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

1,490 篇 期刊文献
1,219 篇 会议
4 册 图书

馆藏范围

2,713 篇 电子文献
0 种 纸本馆藏

日期分布

学科分类号

1,540 篇 理学
- 992 篇 物理学
- 256 篇 数学
- 235 篇 地球物理学
- 182 篇 生物学
- 129 篇 化学
- 105 篇 统计学（可授理学、...
1,445 篇 工学
- 742 篇 计算机科学与技术...
- 612 篇 软件工程
- 311 篇 信息与通信工程
- 215 篇 核科学与技术
- 209 篇 电子科学与技术（可...
- 208 篇 电气工程
- 176 篇 仪器科学与技术
- 166 篇 控制科学与工程
- 137 篇 光学工程
- 133 篇 生物工程
- 126 篇 生物医学工程（可授...
- 95 篇 化学工程与技术
- 79 篇 动力工程及工程热...
- 66 篇 土木工程
- 65 篇 网络空间安全
- 64 篇 航空宇航科学与技...
- 59 篇 安全科学与工程
293 篇 管理学
- 194 篇 管理科学与工程(可...
- 109 篇 图书情报与档案管...
- 93 篇 工商管理
155 篇 医学
- 128 篇 临床医学
- 109 篇 基础医学(可授医学...
- 66 篇 药学(可授医学、理...
- 62 篇 公共卫生与预防医...
60 篇 农学
56 篇 法学
39 篇 经济学
28 篇 教育学
3 篇 文学
2 篇 军事学
1 篇 艺术学

主题

173 篇 hadron colliders
89 篇 accuracy
88 篇 deep learning
83 篇 higgs bosons
66 篇 feature extracti...
54 篇 training
52 篇 internet of thin...
52 篇 real-time system...
50 篇 machine learning
50 篇 convolutional ne...
49 篇 w & z bosons
49 篇 computational mo...
47 篇 proton-proton in...
44 篇 predictive model...
39 篇 relativistic hea...
38 篇 top quark
35 篇 large hadron col...
35 篇 support vector m...
35 篇 standard model (...
33 篇 galaxies

机构

393 篇 department for p...
391 篇 faculty of scien...
381 篇 department of ph...
374 篇 department of ph...
372 篇 department of ph...
369 篇 kirchhoff-instit...
341 篇 yerevan physics ...
338 篇 fakultät für phy...
333 篇 institute of phy...
328 篇 institute of phy...
310 篇 instituto de fís...
292 篇 department of ph...
278 篇 department of ph...
270 篇 nikhef national ...
268 篇 department of ph...
260 篇 dipartimento di ...
258 篇 department of ph...
257 篇 universidade fed...
251 篇 ictp trieste
250 篇 graduate school ...

作者

329 篇 c. alexa
329 篇 j. m. izen
317 篇 g. bella
316 篇 d. calvet
315 篇 c. amelung
314 篇 j. strandberg
294 篇 g. spigo
288 篇 f. siegert
283 篇 r. ströhmer
281 篇 m. rijssenbeek
279 篇 s. jin
279 篇 g. gaudio
278 篇 s. mohapatra
272 篇 y. tayalati
268 篇 s. guindon
263 篇 a. kaczmarska
257 篇 j. schaarschmidt
253 篇 a. d. pilkington
252 篇 m. klein
250 篇 l. chevalier

语言

2,489 篇 英文
215 篇 其他
15 篇 中文

检索条件"机构=Computer Science And Engineering V.S.B Engineering College"

共 2713 条记录，以下是921-930 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：

Outage Probability of an Underwater Wireless system based on the CsK Transmission

Outage Probability of an Underwater Wireless System Based on...

引用

2022 International symposium on Networks, computers and Communications, IsNCC 2022

作者： Fon, R.C. Igboamalu, F. Ndjiongue, A.R. Ouahada, K. Leke, C. Abu-Mahfouz, A.M. University of Johannesburg Faculty of Engineering and the Built Environments Dept. Electrical and Electronic Engineering Science P.O. Box 524 Auckland Park Johannesburg2006 South Africa Memorial University Faculty of Engineering and Applied Science Dept. of Electrical and Computer Engineering 240 Prince Phillip Drive 40 Arctic Ave St. John'sNLA1B 3X7 Canada School of Accounting College of Business and Economics P.O. Box 524 Auckland Park Johannesburg2006 South Africa Pretoria0184 South Africa

ISBN: (数字)9781665485449

ISBN: (纸本)9781665485449

Compared to well-established underwater acoustic communication techniques, underwater wireless optical communication (UWOC) offers significantly more transmission bandwidth and can be used in multiple short-range marine applications. Color-shift keying (CsK) is a modulation techniques advocated for deploying high data rate transmission in red, green and blue (RGb) based laser technology. It utilizes light sources that produce Lambertian light patterns. Consequently, the broadcast message arrives at the receiver via line-of-sight (Los) pathways, with the Rician distribution being used to model the appropriate channel. This paper analyzes UWOC v.s.ble light communication (vLC) links using light emitting diodes (LDs) as transmitter with small angular divergence. The channel direct current (DC) gains is considered in the analysis to show the channel gain, signal-to-noise ratio (sNR), channel capacitance, and outage probability. This study also looks at the outage probability or the locally observed sNR of the CsK link below the threshold set for a particular quality of services. The results are depicted for a random white light in an UWOC system clean ocean. They shows that the sNR of the RGb based Laser UWOC is proportional to P_t/N_0. The results also shows that the channel capacity increases with P_t/N_0 depending on the attenuation intensity ß. Finally, as the data rate increases with a fixed P_t/N_0, the outage probability increases. The data rate increases with P_t/N_0 and the transmission power with a fixed value outage probability. © 2022 IEEE.

关键词： signal to noise ratio

来源：评论

学校读者我要写书评

暂无评论

A Novel Cell Density Prediction Design using Optimal Deep Learning with salp swarm Algorithm

A Novel Cell Density Prediction Design using Optimal Deep Le...

引用

International Conference on Trends in Electronics and Informatics (ICEI)

作者： Govind Hanmantrao balde Md. Abul Ala Walid srinivasan P venkata Rajesh Yella M. soumya Ravi Rastogi Research and P.G. Department of Zoology N.T.V.S's G. T. Patil Arts Commerce and Science College Nandurbar M.S. India Department of Computer Science and Engineering Khulna University of Engineering and Technology (KUET) Khulna Bangladesh Department of ECE Sona college of Technology Salem Tamilnadu India Department of Biotechnology Koneru Lakshmaiah Education Foundation Vaddeswaram Andhra Pradesh INDIA Department of Computer Science & Artificial Intelligence SR University Warangal Telangana India Electronics Engineering NIELIT Gorakhpur Uttar Pradesh India

Cell density prediction can be defined as the process of predicting the number of cells in a given quantity of a culture or cell suspension. It is considered a common practice in cell biology since cell density had a significant impact on cell behavior and can be utilized for monitoring the health and growth of cell culture. Precise prediction of cell density was significant for a range of applications in cell biology., which includes bioprocessing, cell-based assays, and cell culture. Therefore, this article develops a novel Cell Density Prediction design using Optimal Deep Learning with salp swarm Algorithm (CDP-ODLssA) technique. The presented CDP-ODLssA technique predicts the cell densities accurately on the images of cell suspensions or cultures. To do so, the presented CDP-ODLssA technique employs Long short Term Memory-Autoencoder (LsTM-AE) model for prediction of cell densities. In addition, the hyperparameter tuning of the LsTM-AE model takes place by the use of salp swarm Algorithm (ssA). For experimental validation of the CDP-ODLssA technique, a wide range of simulations was taken place. The obtained values highlighted the superiority of the CDP-ODLssA technique compared to other approaches.

关键词： Deep learning Predictive models Prediction algorithms Market research behavioral sciences Informatics Tuning

来源：评论

学校读者我要写书评

暂无评论

A Comprehensive Design of Regulated voltage Flow Control Mechanism using DC-to-DC boost Converter

A Comprehensive Design of Regulated Voltage Flow Control Mec...

引用

smart Technologies in Computing, Electrical and Electronics (ICsTCEE), International Conference on

作者： Rajalakshmi G M. Uma Maheswari senthilkumar b b. Anni Princy Glory E s. Ganga Department of ECE Sathyabama Institute of Science and Technology Chennai Tamil Nadu India Department of EEE R.M.D. Engineering College Chennai Tamil Nadu India Department of EEE V.S.B. Engineering College Karur Tamil Nadu India Department of CCE Panimalar Engineering College Chennai Tamil Nadu India Department of Biosciences Saveetha School of Engineering SIMATS Chennai Tamil Nadu India Department of Information Technology Prince Shri Venkateshwara Padmavathy Engineering College Chennai Tamil Nadu India

ISBN: (数字)9798350384628

ISBN: (纸本)9798350384635

The outcomes of this research have led to the development of an innovative method for converters that enables the flexible distribution of load power across several inputs. In addition, the management of energy storage input sources like charging and discharging may be done with a high degree of precision. The primary objective of this project is to construct a DC-to-DC boost converter and test its performance in real-world conditions. The input and output voltages are managed by a microprocessor, which is also responsible for transmitting the necessary control signal to the switching circuit. The input and output voltages are shown on a liquid crystal display (LCD). In response to the information provided by the potentiometer, the microcontroller alters the proportion of time that the control signal is active. This modulates the output voltage. The off-line power supply of a computer, for example, takes the 120v or 240v ac energy supplied by the utility company and rectifies it into a dc value of around 170v or 340v. A constant supply of either 5v or 3.3v is often required by the processor ICs; hence, a dc-dc converter lowers down the voltage to one of those levels. This system's dynamic behavior is nonlinear because it functions in switch-mode, which operates in a nonstandard manner. Alterations in the load or the input line voltage are two examples of the kind of significant changes that might cause the system to vary from its regular settings and make it susceptible to failure. because the input is often derived from a solar array, the design and simulation that is presented in this work account for the whole spectrum of radiations and temperatures. During the course of this study, we investigate the boost converter equations and recommend the design components and simulation for a DC/DC converter. The study will be carried out in a solar system to establish the times of day during which the system generates the most amount of power.

关键词： voltage measurement Microcontrollers system dynamics Transportation switches Liquid crystal displays Hardware

来源：评论

学校读者我要写书评

暂无评论

An Advanced Learning based Diabetes Mellitus Prediction Using KNN

An Advanced Learning Based Diabetes Mellitus Prediction Usin...

引用

IoT based Control Networks and Intelligent systems (ICICNIs), International Conference on

作者： sriharsha vikruthi Tejesh Reddy singasani v T Ram Pavan Kumar M K spandana M Narasimha Raju Ch Raghavendra Dept of CSE B V Raju Institute of Technology Narsapur Medak Telangana India Dept of Computer Science Kakaraparti Bhavanarayana College Vijayawada Andhrapradesh India Dept of CSE(Data Science) Vignana Bharathi Institute of Technology Ghatkesar Hyderabad Dept of CSE Shri Vishnu Engineering College for Woman Bhimavaram India Dept of CSE(Data Science) KKR & KSR Institute of Technology and Sciences Guntur Andhra Pradesh

ISBN: (数字)9798331518097

ISBN: (纸本)9798331518103

Diabetes Mellitus (DM) is one of the chronic diseases that variations in blood sugars may cause. If it is not identified in the early stages, this may lead to severe issues over health. Diabetes may cause many side effects to the human body. Thus, detecting and diagnosing in the early stages is very important. This paper uses the advanced learning model to detect diabetes mellitus using K-Nearest Neighbours (KNN) combined with other hybrid techniques. The quality and relevance of the input were improved by using various data preprocessing techniques and feature selection methods to solve missing value issues. The KNN in this scenario performed better because of its intelligibility and efficiency in classifying the DM to obtain predictive results. The performance of the proposed approach was analyzed using confusion matrix metrics, which show actual values and predicted values. The results show that the proposed approach outperforms the results based on the given dataset.

关键词： Measurement Data preprocessing Nearest neighbor methods Feature extraction Diabetes Intelligent systems Diseases

来源：评论

学校读者我要写书评

暂无评论

An Automatic ATM Card Fraud Detection Using Advanced security Model based on AOA-CNN-XGboost Approach

An Automatic ATM Card Fraud Detection Using Advanced Securit...

引用

Electronics, Computing, Communication and Control Technology (ICECCC), International Conference on

作者： T. Porkodi R. Rajkumar R. sathiya M. senthil Raja Department of Commerce B. S. Abdur Rahman Crescent Institute of Science & Technology Chennai Tamil Nadu India Department of Commerce St. Joseph's College of Arts & Science (Autonomous) (Affiliated to Annamalai University Chidambaram) Cuddalore Tamil Nadu India Department of Computer Science St. Ann's College of Arts & Science (Affiliated to Annamalai University Chidambaram) Tindivanam Tamil Nadu India Department of Computing Technologies SRMIST Kattankulathur College of Engineering & Technology Chennai Tamil Nadu India

ISBN: (数字)9798350371802

ISBN: (纸本)9798350371819

The implications of financial fraud are becoming more significant as the risk of it grows. For two main reasons, data mining for the purpose of detecting ATM card fraud is quite difficult. First, datasets about ATM card fraud frequently display significant bias. second, what constitutes legitimate and fraudulent behavior is defined differently every time. The variables chosen and the sample methods used have a direct bearing on how well ATM card fraud detection algorithms work. Card fraud at ATMs is a major threat to the security of online payment systems and banking. Model training, feature reduction, preprocessing, and procedure selection must all be part of a systematic approach. The importance of preprocessing in avoiding inaccurate model output and keeping data quality high cannot be overstated. As part of the preprocessing step known as feature reduction, correlation-based measures are used to examine feature correlation. After that, the model is trained using AOA-CNN-XGboost, which produces remarkable outcomes with a 97.13% accuracy rate.

关键词： Training Correlation Accuracy systematics Computational modeling Data models Fraud

来源：评论

学校读者我要写书评

暂无评论

Enhanced security for the authentication of digital signature from the key generated by the CsTRNG method 3

Enhanced security for the authentication of digital signatur...

引用

3rd International Conference on smart systems and Inventive Technology, ICssIT 2020

作者： Prasad, b.v.v.s. Mandapati, sridhar Haritha, b. begum, Md.Jareena Computer Science Engg. Chebrolu Engineering College Guntur India R. V. R J. C COLLEGE of ENGINEERING Department of Computer Applications Guntur India Computer Science Engg. Bapatla Women's Engineering College Bapatla India

ISBN: (纸本)9781728158211

security is the most critical feature of the present e-world. Many applications are based on random number generation. In the present situation, it is very difficult to hide the data. so the key-based encryption process is suggested to keep the files secure. The protection of the data depends on the key. Key generation is more important for all cryptography applications, which is entirely dependent on randomness. As long as many designers have been able to develop many Random Number Generator-based keys. Also work is going on to make hacker data more stable. CsTRNG can be suggested in this work. One of the most commonly used technologies in the marketing field is the production of digital signatures. The generation of digital signatures can be generated using many keys that have the property of RNG. The most stable RNG is the Cryptographically secured True Random Number Generator (CsTRNG). This could generate more unexpected numbers. Work has been built on the Xilinx IsE simulator. © 2020 IEEE.

关键词： Cryptography

来源：评论

学校读者我要写书评

暂无评论

safeguarding Wireless Networks in IoT with sophisticated Privacy Optimization Approach

Safeguarding Wireless Networks in IoT with Sophisticated Pri...

引用

International conference of Electronics, Communication and Aerospace Technology (ICECA)

作者： vijay A vasanth P.Felcy Judith Charushila Axay Patel R Revathi s. Arun R. Thiyagarajan Department School of Computing SRM Institute of Science & Technology Kattankulathur Dept of Computer Applications T.John College Department of Electrical Engineering B V Patel Institute of Technology (DS) Vidyabharti Trust Campus Umrakh Department of Computer Science Karpagam Academy of higher education Department of ECE Jerusalem College of Engineering Chennai India Department of IT Prathyusha Engineering College Chennai India

ISBN: (纸本)9781665482721

IoT security management must study and recognize that IoT security is a challenging issue. The security needs vary as there are more end points at risk when connecting potentially millions of IoT devices. Threat surveillance and remediation capabilities are provided by network-based security systems to lower the likelihood of threats occurring in the first place. This paper aids in determining the security requirements and to ideate a tool for the same. It is also vital to have an integration roadmap for the tool to be used for easy installation and access. Focusing on avoiding attacks provides the knowledge needed for choosing the best IoT security solution. In the proposed work, an integrated solution which has four modules such as Access Control, Network segmentation, Malware Protection and Optimal Allocation has been given.

关键词： Access control Privacy Wireless networks surveillance security management Malware security

来源：评论

学校读者我要写书评

暂无评论

DeepMind Trainer: Harnessing Cognitive Neural Networks on Raspberry Pi for Advanced Cognitive Enhancement Games

DeepMind Trainer: Harnessing Cognitive Neural Networks on Ra...

引用

Advancement in Computation & computer Technologies (InCACCT), International Conference on

作者： P. Abirami D. Antony Joseph Rajan T. vivekanandan v. saillaja N. Mohankumar M. Rajmohan Department of Artificial Intelligence and Data Science Velammal Institute of Technology Chennai Tamil Nadu India Department of Computer Science and Engineering Saveetha School of Engineering Saveetha Institute of Medical and Technical Sciences Chennai Tamil Nadu India Department of Mathematics Vel Tech Multi Tech Dr Rangarajan Dr Sakunthala Engineering College Chennai Tamil Nadu India Faculty of Management Studies SRM Institute of Science and Technology Kattankulathur Chennai Tamil Nadu India Department of Electronics and Communication Engineering B.V. Raju Institute of Technology Telangana India Department of Electronics and Communication Engineering Hindustan Institute of Technology and Science Chennai Tamil Nadu India

ISBN: (数字)9798350371314

ISBN: (纸本)9798350371321

The presentation summarizes a groundbreaking cognitive training program designed specifically for those who suffer from cognitive impairments or neurodevelopmental abnormalities. The work creates a dynamic platform for immersive and adaptable cognitive training games by combining cutting-edge Convolutional Neural Networks (CNNs) with Raspberry Pi technology. Memory, focus, and ability to think creatively are all qualities directly targeted by these games. The CNN model, trained on a broad dataset, interprets real-time user inputs, delivering quick feedback and altering game complexity depending on an individual’s performance. The incorporation of Raspberry Pi guarantees a solution that is both affordable and easily accessible. The capacity of the system to redefine cognitive rehabilitation by providing a solution that is individualizable, interactive, and broadly deployable is the potential source of the system’s influence. The goal of the work is to make a substantial contribution to the field, which will eventually be to the advantage of users, caregivers, and healthcare professionals and ultimately improve the cognitive well-being of those coping with cognitive issues.

关键词： Training Psychology Medical treatment Games software Real-time systems Complexity theory

来源：评论

学校读者我要写书评

暂无评论

The Intelligent smart City Deployment via Artificial Intelligence software Networking 2

The Intelligent Smart City Deployment Via Artificial Intelli...

引用

2nd International Conference on Advance Computing and Innovative Technologies in engineering, ICACITE 2022

作者： Gupta, Ayan Das Kishore, K. Prasad, Arun b Kannadasan, b. Narayana, M srinivasa singh, Prabhdeep Chandernagore Government College Postgraduate Department of Geography West Bengal Hooghly India Chandernagore Government College Affiliated to the University of Burdwan India Voorhees College Department of Commerce Vellore India Institute of Law Nirma University Gujarat Ahmedabad India B.S.Abdur Rahman Crescent Institute of Science and Technology Department of Civil Engineering Vandalur Chennai India Kl Business School K L University Koneru Lakshmaiah Education Foundation Vijayawada India Graphic Era Deemed to Be University Department of Computer Science & Engineering Uttarakhand Dehradun India

ISBN: (纸本)9781665437899

The software Defined Network (sDN) structure is a novel approach to network management. switches in sDN do not process incoming packets in the same way that they do in a traditional network computing environment. They look in the linking tables for incoming packets, and if none are found, they are sent to the control system for processing, which is the sDN's operating system. The most serious threat to cyber security in an sDN network is a spread Denial of service (Dodos) attack. The attack will take place at the network or application layers of the infected devices that are linked to the network. In this paper, an intelligent machine learning-based method for detecting whether incoming packets are infected or not is proposed smart city activities seek to go beyond the limitations of traditional urban planning, which regulates critical infrastructures in silos, and to profit on the pervasiveness of data and services given by electronic technologies such as machine learning, the internet of things, affordable and big data. © 2022 IEEE.

关键词： Machine learning

来源：评论

学校读者我要写书评

暂无评论

breast Cancer segmentation by K-Means and Classification by Machine Learning

Breast Cancer Segmentation by K-Means and Classification by ...

引用

Automation, Computing and Renewable systems (ICACRs), International Conference on

作者： K. Priya v. senthilkumar J samson Isaac sreekanth Kottu v s Ramakrishna M Jogendra Kumar Department of Computer Science P. B Siddhartha College of Arts and Science Vijayawada Andhra Pradesh India Department of Electronics and Communication Engineering Er. Perumal Manimekalai College of Engineering koneripalli Hosur Tamil Nadu India Department of Biomedical Engineering Surgical and Critical care Equipments Laboratory Karunya Institute of Technology and Sciences Coimbatore Tamil Nadu India Department of Information Technology St Peter’s Engineering College Malkajgiri Telangana India Department of Computer Science Engineering BVC Engineering College Odalarevu Andhra Pradesh India Department of Computer Science and Engineering Koneru Lakshmaiah Education Foundation Vaddeswaram Andhra Pradesh India

ISBN: (纸本)9781665460859

breast Cancer (bC) progression is currently a common health problem among modern women. It is the cause of death for a significant number of women. bC is the growth of malignant cells in the breast tissue. Adipose or connective tissue can also develop bC. because of developments in medical technology, ultrasonography is one of many procedures utilised for the early identification of cancer. Ultrasound is a technique that uses high-frequency sound wave technology to create images of inside body structures such as organs and soft tissues. because of the poor quality of the information, there is a lot of possibility for interpretational mistakes when diagnosing cancer based on ultrasound images. As a result of these concerns, this paper uses the idea of Machine Learning (ML) is employed for the classification and segmentation of bC. The K-means clustering approach is used as part of the segmentation procedure to detect where the cancer is present. A recent study has demonstrated that machine learning produces reliable findings, allowing specialists to make better decisions. Using standard bC datasets, the performance of three different Machine Learning algorithms—Logistic Regression (LR), Random Forest (RF), and K-Nearest Neighbors (KNN)—is tested in this work. In terms of accuracy, RF outperformed the other algorithms, according to the finding. Future bC researchers will be able to utilise the findings of this study to guide their investigations and influence their efforts to improve the efficiency of specific algorithms.

关键词： Radio frequency Measurement Image segmentation Machine learning algorithms Medical services Ultrasonography breast cancer

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272页 << < 89 90 91 92 93 94 95 96 97 98 > >>

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：