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

1,088 篇 会议
4 册 图书
4 篇 期刊文献

馆藏范围

1,096 篇 电子文献
0 种 纸本馆藏

日期分布

学科分类号

477 篇 工学
- 396 篇 计算机科学与技术...
- 335 篇 软件工程
- 141 篇 信息与通信工程
- 102 篇 生物工程
- 87 篇 生物医学工程（可授...
- 71 篇 电气工程
- 71 篇 控制科学与工程
- 58 篇 化学工程与技术
- 56 篇 电子科学与技术（可...
- 38 篇 网络空间安全
- 37 篇 仪器科学与技术
- 36 篇 材料科学与工程（可...
- 35 篇 光学工程
- 29 篇 机械工程
- 27 篇 石油与天然气工程
- 27 篇 安全科学与工程
277 篇 理学
- 134 篇 数学
- 108 篇 生物学
- 83 篇 物理学
- 58 篇 统计学（可授理学、...
- 55 篇 化学
- 41 篇 系统科学
150 篇 管理学
- 86 篇 图书情报与档案管...
- 77 篇 管理科学与工程(可...
- 44 篇 工商管理
51 篇 医学
- 49 篇 基础医学(可授医学...
- 49 篇 临床医学
- 37 篇 药学(可授医学、理...
44 篇 法学
- 31 篇 社会学
28 篇 农学
- 27 篇 作物学
21 篇 经济学
10 篇 教育学
3 篇 文学
1 篇 哲学
1 篇 军事学
1 篇 艺术学

主题

157 篇 data engineering
126 篇 computer science
94 篇 conferences
73 篇 computational mo...
56 篇 data models
49 篇 deep learning
48 篇 machine learning
46 篇 predictive model...
39 篇 training
33 篇 feature extracti...
31 篇 support vector m...
31 篇 neural networks
29 篇 machine learning...
22 篇 covid-19
19 篇 education
19 篇 prediction algor...
18 篇 data visualizati...
16 篇 real-time system...
16 篇 social networkin...
16 篇 software

机构

10 篇 queensland unive...
10 篇 brac university ...
8 篇 school of comput...
8 篇 graduate school ...
7 篇 brac university ...
7 篇 school of comput...
7 篇 department of co...
7 篇 computer science...
7 篇 school of inform...
7 篇 school of comput...
6 篇 school of engine...
6 篇 college of infor...
6 篇 school of comput...
5 篇 brac university ...
5 篇 school of inform...
5 篇 school of food a...
5 篇 department of el...
5 篇 doshisha univers...
5 篇 graduate school ...
5 篇 hong kong metrop...

作者

17 篇 neeraj anand sha...
12 篇 md. golam rabiul...
11 篇 sharma neeraj an...
11 篇 bibhya sharma
10 篇 md. ashraful ala...
9 篇 alam md. golam r...
9 篇 richard o. sinno...
9 篇 katsunori shimoh...
9 篇 shimohara katsun...
9 篇 a b m shawkat al...
8 篇 sharma bibhya
8 篇 girija chetty
7 篇 ryo shioya
7 篇 tanaka mizuki
7 篇 shioya ryo
7 篇 shiozu yurika
7 篇 hiromitsu shimak...
7 篇 kunal kumar
7 篇 alam md. ashrafu...
7 篇 mizuki tanaka

语言

1,091 篇 英文
5 篇 其他

检索条件"任意字段=2023 IEEE Asia-Pacific Conference on Computer Science and Data Engineering, CSDE 2023"

共 1096 条记录，以下是81-90 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：

Text Classification on Imbalanced data using Graph Neural Networks and Adversarial Weight Balancer

Text Classification on Imbalanced Data using Graph Neural Ne...

引用

2023 ieee asia-pacific conference on computer science and data engineering, csde 2023

作者： Badiei, Fatemeh Kananian, Makan Ghahramani, S. AmirAli Gh. Sharif University of Technology Department of Computer Engineering International Campus Kish Island Iran

ISBN: (纸本)9798350341072

Text classification in imbalanced datasets poses a significant challenge in natural language processing (NLP) applications. In this paper, we address this issue by treating text data as graphs, with words as nodes, and employ two strategies for establishing connections between words within these graphs. The first strategy employs a fixed-size context window to connect words that lie within the same window, while the second strategy leverages word embedding vectors and a k-nearest neighbors (KNN) approach to connect each word to its k most similar neighbors. To further enhance the classification performance, we combine Graph Convolutional Neural Networks (GCNs) and Long Short-Term Memory (LSTM) networks to process the textual information. Importantly, we address the challenge of class imbalance using an adversarial loss framework. We introduce separate weight generator networks for each class within the dataset, responsible for dynamically assigning weights to individual samples during training. While the classifier aims to minimize its weighted cross-entropy loss, the weight-generating networks strategically assign higher weights to misclassified samples and reduce the weights assigned to correctly classified ones, thus increasing the classifier's loss in subsequent epochs. This adversarial loss, in conjunction with the LSTM-GCN architecture, results in finely tuned sample weights, leading to significantly improved accuracy and F1-Score compared to conventional methods for handling imbalanced text classification problems. Our experimental results demonstrate the effectiveness of our approach in addressing the challenges of imbalanced text classification, offering a solution for a wide range of NLP applications where imbalanced datasets are prevalent. © 2023 ieee.

关键词： Long short-term memory

来源：评论

学校读者我要写书评

暂无评论

Using Novel Hybrid Convolutional Neural Network for Dysarthria Diagnosis

Using Novel Hybrid Convolutional Neural Network for Dysarthr...

引用

2023 ieee asia-pacific conference on computer science and data engineering, csde 2023

作者： Thilakarathne, Navod Neranjan Galajit, Kasorn Karnjana, Jessada Pa, Win Pa Yassin, Hayati Universiti Brunei Darussalam Faculty of Integrated Technologies Brunei Nectec National Science and Technology Development Agency Pathum Thani Thailand University of Computer Studies Yangon Myanmar

ISBN: (纸本)9798350341072

Dysarthria is a motor speech disorder characterized by articulation and phonation difficulties resulting from speech muscle weakness, paralysis, or incoordination. A precise and timely diagnosis of dysarthria is essential for effective treatment and management of the condition, as it may deteriorate over time or be a precursor to a much more serious disease. On the other hand, this is becoming a severe problem in recent times owing to the rising ageing population and the prevalence of neurological disorders among such people. Hence early detection of dysarthria is deemed essential for the timely management of the disease. In recent years, Artificial Intelligence (AI) applications have shown promising results in various audio processing tasks and incorporated into pathological voice analysis for disease diagnosis. The majority of previous studies on dysarthria detection employed Machine Learning (ML) and Deep Learning (DL) models as the disease classification models. In light of this, this study presents a novel hybrid approach for classifying dysarthria based on audio data using Convolutional Neural Network (CNN) and Support Vector Machine (SVM). According to the experimental results, the proposed classification schema achieves an accuracy of 98.25 % compared to previous research work. Overall, our proposed method aims to automate the classification process, enabling faster and more reliable diagnoses. © 2023 ieee.

关键词： Support vector machines

来源：评论

学校读者我要写书评

暂无评论

Two-Stage Fine-Tuning For Low-resource Englishbased Creole with Pre-Trained LLMs

Two-Stage Fine-Tuning For Low-resource Englishbased Creole w...

引用

2023 ieee asia-pacific conference on computer science and data engineering, csde 2023

作者： Amanda Tan, Shu Hui Aung, Eint Sandi Yamana, Hayato Department of Computer Science and Communications Engineering Waseda University Tokyo Japan Waseda University Faculty of Science and Engineering Tokyo Japan

ISBN: (纸本)9798350341072

Sentiment analysis adopts natural language processing (NLP) techniques to determine the emotional tone of the text. Sentiment analysis research has predominantly been conducted on commonly spoken languages, such as English and Mandarin Chinese. However, less widely spoken languages, such as Englishbased Creoles, have received limited attention due to the need for large-scale labeled datasets. English-based Creoles are derived from English, resulting in many similarities with English. However, English-based Creoles differ from English in some aspects, making the Creole unintelligible to other English speakers. In sentiment analysis research conducted on Singapore English-based Creole (Singlish), most existing research does not leverage the capabilities of large-language models, such as pretrained BERT. To our knowledge, only Gotera et al.'s work relates to a large-language model;however, their contribution is creating a new pre-trained model for Singlish. However, creating a new pre-trained model is computationally expensive, and pre-training a less widely spoken language will result in ineffective because of the small dataset. Hence, we propose a new two-stage fine-tuning framework for pre-trained models, targeting a low-resource English-based Creole, Singlish. Our proposed framework initially clusters the dataset into two based on each data point's percentage of English words. Then, two-stage fine-tuning is performed by transferring the pre-trained BERT model onto the clustered dataset with the higher English percentage in the first stage. The model is further transferred onto the clustered dataset with the lower English percentage in the second stage. Our proposed framework outperforms the traditional fine-tuning framework, achieving a weighted F1 score of 0.8344 for sentiment analysis. © 2023 ieee.

关键词： Sentiment analysis

来源：评论

学校读者我要写书评

暂无评论

Review of Secure Healthcare and Patient Monitoring System Using Block Chain for Accessing Medical Records

Review of Secure Healthcare and Patient Monitoring System Us...

引用

2023 ieee asia-pacific conference on computer science and data engineering, csde 2023

作者： Tabassum, Kahkashan Abukhamis, Leena Abdulaziz Ccis Princess Nourah Bint Abdulrahman University Department of Computer Sciences Riyadh Saudi Arabia

ISBN: (纸本)9798350341072

Healthcare industry is evolving rapidly due to the rigorous research and development in health care industry and is contributing to the enormous development the most happening and upcoming innovative block chain technology. This development in both health care and technological industry has enhanced the quality of fitness of an individual by the use of miniaturized sensors that could be invasively or non-invasively embedded to monitor human vital signs to offer a secure patient healthcare system. When sharing personal medical information, data security and comfort are essential requirements for interaction with electronic medical records. However, it is hard for current systems to meet these requirements because they have inconsistent security policies and access control structures. Another problem is switching the medical providers that is extremely unmanageable and creates tedious issues for medical claim approvals since maximum advanced healthcare systems are distributed greatly with low speed issues and frauds. The new solutions should be directed towards improving data access and should be managed by the government in terms of privacy and security requirements to ensure the reliability of data for medical purposes. Block chain technology is the most unique and real solution that promises secure patient data coordination and whole healthcare system, provides pre-approved constraints. Block chain paves the way for a revolution in the traditional pharmaceutical industry and benefits from unique features such as data privacy and transparency. This paper proposes a block chain solution to facilitate patients and healthcare system users to access their health care records with smart contract technology. © 2023 ieee.

关键词： Internet of things

来源：评论

学校读者我要写书评

暂无评论

Performance and Evaluation of Classification Algorithms Using Machine Learning with Comparative Study for Heart Disease Prediction

Performance and Evaluation of Classification Algorithms Usin...

引用

2023 ieee asia-pacific conference on computer science and data engineering, csde 2023

作者： Hossain, Md. Manik Ashraful Alam, Md. Brac University Dept. of Computer Science and Engineering Dhaka Bangladesh

ISBN: (纸本)9798350341072

The leading cause of unseasonable death worldwide is heart complaints. Day by day the causes of heart disease are increasing at a rapid-fire rate and it's veritably important and concerning to prognosticate any such disease beforehand. Predicting how illness will affect a person is a delicate challenge. Machine learning is being applied in different fields around the world. In the healthcare sector, there is no exception. data classification models and machine learning algorithms stoutly introduce diagnostic guidelines and enable experts to increase the effectiveness of the diagnostic process. The body's remaining organs are given advanced precedence over the nucleus. It provides the body with oxygen. The distribution of heart illnesses among medical practitioners can be estimated via data exploration. Medical facilities can examine various disorders and evaluate emerging diseases thanks to data collecting. Predicting the condition based on recent medical research has the biggest impact. To learn statistics more effectively, a variety of methods are being investigated in the scientific community. The renovation has had a big impact on the metropolitan community's way of life in addition to improving it. In this situation, it's crucial to offer a comprehensive tool that will enable medical professionals to foresee the sickness. Different machine learning applications suggest varying prediction precision. It should be analyzed with Logistic Regression, KNN, Decision tree, Random Forest, SVM, Gaussian NB, Ada Boost Classifier Gradient Boosting Classifier, Quadratic Discriminant Analysis, and MLP Classifier with comparative mean of three data sets. It will be better to investigate the accuracy of prediction from the most concerning algorithms of Machine learning with recall and f-score of the heart data and present it in the table with visual representation. This underpinning research has shown that multilayer perceptron with cross-validation has surpassed all other alg

关键词： Heart

来源：评论

学校读者我要写书评

暂无评论

Detection of DeepFake Videos Using computer Vision and Deep Learning

Detection of DeepFake Videos Using Computer Vision and Deep ...

引用

2023 ieee asia-pacific conference on computer science and data engineering, csde 2023

作者： Rahman, Anisur Rahman, Faria Labib, Tahmidul Uschash, Ehteshamul Islam Chowdhury Adiba, Shihaba Jamal Karim, Dewan Ziaul Brac University Department of Cse Dhaka Bangladesh

ISBN: (纸本)9798350341072

DeepFakes are one of the most alarming concepts in this era of Metaverse and technological advancement. DeepFakes are artificially-generated manipulated photos or videos using Deep learning, Generated Adversarial Network (GAN), autoencoder-decoder pairing structure etc. There are several other Deepfaking tools such as;FaceSwap, DeepFace-Lab, DFaker, DeepFake-tensorflow etc. DeepFakes can become concerning if it is used for political purpose, committing fraud, spreading misinformation, pornography, defamation on social media etc. As a result, it is obvious that DeepFakes can be very distressing on the wrong hand if not detected properly. To address this issue, our research aims to develop effective methods for DeepFake video detection, focusing on deep learning approaches, and computer vision techniques. We deployed a dataset consisting of both real and fake videos, obtained from DeepFake Detection Challenge (DFDC) and FaceForensics++. To detect the fake videos, we followed the method of employing temporal feature and exploring visual artifacts within frames. Employing temporal feature uses LSTM and CNN whereas visual artifacts within frames mostly employs deep learning method to detect DeepFakes. We ensembled LSTM and CNN to detect DeepFakes successfully. ResNeXt101-32x8d have been used to extract features and a custom CNN model is added with LSTM for better accuracy for detecting DeepFake. Our ensemble model, which combines LSTM and CNN, successfully detects Deepfakes with an accuracy of 94.05%. Through further improvements and the implementation of learning rate schedulers, such as CosineAnnealingLR, CyclicLR, MultiStepLR, and ReduceLRonPlateau, we achieved even higher accuracy. Among these schedulers, MultiStepLR demonstrated the highest accuracy of 95.33%. © 2023 ieee.

关键词： Feature extraction

来源：评论

学校读者我要写书评

暂无评论

An Investigation on Received Signal Strength Indicator for Wireless Connection such as Bluetooth in an IoT-based Indoor Environment

An Investigation on Received Signal Strength Indicator for W...

引用

2023 ieee asia-pacific conference on computer science and data engineering, csde 2023

作者： Bandhana, Deepika Ali, A. B. M. Shawkat The University of Fiji Department of Computer Science and Mathematics Saweni Fiji

ISBN: (纸本)9798350341072

Period advancement initiates people to opt for options to handle tasks smartly that consume less time and enhance productivity in any aspect of life. Similarly, many individuals are conscious about doing things smartly even in a household where people spend considerable time with their families and loved ones. Consequently, the IoT market is manufacturing more smart products, leading homes to procure more of these smart products. At present, the capability of automated products has improved with the internet, which allows the devices to send data back and forth for awareness and interpretation which is indeed useful for informed decision-making in any home-related scenario. It has been noted via studies and observation that a lot of smart products are Bluetoothenabled for convenient wireless connections to ensure data/information exchange in a home-based smart personal area network. However, circumstances have also dictated that initiating Bluetooth connection between devices is another challenge that everyone is facing. Alas, exploring the variables and parameters that determine a successful connection is essential. One such parameter is the Received Signal Strength, which expresses the signal strength of the receiving device. The value that dictates the measurable strength is called the Received Signal Strength Indicator which will be the theme of this empirical study. The experiment involves taking Bluetooth RSSI readings in a household while introducing various variables to observe the changes in the readings. The experiment was conducted at two different locations to avoid biases in readings and to observe a fair relationship between the dependent and independent variables. The independent variables also included weather parameters to observe if weather patterns play a significant role in determining a better Bluetooth connection, indoors. For that reason, 1200 samples of Bluetooth RSSI data were collected per scenario and explored to understand its significanc

关键词： Bluetooth

来源：评论

学校读者我要写书评

暂无评论

Enhancing Quality of Service in Wireless Mesh Networks through Service Discovery Optimization

Enhancing Quality of Service in Wireless Mesh Networks throu...

引用

2023 ieee asia-pacific conference on computer science and data engineering, csde 2023

作者： Nkonki, Thembisa Mathonsi, Topside E. Sithole, Vusi Tshwane University of Technology Department of Information Technology Pretoria South Africa University of Pretoria Department of Computer Science Pretoria South Africa

ISBN: (纸本)9798350341072

Wireless Mesh Networks (WMNs) are an economical solution for achieving continuous connectivity in wide area networks (WANs) with support for mobility. Nonetheless, the increasing number of users in these networks has amplified competition for resources and services. Consequently, the likelihood of encountering issues like link bottleneck, data collisions, and channel interference at the time of locating and accessing services in WMNs has risen, leading to a decline in Quality of Service (QoS). Swift and efficient issue identification is now essential for optimizing the process of locating and accessing services in WMNs. In this upcoming paper, we introduce an innovative service discovery model designed to address the performance challenges in WMNs. Our proposed model seamlessly assimilates the Particle Swarm Optimization (PSO) and Ant Colony Optimization (ACO) algorithms, which we collectively denote as PSO-ACO. The PSO algorithm prioritizes network services, while the ACO algorithm efficiently establishes the most economical path for transmitters seeking requested services. Additionally, we develop and implement a Link Congestion Reduction (LCR) algorithm to determine the sum of service receivers have concurrent access to services. We employed a computer network simulator namely Network Simulator 2 (NS2) for evaluating our proposed algorithm in WMNs. In our performance evaluation, the PSO-ACO algorithm, the PSO algorithm, and the ACO algorithm exhibited average throughput performances of 95%, 70%, and 55%, respectively. Furthermore, the average service discovery delay for the PSO-ACO algorithm was 3 seconds, while the PSO and ACO algorithms had delays of 4.6 seconds and 5.5 seconds, respectively. In terms of service availability, the PSO-ACO algorithm, the PSO algorithm, and the ACO algorithm demonstrated average performances of 93%, 80%, and 71%, respectively. © 2023 ieee.

关键词： Ant colony optimization

来源：评论

学校读者我要写书评

暂无评论

Revolutionizing Road Safety: YOLOv8-Powered Driver Fatigue Detection

Revolutionizing Road Safety: YOLOv8-Powered Driver Fatigue D...

引用

2023 ieee asia-pacific conference on computer science and data engineering, csde 2023

作者： Xie, Shuaiyue Chuah, Joong Huang Chai, Grace Mei Ting Electronics and Computer Science University of Southampton SouthamptonSO17 1BJ United Kingdom University of Malaya Faculty of Engineering Department of Electrical Engineering Kuala Lumpur50603 Malaysia Smart Manufacturing Systems Research Group University of Southampton Malaysia Johor Iskandar Puteri79100 Malaysia

ISBN: (纸本)9798350341072

Driver fatigue is a significant cause of road accidents. Effective real-time fatigue detection systems are necessary to improve road safety. Utilizing a lightweight and fast model and creating an effective fatigue judgment rule is important in detecting fatigue in real-time. In this research, we propose a fatigue detection model based on You Look Only Once version 8 (YOLOv8) model to detect driver's facial features and use percentage of eyelid closure over the pupil over time (PERCLOS) and Percentage of Open Mouth (POM) indicators to identify fatigue. This research is divided into two parts. The first part involves creating, labeling, and preprocessing the dataset. We use the YawDD dataset as the original dataset and manually label a new dataset using the Roboflow platform. We then preprocessed the new dataset to train the YOLOv8 model for face features detection. In the second part, we established a multi-indicator fatigue determination rule that uses PERCLOS and POM indicators and set a threshold to determine whether the driver is fatigue. By combining the YOLOv8 model with the fatigue determination rules based on PERCLOS and POM, we successfully built a model to identify a driver's fatigue. Finally, the fatigue detection model based on YOLOv8 achieves a high accuracy rate of 96.9% and a high speed of 11.4 ms/frame in face features detection, surpassing other traditional models and previous generations of YOLO models. This model can effectively detect fatigue in both driver-driving pictures and videos. © 2023 ieee.

关键词： Roads and streets

来源：评论

学校读者我要写书评

暂无评论

IoT-Powered Pest Management System for Chili Plants: Analyzing the Effects of Various Light Spectrum Towards Pest and Plant Health

IoT-Powered Pest Management System for Chili Plants: Analyzi...

引用

2023 ieee asia-pacific conference on computer science and data engineering, csde 2023

作者： Hasyer, Muhamad Ahmad Khalid, Ahmad Muzakker Neranjan, Navod Belayan, Joshua Metali, Faizah Yassin, Hayati Baka, Muhammad Saifullah Abu Universiti Brunei Darussalam Faculty of Integrated Technologies Jalan Tungku Link BE1410 Brunei Environmental and Life Sciences Programme Faculty of Science Universiti Brunei Darussalam Jalan Tungku Link BE 1410 Brunei

ISBN: (纸本)9798350341072

Using different light spectra in pest management has gained significant attention due to its potential impact on pest control strategies. This study investigates the effectiveness of the light spectrum in controlling pests and their implications on the health of chili plants. In this regard, we have used an IoT-powered pest management system to monitor and analyze the impacts of the light spectrum on both pests and plant growth. From the experiments, it is evident that, on average, the green-light spectrum showed the most effective protection against pest infestations, while the red-light spectrum showed the least efficacy. Furthermore, in terms of plant health, at day 0 and 7, the chlorophyll contents of chilli plants from Station 3 (violet) and Station 2 (green) were the lowest and greatest, respectively, while at day 14, Station 2 (green) and Station 3 (violet) recorded the lowest and greatest chlorophyll content, respectively. These results suggest that in the early stage of plant growth, green light promoted better plant growth, whereas violet light enhanced growth after 14 days. Overall, this study provides insights into the importance of considering a balanced light spectrum in pest management control strategies and the enhancement of plant growth and health for chilli plants. © 2023 ieee.

关键词： Chlorophyll

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110页 << < 5 6 7 8 9 10 11 12 13 14 > >>

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：