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

2,407 篇 会议
1,329 篇 期刊文献
37 册 图书

馆藏范围

3,773 篇 电子文献
0 种 纸本馆藏

日期分布

学科分类号

2,299 篇 工学
- 1,633 篇 计算机科学与技术...
- 1,341 篇 软件工程
- 622 篇 信息与通信工程
- 365 篇 控制科学与工程
- 300 篇 生物工程
- 288 篇 电气工程
- 229 篇 生物医学工程（可授...
- 220 篇 电子科学与技术（可...
- 180 篇 光学工程
- 160 篇 机械工程
- 160 篇 网络空间安全
- 136 篇 化学工程与技术
- 129 篇 安全科学与工程
- 115 篇 动力工程及工程热...
- 107 篇 交通运输工程
- 104 篇 核科学与技术
- 102 篇 仪器科学与技术
1,346 篇 理学
- 602 篇 数学
- 473 篇 物理学
- 327 篇 生物学
- 214 篇 统计学（可授理学、...
- 154 篇 化学
- 113 篇 系统科学
691 篇 管理学
- 432 篇 管理科学与工程(可...
- 293 篇 图书情报与档案管...
- 153 篇 工商管理
218 篇 医学
- 161 篇 临床医学
- 160 篇 基础医学(可授医学...
- 111 篇 公共卫生与预防医...
129 篇 法学
- 107 篇 社会学
67 篇 经济学
65 篇 农学
36 篇 教育学
34 篇 文学
20 篇 军事学
5 篇 艺术学
1 篇 哲学

主题

172 篇 accuracy
141 篇 deep learning
105 篇 feature extracti...
100 篇 hadron colliders
98 篇 machine learning
89 篇 computational mo...
88 篇 training
84 篇 convolutional ne...
73 篇 real-time system...
66 篇 support vector m...
63 篇 predictive model...
61 篇 artificial intel...
56 篇 optimization
53 篇 internet of thin...
49 篇 reliability
46 篇 genetic algorith...
46 篇 cloud computing
46 篇 data models
44 篇 semantics
44 篇 security

机构

132 篇 yerevan physics ...
129 篇 national and kap...
129 篇 centro brasileir...
129 篇 istanbul technic...
127 篇 university of sp...
127 篇 indian institute...
126 篇 universidad iber...
125 篇 brunel universit...
124 篇 università di to...
124 篇 academy of scien...
124 篇 charles universi...
124 篇 infn sezione di ...
123 篇 department of ph...
122 篇 zhejiang univers...
122 篇 irfu cea univers...
121 篇 infn sezione di ...
120 篇 university of de...
120 篇 department of ph...
118 篇 imperial college...
118 篇 rwth aachen univ...

作者

125 篇 m. lu
95 篇 g. tonelli
95 篇 d. barney
95 篇 l. valencia palo...
95 篇 t. liu
95 篇 c. hensel
95 篇 a. garcia-bellid...
95 篇 a. steen
95 篇 n. cartiglia
95 篇 d. eliseev
94 篇 a. babaev
94 篇 v. karjavine
93 篇 n. colino
93 篇 f. moortgat
92 篇 b. clerbaux
91 篇 g. sultanov
91 篇 a. mallampalli
91 篇 m. a. ciocci
91 篇 k. lamichhane
91 篇 s. maselli

语言

3,148 篇 英文
584 篇 其他
45 篇 中文
2 篇 日文
1 篇 德文
1 篇 法文

检索条件"机构=Computer Science Engineering and Application"

共 3773 条记录，以下是1131-1140 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：

Exploiting Convolutional Neural Networks for Automated Pathology Image Classification

Exploiting Convolutional Neural Networks for Automated Patho...

引用

Optimization Computing and Wireless Communication (ICOCWC), International Conference on

作者： Sunil Sharma C Menaka Akhilendra Pratap Singh Department of Computer Science & Application Vivekananda Global University Jaipur India Department of Computer Science and Information Technology Jain (Deemed to be University) Bangalore India Maharishi School of Engineering & Technology Maharishi University of Information Technology Uttar Pradesh India

Convolutional neural networks (CNNs) are a deep mastering method for the computerized pathology photograph category. With the improvement of superior imaging techniques, the quantity of virtual and representable pathology pix has increased notably. Automatic picture evaluation has become increasingly crucial to exploit those photographs for clinical selections. CNNs have attracted huge interest and were established to be very powerful for automated photograph classification and object detection. The improvement of deep getting-to-know based on Convolutional Neural Networks (CNNs) for computerized pathology photo classes has been a focal point of research in current years. This paper critiques the recent advances in CNNs in automatic pathology image type. The key architectures and algorithms for CNNs are summarized, and their capability applicability in pathology picture classification is discussed. This overview also introduces the maximum hit CNN methods that have been proposed and have proven promising consequences in pathology photograph category duties. The paper concludes with a dialogue of future research directions in this area. Convolutional neural networks (CNNs) are a deep mastering method for the computerized pathology photograph category. With the improvement of superior imaging techniques, the quantity of virtual and representable pathology pix has increased notably. To exploit those photographs for clinical selections, automatic picture evaluation has grown to be an increasingly number of crucial. CNNs have attracted huge interest and were established to be very powerful for automated photograph classification and object detection. The improvement of deep getting-to-know based on Convolutional Neural Networks (CNNs) for computerized pathology photo classes has been a focal point of research in current years. This paper critiques the recent advances in CNNs in automatic pathology image type. The key architectures and algorithms for CNNs are summarized,

关键词：

来源：评论

学校读者我要写书评

暂无评论

Analysis and Classification of Biomedical Data Using Machine Learning Techniques 3rd

Analysis and Classification of Biomedical Data Using Machine...

引用

3rd International Conference on Information and Communication Technology and applications, ICTA 2020

作者： Panda, Sujata Maringanti, Hima Bindu Department of Computer Science Devine Institute of Engineering and Technology Baripada Odisha India Department of Computer Application North Orissa University Baripada Odisha India

ISBN: (纸本)9783030691424

Breast cancer research has been the center of discussion on health information technology in recent years, as it is the second largest cause of cancer deaths in women. A biopsy in which tissue is microscopically extracted and analyzed will be used for the detection of breast cancer. The cancer cells are either categorized as cancer or non-cancer. There are various methods for classifying and predicting breast cancer. The proposed work uses a breast cancer dataset from Wisconsin (Diagnostic). The data collection used to track the effectiveness of different machine learning approaches with respect to main parameters including accuracy, F1-score, specificity and recall. The three basic classification models in this paper are i.e., Naïve Bayes, KNN, Decision Tree was used to forecast cancer. The comparative tests show that the proposed Naïve Bayes classifier gives the accuracy of 98.1%, f1 score of 98.3%, specificity of 97.5%, recall of 98.3%. © 2020, Springer Nature Switzerland AG.

关键词： Decision trees

来源：评论

学校读者我要写书评

暂无评论

Utilizing Deep Learning in Pre-Clinical and Clinical Diagnosis of Peripheral Neuropathies

Utilizing Deep Learning in Pre-Clinical and Clinical Diagnos...

引用

Optimization Computing and Wireless Communication (ICOCWC), International Conference on

作者： Akhilendra Pratap Singh Vikas Kumar Kharbas Prerna Mahajan Maharishi School of Engineering & Technology Maharishi University of Information Technology Uttar Pradesh India Department of Computer Science & Application Vivekananda Global University Jaipur India Department of Computer Science and Information Technology Jain (Deemed to be University) Bangalore India

Peripheral neuropathies are a group of problems that affect the peripheral frightened machine, often leading to a spread of symptoms and impairments. Diagnosis of these situations is frequently imprecise and time-consuming, leading to delays in remedy. Deep studying techniques provide the capacity to automate and enhance the analysis of peripheral neuropathies. Through deep gaining knowledge, clinicians can obtain more excellent correct diagnoses based on enter from MRI pics, photographs of nerve biopsies, or different imaging facts. Moreover, deep studying may be used to create characteristic vectors from different medical features and EEGs that may facilitate the popularity of signs and symptoms and diagnoses extra speedy and more appropriate than traditional methods. This paper explores the capacity of deep learning to accurately diagnose and stratify peripheral neuropathies in pre-scientific and medical settings. It gives a top-level view of contemporary studies on deep getting-to-know strategies for spotting signs and symptoms and diagnosing peripheral neuropathies. Similarly, the paper outlines capacity applications and blessings of deep studying for diagnosing peripheral neuropathies and discusses areas of destiny studies. The software of deep mastering in the pre-medical and clinical prognosis of peripheral neuropathies has been increasingly studied in latest years. Deep mastering fashions, consisting of convolutional neural networks, have shown promising effects in analyzing electromyography (EMG) alerts for the early detection, quantification, and class of peripheral neuropathies, complementing and, in a few cases surpassing conventional diagnostic methods. Moreover, those methods have been advanced as they should be detected and differentiated between myopathic and neuropathic abnormalities and muscle activity. Those algorithms can also distinguish between the diverse kinds of peripheral neuropathies and are potentially useful for early detection and reme

关键词：

来源：评论

学校读者我要写书评

暂无评论

Presentation Analysis of Reasoning Radio-Based Routing Protocols in Wireless Mesh Networks

Presentation Analysis of Reasoning Radio-Based Routing Proto...

引用

Optimization Computing and Wireless Communication (ICOCWC), International Conference on

作者： Ritesh Kumar Vikas Kumar Kharbas Deepak Mehta Maharishi School of Engineering & Technology Maharishi University of Information Technology Uttar Pradesh India Department of Computer Science & Application Vivekananda Global University Jaipur India Department of Computer Science and Information Technology Jain (Deemed to be University) Bangalore India

Reasoning radio-based total routing protocols present a promising technique for permitting powerful conversation in wi-fi mesh networks. By using the spectrum sensing capabilities of Reasoning radio, routers can intelligently pick out and pick out spectrum assets to ahead records, thereby allowing for improved network throughput and reliability. In this paper, we carry out a comprehensive Presentation evaluation of routing protocols primarily based on Reasoning radio in wi-fi mesh networks. Mainly, we Presentation metrics including packet shipping fee, latency, jitter, and energy Presentation. We examine various routing protocols from an empirical and theoretical angle and speak about the strengths and weaknesses of every technique. Subsequently, our consequences provide insights into the capability advantages and tradeoffs of Reasoning radio-based routing protocols in wireless mesh networks, offering practical steerage to designers and engineers within the subject.

关键词：

来源：评论

学校读者我要写书评

暂无评论

An Optimized Grid Computing based Feature Selection approaches from Brain Image dataset using Pretrained models

An Optimized Grid Computing based Feature Selection approach...

引用

Advances in Signal Processing, Power, Communication, and Computing (ASPCC), IEEE International Conference on

作者： Sradhanjali Nayak Pradyut Kumar Biswal Pravakar Mishra Sateesh Kumar Pradhan Dept. of Computer Science NIIS Institute of Business Administration Bhubaneswar India Dept. of ETC IIIT Bhubaneswar Bhubaneswar India Dept. of Computer Science and Engineering NIIS Institute Of Business Administration Bhubaneswar India Dept. of Computer Science and Application Utkal University Bhubaneswar India

ISBN: (数字)9798350355093

ISBN: (纸本)9798350355109

The outcome of simulated experiments expressed the efficiency of grid-based algorithm in the domain of image processing in the context of Brain MRI Images for Tumor Detection. It provides a faster approach in detecting object and achieving higher rate of detection in comparison with existing algorithms for the similar purpose. The foremost goal of this work is improving the rate of detection by using grid based feature fusion approach with Genetic Algorithm(GA), Particle Swarm Optimization(PSO) and Scalp Swarm Optimization Algorithm. This technique produces efficient result due to hybrid fusion of gridded Images and optimization for exhaustive and precise image analysis. In the initial phase Each image is segmented into 4 grids. Pretrained models like Inception-V2, Resnet 50, Mobnetv2, VGG-16 are used to extract features before and after the images are gridded. The extracted features are analysed with classifiers such as Decision tree, Support vector Machine, Multiplayer and Self Attention Transformer that not only chooses the best set of features as well as best feature extractor. Among all these models the VGG-16 gives best result in terms of Accuracy, sensitivity, specificity and F-score. Hence VGG-16 is utilized as evaluation functions in the optimization Algorithms. The performance of the approach is measured by the values produced against the terms as precision, Recall, F-score, and accuracy rate. In the first phase of iteration, features extracted from each grid are assigned with initial weight. Optimization algorithms are used for optimizing the weight values in the combined features to bring best accuracy ratio. Grid based segmentation of Image stabilize the computation time thereby reduces the time complexity. Weighted sum Scalp Swarm Optimisation assigns best weighted values to segmentation parameters to get maximum performance. The experimental outcomes proves the efficiency of the proposed strategy.

关键词： Image segmentation Accuracy Scalp Signal processing algorithms Feature extraction Grid computing Transformers Particle swarm optimization Optimization Tumors

来源：评论

学校读者我要写书评

暂无评论

Analysis and Evaluation of Bio-Inspired Algorithmic Framework, Potential application in Cloud/Multi-Cloud Environment

Analysis and Evaluation of Bio-Inspired Algorithmic Framewor...

引用

Cybernetics, Cognition and Machine Learning applications (ICCCMLA), IEEE International Conference on

作者： Ramanpreet Kaur Divya Anand Upinder Kaur Sahil Verma School of Computer Applications Lovely Professional University Phagwara India Department of Computer Application Baba Farid College Bathinda India School of Computer Science and Engineering Lovely Professional University Phagwara India Department of Computer Science Akal University Talwandi Sabo Bathinda India Department of Computer Science and Engineering CGC Mohali India

Cloud computing allows web-based services to use a variety of reasonably priced services or resources, removing the requirements of centralized knowledge access. There are many provocations available in cloud computing and multi-cloud, so bio-inspired algorithms frequently used to handle particular problems such as load imbalance, resource equipping, and performance optimization. Bio-inspired algorithms have a proclivity for spontaneously resolving a wide range of challenges by giving optimum solutions. The ability has an impact on how bio-inspired algorithms are used to tackle the crucial issues in cloud computing. This study presents a comprehensive review of bio-inspired methods for resolving and optimizing solutions in multi-cloud. ACO, GA, PSO, FPA, BA and COSMIC bio inspired techniques are considered based on cost, scalability, fault tolerance, security, energy consumption, and throughput. ACO is secure and having capability of fault tolerance, PSO is fast but less secure and costly than others. Thus, FPA has a better capability than others for various parameters. FPA is better in security, cost, fault tolerance and energy consumption

关键词：

来源：评论

学校读者我要写书评

暂无评论

Correlating Time Series Analysis with Radiotherapy for the Early Detection of Hodkin Lymphoma

Correlating Time Series Analysis with Radiotherapy for the E...

引用

Optimization Computing and Wireless Communication (ICOCWC), International Conference on

作者： M N Varun Somanna Rakesh Kumar Yadav Inzimam Department of Computer Science and Information Technology Jain (Deemed to be University) Bangalore India Maharishi School of Engineering & Technology Maharishi University of Information Technology Uttar Pradesh India Department of Computer Science & Application Vivekananda Global University Jaipur India

This study aimed to quantify the temporal capabilities of radiotherapy facts from sufferers with Hodgkin lymphoma (HL) and correlate those functions with time collection evaluation (TSA) measures to perceive potential temporal relationships with early analysis of HL. Excessive-decision 3-dimensional computed tomography (CT) scans of HL sufferers have been analyzed using batch-clever TSA methods to derive the temporal collection that characterizes the radiotherapy facts. In the end, a set of temporal features from the measured temporal series have been extracted and correlated with HL's medical and laboratory analysis. The outcomes showed that the derived temporal capabilities had undoubtedly correlated with the analysis, indicating a capability for using radiotherapy information to diagnose HL early. The mean and general deviation of the temporal collection in the radiotherapy curves from HL sufferers has been notably one-of-a-kind from wholesome patients. Furthermore, the temporal series of radiotherapy statistics from HL sufferers showed notably better peaks in the temporal capabilities than healthful patients, indicating an elevated stage of radiotherapy for HL sufferers. The effects of this observation recommend that TSA may be a viable tool for early analysis of HL, presenting a more comprehensive view of the temporal traits of radiotherapy data for HL sufferers.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Improved Piano Music Recognition Algorithm Based on Artificial Intelligence 2

Improved Piano Music Recognition Algorithm Based on Artifici...

引用

2nd International Conference on Smart Technologies for Smart Nation, SmartTechCon 2023

作者： Sahaya Sheela, M. Muthu Krishnammal, P. Shetty, Surendra Surendran, S. Vinothkumar, K. Venkataramanaiah, B. Department of ECE Vel Tech Rangarajan Dr.Sagunthala R&D Institute of Science and Technology Chennai Avadi India School of Electronics Engineering VIT-AP University Andhra Pradesh Amaravati India Department of Master of Computer Application NMAM Institute of Technology Nitte Deemed University Karnataka India Department of Computer Science and Engineering Tagore Engineering College Tamil Nadu Chennai India Department Of ECE PSNA College Of Engineering And Technology Tamilnadu Dindigul India Department Of ECE Veltech rangarajan Dr sagunthala R&D institute of science and Technology Chennai Avadi India

ISBN: (纸本)9798350305418

Not only do people enjoy listening to piano music, but it may also be differentiated from vocal music in the realm of digital music. With its ongoing development, the piano music recommendation algorithm has found solutions to a great number of practical issues, and its technical path has also progressed from its initial recommendation based on the behavioral preferences of users to the correlation recommendation among users to the mining of users' potential preferences in recent years. The birth of The ONE smart piano means that a new teaching mode will be produced, that is, piano learning and user experience will be integrated, and the latest achievements of modern science and technology will be applied and rooted in the field of music education and teaching, so that the piano, a large musical instrument, can be easily combined with a variety of intelligent devices. This is significant in terms of the combination of offline artificial intelligence and music education because it means that a new teaching mode will be produced. Additionally, this new teaching mode will The improved piano music recognition system is investigated in this study, which uses artificial intelligence as its foundation. In the beginning, both the overall architecture of the system and the functional module design plan are shown. It is well known that the feature matrix of a piano is distinct from that of other musical instruments. This distinction was discovered when a digital recognition approach was used to extract the music timbre feature matrix of a piano. The findings of the experiments indicate that the suggested system has a high recognition accuracy for the purpose of timbre recognition of piano arrangements, which demonstrates that it is deserving of further promotion and application. © 2023 IEEE.

关键词： Artificial intelligence improved recognition algorithm piano music

来源：评论

学校读者我要写书评

暂无评论

A Robust Ensemble Learning Approach for Medical Image Segmentation with Transfer Learning

A Robust Ensemble Learning Approach for Medical Image Segmen...

引用

Optimization Computing and Wireless Communication (ICOCWC), International Conference on

作者： Ritu Shree Kavitha R Shweta Singh Department of Computer Science & Application Vivekananda Global University Jaipur India Department of Computer Science and Information Technology Jain (Deemed to be University) Bangalore India Maharishi School of Engineering & Technology Maharishi University of Information Technology Uttar Pradesh India

This paper proposes a robust ensemble mastering approach for clinical picture segmentation. The proposed technique combines a convolution neural community (CNN) with a switch studying-based totally ensemble model. The CNN is pre-educated with a dataset containing clinical photo modalities, particularly Magnetic Resonance Imaging (MRI) and computed tomography (CT)., a weight-averaged ensemble model is acquired between the two scientific photograph modalities. This version is an initial way to the clinical image segmentation problem. Eventually, the ensemble model is great-tuned with additional imaging statistics from an unmarried modality to improve the segmentation accuracy. The proposed technique is evaluated on a range of datasets, and the effects display that it achieves competitive performance compared to the country of the artwork. Moreover, the experiments reveal that combining the transfer gaining knowledge of-based totally ensemble mastering approach with extra imaging information enhances the accuracy of medical picture segmentation.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Utilizing Random Forests for High-Accuracy Classification in Medical Diagnostics

Utilizing Random Forests for High-Accuracy Classification in...

引用

International Conference on Contemporary Computing and Informatics (IC3I)

作者： Meenakshi Maindola Ramy Riad Al-Fatlawy Rakesh Kumar Nandini Shirish Boob S P Sreeja N Sirisha Abhinav Srivastava Department of Computer Science & Engineering Graphic Era Deemed to be University Dehradun Department of computers Techniques engineering College of technical engineering The Islamic university Najaf Iraq Department of Computer Engineering & Applications GLA University Mathura Saveetha School of Engineering Saveetha Institute of Medical and Technical Sciences Chennai Tamilnadu Master of Computer Application New Horizon College of Engineering Bangalore Department of Computer Science and Engineering MLR Institute of Technology Hyderabad Telangana FS University Shikohabad Firozabad India

ISBN: (数字)9798350350067

ISBN: (纸本)9798350350074

In recent years, medical diagnostics has increasingly relied on machine learning techniques to improve accuracy and efficiency. Among these, the Random Forest algorithm has emerged as a powerful tool for classification tasks due to its robustness and ability to handle complex datasets. This paper explores the application of Random Forests in medical diagnostics, specifically focusing on enhancing the accuracy of disease classification. By analyzing large, heterogeneous medical datasets, we demonstrate how Random Forests can outperform traditional classification algorithms, offering high precision in identifying and classifying diseases. Key features, such as decision tree ensemble methods and bootstrap aggregation, are utilized to minimize overfitting and improve model generalization. The research compares Random Forests to other machine learning models, such as Neural Networks and Support Vector Machines, and finds that Random Forests perform better in terms of dependability and classification accuracy. We further emphasise that the technique can scale to big datasets and that it can manage missing data. The findings show that Random Forests might be a useful tool for accurate and early diagnosis when incorporated into clinical procedures. The findings of this study highlight the promise of machine learning, and Random Forests in particular, to revolutionise healthcare diagnostics and enhance patient results.

关键词： Radio frequency Support vector machines Accuracy Scalability Robustness Classification algorithms Medical diagnosis Random forests Medical diagnostic imaging Diseases

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378页 << < 110 111 112 113 114 115 116 117 118 119 > >>

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：