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

2,011 篇 会议
500 篇 期刊文献
42 册 图书

馆藏范围

2,553 篇 电子文献
0 种 纸本馆藏

日期分布

学科分类号

1,601 篇 工学
- 982 篇 计算机科学与技术...
- 825 篇 软件工程
- 335 篇 信息与通信工程
- 284 篇 控制科学与工程
- 224 篇 电气工程
- 223 篇 电子科学与技术（可...
- 144 篇 仪器科学与技术
- 137 篇 生物医学工程（可授...
- 134 篇 生物工程
- 125 篇 光学工程
- 101 篇 机械工程
- 93 篇 动力工程及工程热...
- 82 篇 化学工程与技术
- 68 篇 建筑学
- 63 篇 航空宇航科学与技...
- 60 篇 材料科学与工程（可...
910 篇 理学
- 477 篇 数学
- 282 篇 物理学
- 159 篇 生物学
- 136 篇 统计学（可授理学、...
- 128 篇 系统科学
- 104 篇 化学
- 85 篇 地球物理学
394 篇 管理学
- 270 篇 管理科学与工程(可...
- 166 篇 工商管理
- 140 篇 图书情报与档案管...
128 篇 医学
- 112 篇 临床医学
- 101 篇 基础医学(可授医学...
- 65 篇 药学(可授医学、理...
60 篇 经济学
- 60 篇 应用经济学
60 篇 法学
40 篇 教育学
24 篇 农学
6 篇 文学
5 篇 军事学
4 篇 艺术学
1 篇 哲学
1 篇 历史学

主题

62 篇 accuracy
45 篇 training
44 篇 optimization
43 篇 computational mo...
35 篇 feature extracti...
33 篇 predictive model...
32 篇 computer archite...
32 篇 software
32 篇 artificial intel...
31 篇 neural networks
30 篇 machine learning
29 篇 internet of thin...
26 篇 costs
25 篇 servers
24 篇 support vector m...
24 篇 hardware
24 篇 estimation
23 篇 computer science
23 篇 neutrons
23 篇 real-time system...

机构

88 篇 infn sezione di ...
87 篇 université de st...
87 篇 nikhef national ...
86 篇 ncsr demokritos ...
86 篇 infn sezione di ...
85 篇 institut univers...
85 篇 tno technical sc...
84 篇 infn sezione di ...
83 篇 north-west unive...
83 篇 university würzb...
83 篇 university of jo...
82 篇 infn sezione di ...
82 篇 national centre ...
81 篇 università la sa...
80 篇 university moham...
80 篇 western sydney u...
76 篇 infn sezione di ...
73 篇 università di sa...
70 篇 university of am...
70 篇 tbilisi state un...

作者

95 篇 ardid m.
94 篇 díaz a.f.
94 篇 coleiro a.
94 篇 enzenhöfer a.
94 篇 celli s.
94 篇 brunner j.
93 篇 ferrara g.
93 篇 boumaaza j.
93 篇 di palma i.
92 篇 kalekin o.
91 篇 dornic d.
91 篇 coniglione r.
91 篇 eberl t.
89 篇 calvo d.
87 篇 bendahman m.
84 篇 gal t.
84 篇 bozza c.
84 篇 gozzini s.r.
84 篇 dallier r.
83 篇 carretero v.

语言

2,287 篇 英文
222 篇 其他
25 篇 日文
17 篇 中文
2 篇 朝鲜文

检索条件"机构=Dept. of Computer Systems Architecture and Technology"

共 2553 条记录，以下是351-360 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：

Instructors' Perspectives on Capstone Courses in Computing Fields: A Mixed-Methods Study 2024

Instructors' Perspectives on Capstone Courses in Computing F...

引用

29th Working Group Reports on Innovation and technology in computer Science Education, ITiCSE WGR 2024

作者： Hooshangi, Sara Shakil, Asma Dasgupta, Subhasish Davis, Karen C.C. Farghally, Mohammed Fitzpatrick, KellyAnn Gutica, Mirela Hardt, Ryan Riddle, Steve Seyam, Mohammed Department of Computer Science Virginia Tech BlacksburgVA United States School of Computer Science University of Auckland Auckland New Zealand Info Systems and Tech Mgmt Dept George Washington University WashingtonDC United States Computer Science and Software Engineering Dept. Miami University OxfordOH United States School of Computing Instruction Georgia Institute of Technology AtlantaGA United States School of Computing & Academic Studies British Columbia Institute of Technology BurnabyBC Canada Computer & Information Science University of St. Thomas Saint PaulVA United States School of Computing Newcastle University Newcastle upon Tyne United Kingdom

ISBN: (纸本)9798400712081

Team-based capstone courses are integral to many undergraduate and postgraduate degree programs in the computing field. They are designed to help students gain hands-on experience and practice professional skills such as communication, teamwork, and self-reflection as they transition into the real world. Prior research on capstone courses has focused primarily on the experiences of students. The perspectives of instructors who teach capstone courses have not been explored comprehensively. However, an instructor's experience, motivation, and expectancy can have a significant impact on the quality of a capstone course. In this working group, we used a mixed methods approach to understand the experiences of capstone instructors. Issues such as class size, industry partnerships, managing student conflicts, and factors influencing instructor motivation were examined using a quantitative survey and semi-structured interviews with capstone teaching staff from multiple institutions across different continents. Our findings show that there are more similarities than differences across various capstone course structures. Similarities include team size, team formation methodologies, duration of the capstone course, and project sourcing. Differences in capstone courses include class sizes and institutional support. Some instructors felt that capstone courses require more time and effort than regular lecture-based courses. These instructors cited that the additional time and effort is related to class size and liaising with external stakeholders, including industry partners. Some instructors felt that their contributions were not recognized enough by the leadership at their institutions. Others acknowledged institutional support and the value that the capstone brought to their department. Overall, we found that capstone instructors were highly intrinsically motivated and enjoyed teaching the capstone course. Most of them agree that the course contributes to their professional de

关键词： Students

来源：评论

学校读者我要写书评

暂无评论

Enhanced Driver Stress Prediction from Multiple Biosignals via CNN Encoder-Decoder Model

Enhanced Driver Stress Prediction from Multiple Biosignals v...

引用

Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC)

作者： Vishal Singh Roha Maggie Ezzat Gaber Gendy Kaveti Pavan Thomas M. Deserno Nagarajan Ganapathy Mehmet R. Yuce Dept. of Electrical & Computer Systems Monash University Melbourne Australia Dept. of Biomedical Engineering Indian Institute of Technology Hyderabad Hyderabad India PLRI Lab for Medical Informatics Technical University of Braunschweig Brunswick Germany

ISBN: (数字)9798350371499

ISBN: (纸本)9798350371505

In this work, we present PhysioFuseNet, a novel framework designed to enhance driver stress state classification. PhysioFuseNet integrates a CNN-based encoder-decoder model with multimodal biosignal fusion. Using a driving simulator, different multimodal signals were acquired, namely electrocardiography, electrodermal activity, photoplethysmography, and respiration rate from (N = 25) healthy subjects. The experiment is of 35 minutes duration and contains different stress states (baseline (5 minutes), while normal, cognitive, and emotional sessions for 10 minutes). Multimodal features are extracted and employed in an encoder-decoder network. Extracted encoder features are combined through intermediate fusion and fed to support vector machine (SVM) and random forest (RF) classifiers. Experimental results demonstrate the efficacy of our approach, outperforming previous methods by achieving accuracies of 0.95 and 0.94 for SVM and RF, respectively. Notably, the framework excels in classifying emotional and cognitive stress states. In summary, the proposed framework could be useful in stress assessment in real-time and clinical conditions.

关键词： Support vector machines Radio frequency Biological system modeling Anxiety disorders Predictive models Electrocardiography Feature extraction Photoplethysmography Real-time systems Engineering in medicine and biology

来源：评论

学校读者我要写书评

暂无评论

A Distributed Ensemble of Diverse Deep Learning Models for Predicting COVID-19 Cases 20

A Distributed Ensemble of Diverse Deep Learning Models for P...

引用

20th International Conference on Smart Technologies, EUROCON 2023

作者： Hassan, Mohammad Mehedi Alrakhami, Mabrook S. Elhendi, Ahmed Zohier Alqahtani, Salman A. King Saud University Information Systems Department Ccis Riadh 11543 Saudi Arabia King Saud University Science Technology and Innovation Dept. Riadh 11543 Saudi Arabia King Saud University Computer Engineering Department Ccis Riadh 11543 Saudi Arabia

ISBN: (纸本)9781665463973

The outbreak of the COVID-19 pandemic has resulted in a significant impact on global health and economy. Forecasting the spread of COVID-19 cases is essential for policymakers to make informed decisions and allocate resources accordingly. Deep learning has shown promising results in predicting the spread of infectious diseases, including COVID-19. However, selecting the most appropriate model for a given forecasting task can be challenging, as no single model is guaranteed to perform well for all scenarios. In this paper, we propose a distributed ensemble approach that combines the predictions of different deep learning models, including Autoregressive Integrated Moving Average (Auto-ARIMA), Convolutional Neural Networks (CNN) and Long Short-Term Memory (LSTM), to improve the accuracy of COVID-19 case forecasts. Specifically, we train each deep learning model on a subset of the data and aggregate their predictions to obtain an ensemble forecast. To achieve a distributed ensemble, we use an edge computing framework to train the deep learning models on multiple nodes in a parallel and distributed manner. We evaluate our approach on publicly available COVID-19 datasets, and our results show that the proposed ensemble model outperforms the individual models in terms of forecasting accuracy. Furthermore, our distributed ensemble approach significantly reduces the training and prediction time compared to training each model separately. © 2023 IEEE.

关键词： COVID-19

来源：评论

学校读者我要写书评

暂无评论

Localization of Dengue Virus Likelihood Using Image Processing Technique

Localization of Dengue Virus Likelihood Using Image Processi...

引用

Emerging Smart Computing and Informatics (ESCI), Conference on

作者： Md. Mahbub Hosen Md. Rahatul Islam Faria Tabassum Syeda Thamina Tonni Malik Mohammad Nafiur Noor Shahid Rahman Dept. of Computer Science & Engineering Northern University of Bangladesh Dhaka Bangladesh Dept. of Human Intelligence Systems Kyushu Institute of Technology Wakamatsu Kitakyushu Japan Dept. of Computer Science & Engineering Bangladesh University of Engineering and Technology Dhaka Bangladesh Human Intelligence Lab Bangladesh Advance Robotics Research Center Dhaka Bangladesh Dept. of Electrical & Electronic Engineering Canadian University of Bangladesh Dhaka Bangladesh

The Aedes mosquito, found in tropical areas, transmits, and causes dengue fever. The spread of the dengue fever virus from an infected Aedes mosquito bite typically takes between three and fifteen days to manifest itself clinically as dengue fever symptoms. Early and automated detection of this illness will reduce the occurrence of outbreaks and facilitate the digitization of the system. Our primary objective is to identify regions at high risk for dengue fever using limited image data through the utilization of sophisticated machine learning and image processing methods. This work showcases the application of transfer learning algorithms for the timely identification of regions at risk for dengue mosquito infestation, particularly in situations where obtaining early data on dengue outbreaks is challenging. The experiments included images of 2150 dengue-positive data sets and 1440 dengue-negative data sets. We used AI and image classifiers Yolo V4 Tin, Tensor Flow, Google Colab, etc. for the training data set, and the system makes predictions with a 99.63% accuracy rate. Our system has some unique attributes; it not only detects the percentage of dengue probability but also the specific dengue-prone location on the submitted image.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Interaction of Spatial Computing in Augmented Reality 7

Interaction of Spatial Computing in Augmented Reality

引用

7th International Conference on Advanced Computing and Communication systems, ICACCS 2021

作者： Balakrishnan, S. Hameed, M.Syed Shahul Venkatesan, K. Aswin, G. Sri Krishna College of Engg. and Technology Dept. of Computer Science and Business Systems Tamilnadu Coimbatore India

ISBN: (纸本)9781665405201

In the above certain years, the technology of spatial computing has recognized the environment growth of simulated reality by user interaction and extensive knowledge which assist the 3D canvas used space for user interfaces. Spatial computing is widely compatible with XR which is an Extended Reality. This acts itself as an umbrella phase for Augmented Reality (AR), Mixed Reality (MR) and Virtual Reality (VR). Moreover, we are looking into the deep concepts of AR in spatial computing. Augmented reality is a new medium of laminating and merging digital contents towards the real world. This medium provides individual assets connecting the physical-virtual world with steady control and enhances the overall environment reality of user's information. These are obtained based on mobile devices, projection devices and mounted displays that help in augmenting the information over real-life. In advance, AR is part of spatial augmented reality which is an assistive technology tool used for determining the completion time of task, speed range and quality of interactive computation. This paper delivers the effectiveness of Augmented Reality (AR) with possible combination of technologies and applications from a user's point of view. © 2021 IEEE.

关键词： Augmented reality

来源：评论

学校读者我要写书评

暂无评论

Evaluation of Incremental Conductance MPPT Algorithm Under Varying Conditions

Evaluation of Incremental Conductance MPPT Algorithm Under V...

引用

IEEE SSD International Multi-Conference on systems, Signals and Devices

作者： Ahmad M. NEZAM Musaria K. MAHMOOD Sulaiman M. KARIM Abdirahim ADDAWE dept. of Energy Systems Engineering Ankara Yildirim Beyazit University Ankara Türkiye dept. of Medical Instr. Tech. Eng. Jannat Iraq College Ramadi Iraq dept. of Computer Technology Engineering Al-Hadba'a University College Mosul Iraq dept. of Computer Engineering Karabük Üniversitesi Karabük Turkey

ISBN: (数字)9798350374131

ISBN: (纸本)9798350374148

Photovoltaic-based renewable energy production is constantly developing and becoming an increasing part of mod-ern energy markets. The power efficiency of a PV system is one of the most challenging problems, especially in changing climate conditions. Tracking the Maximum Power Point (MPP) to achieve optimal power production is one of the most important requirements of any PV-based system. This article explores the functionality of the Incremental Conductance (INC) algorithm as a highly effective approach for Maximum Power Point Tracking (MPPT). Simulations are conducted to investigate the effectiveness of INC across diverse operational case studies, considering both Standard Test Conditions (STC) and Partial Shading Conditions (PSC). In this investigation, key factors including system power efficiency, settling time, and steady-state power oscillation are taken into account. Simulation reveals rapid tracking and reduced oscillation under STC, meanwhile, it occasionally demonstrates inadequacy in accurately tracking the MPP under PSC in the case of multi-panel systems.

关键词： Maximum power point trackers Solar irradiance Photovoltaic systems Performance evaluation Renewable energy sources Radiation effects Production

来源：评论

学校读者我要写书评

暂无评论

Cascaded Deep CNN Network for Breast Cancer Screening from Ultrasound Images Using Differential Evolution Algorithm

Cascaded Deep CNN Network for Breast Cancer Screening from U...

引用

Digital Society and Intelligent systems (DSInS), International Conference on

作者： Wahidur Rahman Md Shadman Sakib Md Solaiman Hosen Mir Mohammad Azad Hani Alshahrani Adel Sulaiman Mana Saleh Al Reshan Asadullah Shaikh Dept. of Computer Science and Engineering Uttara University Uttara Dhaka Bangladesh Dept. of Computer Science and Engineering University of Information Technology & Sciences Dhaka Bangladesh Department of Computer Science Iowa State University USA Department of Computer Science and Engineering Dhaka Bangladesh Department of Computer Science College of Computer Science and Information Systems Najran University Saudi Arabia Emerging Technologies Research Lab (ETRL) College of Computer Science and Information Systems Najran University Saudi Arabia Department of Information Systems College of Computer Science and Information Systems Najran University Saudi Arabia

ISBN: (数字)9798331528829

ISBN: (纸本)9798331528836

Because of poor blood flow and susceptibility to infections, breast cancer can be challenging to heal and, if not treated, might cause major problems, including limb amputation and a lowered quality of life. Though several systems exist to identify breast cancer, few combine machine learning (ML), deep learning (DL), and optimization strategies. This work presents a novel method leveraging complex algorithms to precisely identify breast cancer from ultrasound images. The study utilizes a dataset from a secondary source, categorizing it into three identical classes: normal (Class 0), benign (Class 1), and malignant (Class 2). It extracts features using pre-trained convolutional neural networks (CNNs), optimizes these features using the Differential Evolution Algorithm (DEA), and classifies images using standard machine learning algorithms. To show how well it detects breast cancer, the approach combines seven conventional ML classifiers with ten pre-trained CNN models. Using DenseNet121 + DEA + Xtreme Gradient Boosting (XGB) Classifier, DEA chooses important features derived by CNNs with a high accuracy of 97.76%. However, the proposed method can be very effective for real-time breast cancer screening using ultrasound images.

关键词： Limbs Ultrasonic imaging Machine learning algorithms Feature extraction Breast cancer Real-time systems Classification algorithms Convolutional neural networks Standards Optimization

来源：评论

学校读者我要写书评

暂无评论

Current Vector Control of AC Servo Motor Considering Output Delay of PWM Inverter

Current Vector Control of AC Servo Motor Considering Output ...

引用

International Workshop on Advanced Motion Control (AMC)

作者： Haruta Shimamoto Takashi Yoshioka Shiro Urushihara Advanced Course in Industrial and Systems Engineering National Institute of Technology Kagawa College Takamatsu Japan Dept. of Electrical and Computer Engineering National Institute of Technology Kagawa College Takamatsu Japan

In this paper, to expand a control bandwidth of AC servo motor, a new current vector control considering an output delay of PWM Inverter is proposed. The proposed current control is a I-P control with an additional feedback gain, which is based on an extended state feedback consisted from a d-q motor model, the output delay of PWM inverter and an integrator of ACR. In addition, the proposed method is easy to implement to the existing AC servo system. The effectiveness of proposed method is validated in a computer simulation and an experiments using a 3.7 kW class motor test bench. In the condition that a cut-off frequency of ACR is close to a carrier frequency, the simulation results show that the proposed method dramatically improves the current response at the higher cut-off frequency. Moreover, the experimental results show that the proposed method dramatically improves the current response at each operating point. From the results, the proposed method is effective to the expand the bandwidth of AC servo motor.

关键词：

来源：评论

学校读者我要写书评

暂无评论

A Dementia Diagnosis Technique Based on AI and Hardware Acceleration

A Dementia Diagnosis Technique Based on AI and Hardware Acce...

引用

2023 IEEE International Conference on Artificial Intelligence, Blockchain, and Internet of Things, AIBThings 2023

作者： Khalil, Kasem Khan Mamun, Mohammad M. R. Sherif, Ahmed Elsersy, Mohamed Imam, Ahmad Abdel-Aliem Abouzaid, Kamal University of Mississippi Electrical and Computer Engineering Department MS United States Tennessee Technological University Electrical and Computer Engineering Department TN United States University of Southern Mississippi School of Computing Sciences and Computer Engineering MS United States Higher Colleges of Technology Computer and Information Systems Dept. Al Ain United Arab Emirates William Carey University College of Osteopathic Medicine Mississippi MS United States

ISBN: (纸本)9798350322347

The effects of Alzheimer's disease (AD) are devastating, both personally and within the patient's family, as the disease progresses slowly over many years. It could significantly affect illness consequences and outcomes if detected early and accurately. Non-invasive medical testing often uses blood bio-samples because they are easy to collect and relatively cheap to analyze. This paper proposes a federated learning (FL)-based diagnostic model for AD using blood bio-samples. We have used blood bio-sample data sets downloaded from the ADNI website to test and compare the efficacy of our models. According to the enormous data collected for early AD detection, we used a hardware acceleration scheme to implement our FL model to fasten the training and testing operations. The hardware-Accelerator method is implemented using VHDL and Altera 10 GX FPGA. The simulation results show the proposed algorithms reach an accuracy and sensitivity of 89% and 87%, respectively, for early detection while taking less time to train than other state-of-The-Art algorithms. The proposed algorithms also consume 52-172 mW, which makes them suitable for constrained devices. © 2023 IEEE.

关键词： Diagnosis

来源：评论

学校读者我要写书评

暂无评论

Towards the Certification of an Evacuation Assistance System Utilizing AI-based Approaches

Towards the Certification of an Evacuation Assistance System...

引用

IEEE International Conference on Software Reliability Engineering Workshops (ISSRE Wksp)

作者： Georg Hägele Abdelbaki Bouguerra Arezoo Sarkheyli-Hägele BSP - Shared Services ASSA ABLOY Entrance Systems Landskrona Sweden Dept. of Computer Science University of M’Sila M’Sila Algeria Dept. of Computer Science and Media Technology Internet of Things and People Research Center Malmö University Malmö Sweden

ISBN: (数字)9798350367041

ISBN: (纸本)9798350367058

Using Artificial Intelligence-based approaches in safety-critical applications requires special attention during development. For instance, as of the beginning of 2027, European Union regulations mandate certification by a notified body for AI integration in safety-critical machinery applications. Nevertheless, AI-based approaches find application across diverse domains, enhancing system performance. Evacuation Assistance systems used for evacuating buildings during emergencies like fires or terrorist attacks are examples in this context. In recent years, there has been a surge in research and standardization attempts to provide an assurance base for utilizing AI techniques in safety-critical applications from the technical and legislative perspectives. However, the focus is often reduced to automated driving and robotics, and many questions still need to be *** paper presents our research on the certification of AI-based systems. We highlight our effort in determining the relevant international standards that need to be complied with. The contribution of this paper is a certification concept for AI-based systems, where performance and reliability are crucial. The unique overview of state-of-the-art and industrial standards allows a certification attempt for this type of system. It also provides a base for future work beyond the scope of automated driving and robotics, such as assistance systems and building *** analytical discourse presented in this contribution justifies and highlights the mapping of standards and techniques to required functionalities and architectural components of the Evacuation Assistance System, supporting the quality and performance, system acceptance, and certification for the dedicated domain and purpose.

关键词： Service robots Terrorism System performance Buildings Regulation Software reliability Artificial intelligence Surges Certification Standards

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256页 << < 32 33 34 35 36 37 38 39 40 41 > >>

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：