount of experiments to demonstrate the efficacy of AdvRush on various benchmark datasets. Notably, on CIFAR-10, AdvRush achieves 55.91% robust accuracy under FGSM attack after standard training and 50.04% robust accuracy under AutoAttack after 7-step PGD adversarial training.

关键词： Training Deep learning Computer vision Neural networks Computer architecture Benchmark testing Linear programming

来源：评论

学校读者我要写书评

暂无评论

Domain adaptive object detection with generative adversarial network

Domain adaptive object detection with generative adversarial...

引用

2020 International conference on Internet of Things and Intelligent Applications, ITIA 2020

作者： Huang, Xiaohua Huang, Wei Li, Yi Shao, Xiuyan Li, Hang Yu, Xiang Han, Lei Nanjing Institute of Technology School of Computer Engineering Nanjing China

ISBN: (纸本)9781728193014

Domain adaptive object detection has emerged to alleviate the lack of massive amounts of labeled data in the target field. Currently, Generative Adversarial network (GAN) has been exhibited its benefits to the Faster R-CNN for some specific application. However, it brings up an open question that GAN still has flexibility and robustness in more generic scenarios. Thus, this paper aims to extensively evaluate its efficiency of the GAN on more generic domain-adaptive object detection. More specifically, it presents four generic domain-adaptive object detection with GAN architectures, containing Faster R-CNN with CycleGAN, Faster R-CNN with DualGAN, RetinaNet with CycleGAN, and RetinaNet with DualGAN. Extensive experiment results demonstrate that GAN-derived model makes significant contribution and consistent improvements in two domain shift scenarios for domain-adaptive object detection. Additionally, comparing with the state-of-the-art methods, domain-adaptive object detection with GAN has been validated its ability of generalization and robustness in more challenging scenarios. © 2020 ieee.

关键词： Generative adversarial networks

来源：评论

学校读者我要写书评

暂无评论

RED-SEA: network Solution for Exascale architectures

RED-SEA: Network Solution for Exascale Architectures

引用

Euromicro Symposium on Digital System Design

作者： Andrea Biagioni Paolo Cretaro Ottorino Frezza Francesca Lo Cicero Alessandro Lonardo Michele Martinelli Pier Stanislao Paolucci Elena Pastorelli Francesco Simula Matteo Turisini Piero Vicini Roberto Ammendola Pascale Bernier-Bruna Claire Chen Said Derradji Stephane Guez Pierre-Axel Lagadec Gregoire Pichon Etienne Walter Gaetan De Gassowski Matthieu Hautreaux Stephane Mathieu Gilles Moreau Marc Perache Hugo Taboada Torsten Hoefler Timo Schneider Matteo Barnaba Giuseppe Piero Brandino Francesco De Giorgi Matteo Poggi Iakovos Mavroidis Yannis Papaefstathiou Nikolaos Tampouratzis Benjamin Kalisch Ulrich Krackhardt Mondrian Nuessle Pantelis Xirouchakis Vangelis Mageiropoulos Michalis Gianioudis Harisis Loukas Aggelos Ioannou Nikos Kallimanis Nikos Chrysos Manolis Katevenis Wolfang Frings Dominik Gottwald Felime Guimaraes Max Holicki Volker Marx Yannik Muller Carsten Clauss Hugo Falter Xu Huang Jennifer Lopez Barillao Thomas Moschny Simon Pickartz Francisco J. Alfaro Jesus Escudero-Sahuquillo Pedro Javier Garcia Francisco J. Quiles Jose L. Sanchez Adrián Castelló Jose Duro Maria Engracia Gomez Enrique Quintana Julio Sahuquillo Eugenio Stabile INFN Sezione di Roma Italy INFN Sezione di Roma Tor Vergata Italy Atos France CEA France ETH Zürich Switzerland Exact Lab Italy Exapsys Greece Extoll Germany Forth Greece Julich Research Centre Germany ParTec Germany University of Castilla-La Mancha Spain Universidad Politecnica de Valencia Spain

ISBN: (数字)9781665474047

ISBN: (纸本)9781665474054

In order to enable Exascale computing, next generation interconnection networks must scale to hundreds of thousands of nodes, and must provide features to also allow the HPC, HPDA, and AI applications to reach Exascale, while benefiting from new hardware and software trends. RED-SEA will pave the way to the next generation of European Exascale interconnects, including the next generation of BXI, as follows: (i) specify the new architecture using hardware-software co-design and a set of applications representative of the new terrain of converging HPC, HPDA, and AI; (ii) test, evaluate, and/or implement the new architectural features at multiple levels, according to the nature of each of them, ranging from mathematical analysis and modeling, to simulation, or to emulation or implementation on FPGA testbeds; (iii) enable seamless communication within and between resource clusters, and therefore development of a high-performance low latency gateway, bridging seamlessly with Ethernet; (iv) add efficient network resource management, thus improving congestion resiliency, virtualization, adaptive routing, collective operations; (v) open the interconnect to new kinds of applications and hardware, with enhancements for end-to-end network services - from programming models to reliability, security, low- latency, and new processors; (vi) leverage open standards and compatible APIs to develop innovative reusable libraries and Fabrics management solutions.

关键词： Analytical models Adaptation models Routing Hardware Software Security Artificial intelligence

来源：评论

学校读者我要写书评

暂无评论

Quantifying Influential Communities in Granular Social networks Using Fuzzy Theory 20th

Quantifying Influential Communities in Granular Social Netwo...

引用

20th International conference on Computational Science and Its Applications (ICCSA)

作者： Kumari, Anisha Behera, Ranjan Kumar Shukla, Abhishek Sai Sahoo, Satya Prakash Misra, Sanjay Rath, Sanatanu Kumar Veer Surendra Sai Univ Technol Dept CSE Burla Odisha India PwC Serv Delivery Ctr Bengaluru India Covenant Univ Dept Elect & Informat Engn Ota 1023 Nigeria Natl Inst Technol Dept CSE Rourkela India

ISBN: (纸本)9783030588113;9783030588106

Community detection and centrality analysis in social networks are identified as pertinent research topics in the field of social network analysis. Community detection focuses on identifying the subgraphs (communities) which have dense connections within it as compared to outside of it, whereas centrality analysis focuses on identifying significant nodes in a social network based on different aspects of importance. A number of research works have focused on identifying community structure in large-scale network. However, very less effort has been emphasized on quantifying the influence of the communities. In this paper, group of nodes that are likely to form communities are first uncovered and then they are quantified based on the influencing ability in the network. Identifying exact boundaries of communities are quite challenging in large scale network. The major contribution in this paper is to develop a model termed as FRC-FGSN (Fuzzy Rough Communities in Fuzzy Granular Social network), to identify the communities with the help of fuzzy and rough set theory. The proposed model is based on a idea that, the degree of belongingness a node in a community may not be binary but can be models through fuzzy membership. The second contribution is to quantifying the influence of the community using eigenvector centrality. In order to improve the scalability, several steps in the proposed model have been implemented using map-reduce programming paradigm in a cluster-computing framework like Hadoop. Comparative analysis of FRC-FGSN with other parallel algorithms as available in the literature has been presented to demonstrate the scalability and effectiveness of the algorithm.

关键词： Influential community Eigenvector centrality Granular social network Cluster-computing

来源：评论

学校读者我要写书评

暂无评论

Multivariate Prediction of Correct Lane for Autonomous Electric Vehicle Using Deep Learning Models 8

Multivariate Prediction of Correct Lane for Autonomous Elect...

引用

8th International conference on Control, Mechatronics and Automation, ICCMA 2020

作者： Setta, Islam G. Abou Shehata, Omar M. Awad, Mohammed A. Ain Shams University Faculty of Engineering Department of Design and Production Engineering Cairo Egypt Ain Shams University Faculty of Engineering Department of Mechatronics Engineering Cairo Egypt

ISBN: (纸本)9781728192109

The target of a self-driving car researches is to build a better autonomous driver. We control the car to be able to drive itself without falling off the track using appropriate accelerating and braking. Using udacity as an open source simulator to depict a real-time environment. With the help of a model trained by deep neural networks, we mimic the driving behavior of a human on the simulator (Behavioral Cloning) [1]. We use Keras and a high-level API that uses TensorFlow as the backend for dataflow programming. Keras provides sequential models for building a linear stack of network layers. CNN models (Neural network layers were optimized in series combinations of Time-Distributed Convolution Layers, Maxpooling, Flatten, Dense, Dropout and so on) are experimented for reaching the best model of control. Finally, we concluded that model 2 performed the best at the end of 60 epochs with the least loss = 0.007. © 2020 ieee.

关键词： network layers

来源：评论

学校读者我要写书评

暂无评论

Revenue-Sharing based Computation-Resource Allocation for Mobile Blockchain

Revenue-Sharing based Computation-Resource Allocation for Mo...

引用

39th ieee International conference on Computer Communications (ieee INFOCOM)

作者： Wu, Yuan Xu, Xu Qian, Liping Ji, Bo Shi, Zhiguo Jia, Weijia Univ Macau State Key Lab Internet Things Smart City Taipa Macau Peoples R China Zhejiang Univ Technol Coll Informat Engn Hangzhou Peoples R China Temple Univ Dept Comp & Informat Sci Philadelphia PA 19122 USA Zhejiang Univ Coll Informat Sci & Elect Engn Hangzhou Peoples R China

ISBN: (数字)9781728186955

ISBN: (纸本)9781728186955

In this paper, we investigate the revenue-sharing based computation-resource allocation for mobile Blockchain, in which conventional mobile devices (i.e., the edge-computing users, EUs) can acquire computation-resources from the edge-server (ES) for increasing their chances of winning the mining game in Blockchain. Meanwhile, as a compensation to the ES, the EUs adopt the revenue-sharing mechanism by sharing parts of their respective rewards to the ES. We formulate a joint optimization of the ES's computation-resource allocation to the EUs and the EUs' revenue-sharing to the ES, with the objective of maximizing the system-reward of all EUs and the ES. Despite the non-convexity of the joint optimization problem, we propose an algorithm based on the cyclic block coordinate descent (CBCD) to solve the problem. Our algorithm decouples the original problem into two subproblems and alternatively optimizes the EUs' revenue-sharing and ES's computation-resource allocation until reaching convergence. For each subproblem, we also propose an efficient algorithm for solving it. Numerical results are provided to validate the effectiveness and efficiency of our proposed algorithms, as well as the performance advantage of our proposed revenue-sharing based computation-resource allocation for mobile Blockchain.

关键词： Resource management Optimization Games Edge computing Computational modeling Linear programming

来源：评论

学校读者我要写书评

暂无评论

Meta-ensemble based classifier approach for attack detection in multi-tenant distributed systems

Meta-ensemble based classifier approach for attack detection...

引用

2020 International conference for Emerging Technology, INCET 2020

作者： Patil, Pravin Ingle, Rajesh Pune Institute of Computer Technology Dept. of Computer Engineering Maharashtra India

ISBN: (数字)9781728162218

ISBN: (纸本)9781728162218

Distributed systems in a network have always been vulnerable to cyber attacks due to exposure of vulnerabilities in shared memories, configurations, and network access. Being co-holders in the same server provides attackers with an opportunity to track the activities of other users and accordingly make an attack when the security of the latter is in peril. Traditionally, the effort has been to build full proof network architectures free from any threats and attacks. However, owing to its open-ended nature, it is impossible to come up with a completely secure architecture. A common factor that can always be observed irrespective of the type of attacks is the specific values and configuration of the system through which the attack is instantiated. The rise in the use of machine learning algorithms and data collection facilities provides us with an opportunity to use network parameter values for modeling any anomaly and subsequent possibility of attacks. In this paper, we propose an ensemble-based meta classifier for predicting the probability of attack instantiation based on certain system parameter values. We also contribute to the research in this area by creating a dataset for analysis purpose. Efforts are taken by us to tackle the class imbalance problem often found in this domain where the instances of attack being carried out are rare. The results obtained by us on our data demonstrate that machine learning coupled with ensembling can be used as a good aid for network attacks analysis. While increased measures are being taken to improve security in the digital space, machine learning algorithms can be used to analyze any aberrant behavior left unchecked. © 2020 ieee.

关键词： network architecture

来源：评论

学校读者我要写书评

暂无评论

Planning of Soft open Point Integrated with ESS in Active Distribution network

Planning of Soft Open Point Integrated with ESS in Active Di...

引用

ieee Asia Power and Energy Engineering conference (APEEC)

作者： Zijia Ding Chunyi Wang Fei Wang Liang Feng Guangxiao Li Zhendong Xu Jining Power Supply Company of State Grid Shandong electric power Jining Shandong China State Grid Shandong electric power company Jinan Shandong China College of Electrical Engineering and Automation Shandong University of Science and Technology Qingdao Shandong China

ISBN: (纸本)9781665425513;9781665430791

With the increasing penetration of renewable energy in the distribution network, a large number of distributed generation access network, making the traditional passive network into active network, and changing the power flow distribution of radial network. The Soft open Point Integrated with ESS (ESOP) can regulate the network power flow from two dimensions of time and space, and improve the economy of system operation. Due to the high investment cost and complex model of Soft open Point Integrated with ESS, considering the time sequence characteristics of load and the fluctuation of distributed generation, the capacity of converter and energy storage part should be reasonably planned to achieve the ideal optimization effect with minimum economic loss. First of all, the soft open point integrated with ESS is modeled. Taking the minimum annual comprehensive cost as the objective function, the second-order cone programming model is established, which is solved by commercial solver and verified by the modified PG&E 69 node example. The results show that the economic efficiency of distribution system can be effectively improved by selecting reasonable planning scheme.

关键词： Economics Analytical models Uncertainty Systems operation Distribution networks Planning Distributed power generation

来源：评论

学校读者我要写书评

暂无评论

Changes in Intent: Behavioral Predictions of Distributed SDN Controller Reconfiguration

Changes in Intent: Behavioral Predictions of Distributed SDN...

引用

ieee International conference on Software Reliability Engineering Workshops (ISSRE Wksp)

作者： Yuming Wu Nishok Narasimha Mohanasamy Lalita Jagadeesan Muntasir Raihan Rahman Univ. of Illinois Urbana-Champaign Nokia Bell Labs Microsoft

ISBN: (纸本)9781665426046

Intent-based programming enables software-defined networks (SDN) to be able to dynamically reconfigure themselves through automatic intent recomputation in response to network events, such as host mobility. This allows SDN to be used as a platform for new technologies such as swarms of drones in data-driven agriculture. At the same time, this dynamicity results in SDN networks having a very large state space - whose size is further exacerbated when SDN controllers are distributed for reliability and scalability. This renders infeasible comprehensive testing or verification of network performance prior to deployment, necessitating the use of monitoring at run-time, together with associated abortive or healing actions to ensure reliability. However, as intent recomputation time can vary significantly based on the underlying network topologies, it is very difficult to experimentally determine the boundary between normal expected performance and anomalous performance at scale, and hence to specify when these actions should take place. In this paper, we demonstrate the use of machine learning to automatically learn intent recomputation performance; the resulting predictions can be used as input into the specification of run-time monitors and the determination of associated reliability mitigations. More specifically, we describe our proof-of-concept case study on using linear regression to predict the expected time for intent recomputation due to host mobility on the distributed ONOS open-source SDN controller.

关键词： network topology Scalability Linear regression Machine learning programming Software reliability Monitoring

来源：评论

学校读者我要写书评

暂无评论

Piranha: Reducing Feature Flag Debt at Uber 42

Piranha: Reducing Feature Flag Debt at Uber

引用

42nd ACM/ieee International conference on Software Engineering - Companion Proceedings (ICSE-Companion) / 42nd ACM/ieee International conference on Software Engineering - Software Engineering in Practice (ICSE-SEIP)

作者： Ramanathan, Murali Krishna Clapp, Lazaro Barik, Rajkishore Sridharan, Manu Uber Technol Inc New York NY 10001 USA Univ Calif Riverside Riverside CA 92521 USA

ISBN: (纸本)9781450371230

Feature flags are commonly used in mobile app development and can introduce technical debt related to deleting their usage from the codebase. This can adversely affect the overall reliability of the apps and increase their maintenance complexity. Reducing this debt without imposing additional overheads on the developers necessitates the design of novel tools and automated workflows. In this paper, we describe the design and implementation of PIRANHA, an automated code refactoring tool which is used to automatically generate differential revisions (a.k.a diffs) to delete code corresponding to stale feature flags. PIRANHA takes as input the name of the flag, expected treatment behavior, and the name of the flag's author. It analyzes the ASTs of the program to generate appropriate refactorings which are packaged into a diff. The diff is assigned to the author of the flag for further processing, who can land it after performing any additional refactorings. We have implemented PIRANHA to delete code in Objective-C, Java, and Swift programs, and deployed it to handle stale flags in multiple Uber apps. We present our experiences with the deployment of PIRANHA from Dec 2017 to May 2019, including the following highlights: (a) generated code cleanup diffs for 1381 flags (17% of total flags), (b) 65% of the diffs landed without any changes, (c) over 85% of the generated diffs compile and pass tests successfully, (d) around 80% of the diffs affect more than one file, (e) developers process more than 88% of the generated diffs, (f) 75% of the generated diffs are processed within a week, and (g) PIRANHA diffs have been interacted with by similar to 200 developers across Uber. Piranha is available as open source at https://***/uber/piranha.

关键词： C (programming language)

来源：评论

学校读者我要写书评

暂无评论

没有更多数据了...

全选清除本页清除全部题录导出标记到“检索档案”

共230页 << < 77 78 79 80 81 82 83 84 85 86 > >>

检索报告对象比较合并检索0

隐藏清空

合并搜索

回到顶部

执行限定条件

内容：

评分：

请选择保存的检索档案：

请选择收藏分类：

订阅名称：

通借通还

温馨提示：

图书名称：

借书校区：

取书校区：

手机号码：

邮箱地址：

一卡通帐号：

电话和邮箱必须正确填写，我们会与您联系确认。

联系人：

所在院系：

联系邮箱：

联系电话：

内蒙古自治区呼和浩特市赛罕区大学西街235号邮编: 010021

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：