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

3,492 篇 会议
1,278 篇 期刊文献
30 册 图书

馆藏范围

4,800 篇 电子文献
0 种 纸本馆藏

日期分布

学科分类号

2,717 篇 工学
- 2,100 篇 计算机科学与技术...
- 1,725 篇 软件工程
- 761 篇 信息与通信工程
- 513 篇 控制科学与工程
- 390 篇 电气工程
- 329 篇 生物工程
- 295 篇 生物医学工程（可授...
- 289 篇 电子科学与技术（可...
- 240 篇 网络空间安全
- 193 篇 光学工程
- 188 篇 动力工程及工程热...
- 185 篇 安全科学与工程
- 167 篇 机械工程
- 159 篇 化学工程与技术
- 138 篇 交通运输工程
- 133 篇 材料科学与工程（可...
1,526 篇 理学
- 768 篇 数学
- 406 篇 物理学
- 384 篇 生物学
- 268 篇 统计学（可授理学、...
- 182 篇 化学
- 170 篇 系统科学
869 篇 管理学
- 523 篇 管理科学与工程(可...
- 389 篇 图书情报与档案管...
- 275 篇 工商管理
357 篇 医学
- 280 篇 临床医学
- 266 篇 基础医学(可授医学...
- 201 篇 公共卫生与预防医...
- 159 篇 药学(可授医学、理...
174 篇 法学
- 145 篇 社会学
102 篇 经济学
90 篇 农学
47 篇 教育学
22 篇 文学
10 篇 军事学
3 篇 艺术学

主题

296 篇 accuracy
208 篇 deep learning
175 篇 machine learning
162 篇 real-time system...
156 篇 internet of thin...
150 篇 feature extracti...
146 篇 computational mo...
142 篇 convolutional ne...
123 篇 predictive model...
113 篇 support vector m...
113 篇 training
98 篇 optimization
91 篇 security
87 篇 data models
83 篇 artificial intel...
83 篇 cloud computing
81 篇 technological in...
78 篇 machine learning...
73 篇 data mining
68 篇 neural networks

机构

114 篇 lovely professio...
111 篇 department of co...
103 篇 department of co...
63 篇 department of co...
61 篇 school of comput...
55 篇 gla university d...
51 篇 maharishi school...
49 篇 department of co...
47 篇 centre of resear...
46 篇 department of co...
45 篇 chitkara centre ...
45 篇 lloyd law colleg...
41 篇 lloyd institute ...
40 篇 gla university d...
38 篇 chitkara univers...
37 篇 graphic era deem...
37 篇 the islamic univ...
34 篇 department of co...
34 篇 department of co...
34 篇 department of co...

作者

52 篇 neeraj varshney
44 篇 varshney neeraj
42 篇 singh kamred udh...
40 篇 singh teekam
39 篇 rakesh kumar
35 篇 kumar ankit
34 篇 singh ashutosh k...
33 篇 kumar rakesh
28 篇 tina babu
28 篇 kumar gaurav
27 篇 asha v.
27 篇 saloni bansal
26 篇 teekam singh
25 篇 kamred udham sin...
24 篇 n. naga saranya
23 篇 babu tina
23 篇 ankit kumar
23 篇 pan jeng-shyang
23 篇 patra sudhansu s...
20 篇 bibhuti bhusan d...

语言

3,837 篇 英文
946 篇 其他
27 篇 中文
1 篇 阿拉伯文
1 篇 西班牙文
1 篇 法文
1 篇 俄文
1 篇 斯洛文尼亚文

检索条件"机构=Department of Computer Applications in Science and Engineering"

共 4800 条记录，以下是541-550 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：

An Analysis of Signature-Based Components in Hybrid Intrusion Detection Systems

An Analysis of Signature-Based Components in Hybrid Intrusio...

引用

2023 Intelligent Computing and Control for engineering and Business Systems, ICCEBS 2023

作者： Agoramoorthy, Moorthy Ali, Ahamed Sujatha, D. Michael Raj, T.F. Ramesh, G. Saveetha Institute of Medical and Technical Sciences Department of Computer Science and Engineering Saveetha School of Engineering Chennai India Computer Science and Engineering Easwari Engineering College Chennai Ramapuram India St.Peters College of Engineering and Technology Department of Computer Science and Engineering Chennai Avadi India Simats Department of Computer Applications Sclas Tamilnadu Chennai India K.L.N.College of Engineering Department of Information Technology Sivagangai - Tamilnadu Pottapalayam India

ISBN: (纸本)9798350394580

In cybersecurity, Intrusion Detection Systems (IDS) protect against emerging cyber threats. Combining signature-based and anomaly-based detection methods may improve IDS accuracy and reduce false positives. This research analyzes hybrid intrusion detection systems' signature-based components' performance and limitations. The paper begins with a detailed history of signature-based detection methods responding to changing threat situations. This research analyzes signature databases to determine their capacity to identify and guard against current threats and cover known vulnerabilities. The paper also examines the intricate relationship between signature-based detection and anomaly-based techniques in hybrid IDS systems. This investigation examines how these two methodologies work together to uncover old and new attack strategies, focusing on zero-day vulnerabilities and polymorphic malware. A diverse dataset of network traffic and attack scenarios is used to test. Detection, false positives, and response times assess signature-based components. Comparative examinations investigate how signature-based detection affects system accuracy and efficiency. This research illuminates the role of signature-based aspects in hybrid intrusion detection systems. This study recommends integrating signature-based detection techniques with anomaly-based methods to improve hybrid intrusion detection systems (IDS) at recognizing and mitigating various cyber threats. © 2023 IEEE.

关键词： Anomaly-Based Detection Cybersecurity False Positives Hybrid IDS Intrusion Detection Systems Network Security Polymorphic Malware Signature-Based Detection Threat Detection Zero-Day Exploits

来源：评论

学校读者我要写书评

暂无评论

An IOT-Based Soil Moisture Management System for Precision Agriculture: Real-Time Monitoring and Automated Irrigation Control 4

An IOT-Based Soil Moisture Management System for Precision A...

引用

4th International Conference on Smart Electronics and Communication, ICOSEC 2023

作者： Laha, Suprava Ranjan Pattanayak, Binod Kumar Pattnaik, Saumendra Mishra, Debashree Kumar Nayak, Debasish Swapnesh Dash, Bibhuti Bhusan Iter Siksha O Anusandhan University Department of Computer Science and Engineering Odisha Bhubaneswar India School of Computer Applications Kalinga Institute of Industrial Technology Bhubaneswar India

ISBN: (纸本)9798350300888

Managing soil moisture is crucial for optimizing crop growth and yield in agriculture. With the advancements in Internet of Things (IoT) technology, innovative soil moisture monitoring and control solutions have emerged. This paper presents a pioneering IoT -based soil moisture management system tailored for precision agriculture within Siksha 'O' Anusandhan (SOA) University. The system utilizes sensor nodes, wireless communication, and cloud computing to enable real-time monitoring and automated irrigation control, addressing the limitations of conventional manual approaches. Providing continuous, remote, and precise measurements of soil moisture levels revolutionizes how soil moisture is managed within the university's agricultural practices. Low-cost sensor nodes are strategically placed throughout the fields to collect data, which is wirelessly transmitted to a central hub for analysis and decision-making. A cloud-based platform processes the data, generating actionable insights and triggering automated irrigation when necessary. Extensive testing and validation demonstrate the system's reliability and ability to improve water use efficiency, surpassing traditional methods. Furthermore, the IoT architecture of the system offers scalability and flexibility, making it adaptable to different crop types and field conditions present within SOA University. This innovative research contributes to the field of precision agriculture by providing an efficient and tailored solution for soil moisture management within the university's agricultural practices. This IoT -based system enhances crop productivity by enabling real-time monitoring and automated irrigation control, promoting sustainable water resource utilization. Its implementation within SOA University fosters the integration of cutting-edge technology into agricultural practices, facilitating optimized crop growth and contributing to the university's commitment to environmental sustainability and resource managem

关键词： Soil moisture

来源：评论

学校读者我要写书评

暂无评论

Optimizing Image Recognition Model through Transfer Learning and Robust Feature Extraction in Neural Networks 2

Optimizing Image Recognition Model through Transfer Learning...

引用

2nd IEEE International Conference on Communication, Security and Artificial Intelligence, ICCSAI 2023

作者： Ramesh, G. Agoramoorthy, Moorthy Ahamed Ali, S. Sujatha, D. Michael Raj, T.F. K.L.N.College of Engineering Department of Information Technology Sivagangai Tamilnadu Pottapalayam India Saveetha School of Engineering Saveetha Institute of Medical and Technical Sciences Department of Computer Science and Engineering Chennai India Easwari Engineering College Computer Science and Engineering Chennai Ramapuram India St. Peters College of Engineering and Technology Department of Computer Science and Engineering Chennai Avadi India Sclas Simats Department of Computer Applications Tamilnadu Chennai India

ISBN: (纸本)9798350369960

These advances in image identification's technology have created massive changes, mainly in the health care facilities plus self-directed systems. Transfer learning strategies coupled with robust feature extraction techniques are used in the model to promote efficiency in the imaging system. A technique of fine-tuning the weights used for recognition tasks on pre-trained convolutional neural network architectures is proposed. State of art feature extraction pipeline composed with edge detection, texture analysis and spatial frequency analysis to enrich network capacity of distinguishing intricate visual textures and patterns. This combination of techniques helps in faster model training with top class prediction results on mixed image datasets. After rigorous testing on various benchmark datasets, including CIFAR-10 and ImageNet, considerable enhancement in recognition performance beyond baselines was observed. Additionally, the proposed approach is resilient to changes in image quality, illumination, and occlusions. The proposed framework enhances the existing model efficiency, flexibility, and robustness for application in real-time image identification. This approach opens new capabilities for the medical imagery, self-navigation cars, and object recognize mechanisms whose image classification must be exact. © 2023 IEEE.

关键词： Feature Extraction Image Recognition Neural Network Transfer Learning

来源：评论

学校读者我要写书评

暂无评论

Integrated Healthcare Monitoring System using Wireless Body Area Networks and Internet of Things 4

Integrated Healthcare Monitoring System using Wireless Body ...

引用

4th International Conference on Innovative Trends in Information Technology, ICITIIT 2023

作者： Ezhilarasi, M. Kumar, Anand Shanmugapriya, M. Ghanshala, Anshul Gupta, Anshika Sri Ramakrishna Engineering College Department of EEE Coimbatore India Graphic Era University Dept of Computer Applications Dehradun India Ayya Nadar Janaki Ammal College Department of Computer Science Sivakasi India The Chinese University of Hong Kong Department of Computer Science and Engineering Hong Kong

ISBN: (纸本)9781665494144

To minimize overall healthcare costs and enhance workflows and processes, remote health monitoring solutions are needed in both clinics and at home. One of the most effective communication technologies, the Internet of Things (IoT) offers the ability of integrated data access and fusion across a variety of applications. Depending on how each person's role is defined, users and qualified professionals (like doctors and nurses in the medical industry) may be able to access data. The goal of the Internet of Things in the healthcare industry is to redefine the healthcare system by bringing together all involved authorities and cutting-edge technology makes the most of the data shared between intimately linked technologies that use the IoT platform. IoT is generally anticipated to provide an enhanced device, scheme, and application connectivity that extend over machine-To-machine communications. In the past few years, the development of wearable sensors has offered ease, simplicity, and better health. By making medical sensors smaller and less expensive, technological advancements have boosted the use of these devices. The expertise and abilities of healthcare services, such as remote health monitoring, surgery, rehabilitation, and therapy are improved through medical sensors. Fog computing techniques are also added to enhance precision medicine, obtain real-Time data processing, and prevent the connection from failing. As a result, the operating environment for devices is more nimble and local. In this regard, this study suggests an architecture model for the healthcare domain that incorporates the technologies of body area networks, IoT, and Fog computing. The key contribution is to boost the capabilities and resources of IoT devices by using an intermediate Fog layer close to the edge to get beyond IoT restrictions. Experiments show that when compared to other standard architecture, the suggested model can reach a 75% faster response time. The evaluation's results sup

关键词： Diagnosis

来源：评论

学校读者我要写书评

暂无评论

Hybrid Compiler and Hardware Approach to Mitigate Side-Channel Vulnerabilities in Parallel GPU Architectures 8

Hybrid Compiler and Hardware Approach to Mitigate Side-Chann...

引用

8th International Conference on I-SMAC (IoT in Social, Mobile, Analytics and Cloud), I-SMAC 2024

作者： Lungu, Nelson Dash, Bibhuti Bhusan De Chandra, Utpal Dash, Bibek Bikram Pattanayak, Binod Kumar Patra, Sudhansu Shekhar Electrical and Electronical Engineering University of Zambia Lusaka Zambia School of Computer Applications Kiit Deemed to be University Bhubaneswar India HealthWorksAI Bangalore India Iter Siksha 'O' Anusandhan University Department of Computer Science & Engineering Odisha Bhubaneswar India

ISBN: (纸本)9798350376425

Graphics processing units (GPUs) have become ubiquitous in computing systems, from personal devices to data centres. Their massively parallel architecture delivers tremendous performance for graphics and general-purpose workloads. However, the open nature of GPUs also introduces security vulnerabilities that can be exploited through side-channel attacks. Defending against such threats often incurs performance overhead, creating tradeoffs between security and speed. This article examines recent research analysing and mitigating GPU side channel attacks while maintaining acceptable performance and presented a multi-faceted defence strategy combining compiler transformations, runtime monitoring, and microarchitectural techniques to balance security and performance. The methodology integrates formal threat models, empirical side-channel evaluations, and rigorous benchmarking. It implements and evaluates prototypes demonstrating security improvement with minimal impact on representative workloads. The results provide promising directions for practical GPU security defences. © 2024 IEEE.

关键词： Program compilers

来源：评论

学校读者我要写书评

暂无评论

Systematic Review of GAN for Enhancing Efficiency in AI in Gaming

Systematic Review of GAN for Enhancing Efficiency in AI in G...

引用

2024 International Conference on Advances in Computing Research on science engineering and Technology, ACROSET 2024

作者： Singh, Jasdeep Islam, Sardar M. N. Tewatia, Manav Garg, Deepanshu Fatima, Neda School of Computer Applications Manav Rachna International Institute of Research and Studies Faridabad India Victoria University Department of Computer Science and Engineering Melbourne Australia School of Engineering and Technology Manav Rachna International Institute of Research and Studies Faridabad India

ISBN: (纸本)9798350388800

A thorough analysis of Generative Adversarial Networks (GANs) and how they might be used to improve AI gaming efficiency is presented in this research. Game developers now have never-before-seen possibilities for innovation, immersion, and personalization thanks to GANs, which have become a potent tool for producing realistic data samples across a variety of fields. This review investigates the architecture, training methods, applications, difficulties, and potential future directions of GANs in AI gaming through a thorough analysis of the body of research and publications. The review demonstrates how GANs can transform the game industry by highlighting their many uses in procedural content generation, texture synthesis, character animation, environment design, and content customization. Nevertheless, there are certain difficulties in integrating GANs into AI games, such as computational resources, mode collapse, training instability, and assessment *** well as legal matters. To tackle these obstacles, multidisciplinary research endeavors and cooperation across academic institutions, corporate entities, and regulatory agencies are necessary. Going forward, new avenues for study and developments in GAN technology hold great potential for getting over these roadblocks and opening up fresh possibilities in AI gaming. We can create a future where AI powered gaming experiences change the parameters of interactive entertainment and provide players globally with more engaging, varied, and personalized gaming experiences by utilizing the possibilities of GANs and addressing the related obstacles. © 2024 IEEE.

关键词： Generative adversarial networks

来源：评论

学校读者我要写书评

暂无评论

Security Attacks and Key Challenges in Blockchain Technology: A Survey 4th

Security Attacks and Key Challenges in Blockchain Technology...

引用

4th International Conference on Advances in Information Communication Technology and Computing, AICTC 2022

作者： Patel, Rima Patel, Dharmendra Department of Computer Science & Engineering Faculty of Technology & Engineering Devang Patel Institute of Advance Technology and Research CHARUSAT Changa India Department of Computer Application Smt. Chandaben Mohanbhai Patel Institute of Computer Applications CHARUSAT Changa India

ISBN: (纸本)9789811998874

A blockchain is decentralized, distributed and public ledger, which is used to record the transaction across the number of clusters of computers. The record cannot be altered without an alternation in subsequent blocks. In the world of IT, the term Blockchain is not obscure. Despite tremendous applications in the field of information technology, finance and other industries, there are some challenges with Blockchain technology that need to be taken into consideration. In this paper, we have discussed the key challenges and issues with Blockchain technology. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Smart contract

来源：评论

学校读者我要写书评

暂无评论

A Hybrid Approach of BBO and PSO for Resource Management in Fog Computing 13

A Hybrid Approach of BBO and PSO for Resource Management in ...

引用

13th International Conference on System Modeling and Advancement in Research Trends, SMART 2024

作者： Bhakhar, Ruchika Chhillar, Rajender Singh Goyal, Archna Maharshi Dayanand University Department of Computer Science and Applications Haryana Rohtak India School of Engineering and Technology K.R. Mangalam University Sohna Rural Gurugram India

ISBN: (纸本)9798350380583

Efficient resource management is crucial for fog computing to achieve optimal performance and resource utilization over different cloud nodes. In order to overcome this issue, a hybrid BBO-PSO has been proposed. Inspired by species migration, BBO treats fog nodes as habitats with suitability indices specifying the performance of each in terms to tasks and adapt inferior convergence schedules dynamically based on resource load without locality-awareness while minimizing latency through migration and mutation ha1933b. The resulting system is akin to the PSO, which uses swarm intelligence for resource configuration (e.g., particles in a nearby cluster), and adjusts their position via historical information as well global best-known placements based on performance metrics such as increased resource utilization, reduced request latency and energy efficiency. This paper takes a hybrid approach by directly integrating these techniques through exchanging suitability indices and best-known positions, thereby combining the exploration ability of BBO with the targeted search capability of PSO. Migration and mutation techniques are optimized to cope with adapting mechanisms changes in environments thus accommodates workload patterns as well network conditions. This BBO-PSO hybrid approach holds significant promise for improving fog computing's scalability and robustness. © 2024 IEEE.

关键词： Swarm intelligence

来源：评论

学校读者我要写书评

暂无评论

Weapon Detection Identification and Classification for DCNN and YOLO-V5 Techniques 5

Weapon Detection Identification and Classification for DCNN ...

引用

5th International Conference on IoT Based Control Networks and Intelligent Systems, ICICNIS 2024

作者： Ashok Kumar, J. Dhivya, G. Selvaraj, P. Karthikeyan, V. Ganesh Ramesh, S.P. Lakshmi, S. Jeya Saravanakumar, R. Karpagam Academy of Higher Education Department of Computer Applications Tamil Nadu Coimbatore India School of Computer Science and Engineering Department of Computer Science and Engineering Galgotias University Uttar Pradesh Greater Noida India School of Computing SASTRA Deemed to Be University Thanjavur Tamil Nadu Thirumalaisamudram India Iconix Software Solution Tamil Nadu Tirunelveli India

ISBN: (纸本)9798331518097

Over 850,000 people die every year as a direct result of gun violence, yet civilians hold more than 85% of the world's weapons. Detecting weapons via manual surveillance has not been successful. It is critical to automate a system that detects weapons. A large number of convolution neural network CNN-based automated weapon identification systems have shown promising results. These methods are crucial for weapon identification but expensive. These devices produce a large amount of false negatives since monitoring videos are not high enough quality or visible enough to identify weapons. Finding the sweet spot between fast detection and a few false positives and negatives in weapon detection is the main goal of this research. In addition to defining an Area of Interest, the suggested structure uses YOLO. The models use previously processed images with backgrounds that have been blurred using a median filter. Metrics such as F1 scores, accuracy, recall, False Positive, and False Negative will be used to assess the suggested architecture. This investigation shows that YOLO-v5 can quickly identify and has a high recall rate. The deep convolution neural network DCNN required 0.17 ms for each frame, but this one only required 0.010 ms, which would indicate that security and weapon detection have good promise. Starting with a labeled collection of weapon and non-weapon photos is the initial stage in DCNN and YOLOv5 weapon detection. Use YOLOv5's ability to recognize multiple things within frames to train a real-time object localization and identification model. DCNNs categorize weapons and extract complex data effectively. DCNN classifies objects, whereas YOLOv5 detects, bounds, and tracks them. Optimize both models' hyperparameters and apply data augmentation for better performance. Install the integrated system on cutting-edge equipment for real-time weapon identification and classification. © 2024 IEEE.

关键词： Median filters

来源：评论

学校读者我要写书评

暂无评论

An Effective Forest Fire Prediction based on Contrastive Vision Transformer with Pool Former 2

An Effective Forest Fire Prediction based on Contrastive Vis...

引用

2nd IEEE International Conference on Integrated Intelligence and Communication Systems, ICIICS 2024

作者： Deepa, N. Husain, Saef Obad Ezhil, G. Indhumathi, V. Revathi, R. Department of Computer Science and Engineering Saveetha School of Engineering Saveetha Institute of Medical and Technical Sciences Chennai India Department of Computers Techniques Engineering College of Technical Engineering The Islamic University Najaf Iraq Department of Humanities Bannari Amman Institute of Technology Sathyamangalam India Department of Computer Applications Sona College of Arts and Science Salem India Department of Electrical and Electronics Engineering New Prince Shri Bhavani College of Engineering and Technology Chennai India

ISBN: (纸本)9798331504960

Since years, forest fires are a significant concern globally, causing damage to ecosystems and human settlements. For effective prevention and mitigation predicting forest fires is important, different factors contribute to forest fires which includes human activities, topography, climate change and weather conditions. Traditional approaches for predicting forest fires had faced significant challenges which include limited validation of prediction models and lack of standardization. Therefore, this paper proposes Contrastive Vision Transformer (CViT)-Pool Former for predicting forest fire which is employed on Forest Fire Big Data dataset which enabled better comparability. This dataset is preprocessed by using data augmentation, noise reduction and data enhancement techniques. Then, the features are extracted by using CViT which extracted optimal features based on weather conditions and captured contextual relationships by maximizing mutual information. After that, Pool Former light weight attention module is used for predicting fires which gave more accurate predictions by enabling targeted prevention and mitigation, minimized unwanted deployments and resource waste, boosted prediction accuracy by token fusion and enhanced representation learning. The proposed CViT-Pool Former method established better results including accuracy (92.8%), precision (89.4%), recall (91.4%) and F1-score (90.2%) when compared with existing Region Proposed Convolutional Neural Network (R-CNN). © 2024 IEEE.

关键词： Premixed flames

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480页 << < 51 52 53 54 55 56 57 58 59 60 > >>

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：