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

6,378 篇 会议
161 册 图书
46 篇 期刊文献

馆藏范围

6,585 篇 电子文献
0 种 纸本馆藏

日期分布

学科分类号

4,749 篇 工学
- 4,176 篇 计算机科学与技术...
- 3,369 篇 软件工程
- 1,157 篇 信息与通信工程
- 762 篇 生物工程
- 563 篇 生物医学工程（可授...
- 497 篇 控制科学与工程
- 420 篇 电气工程
- 326 篇 动力工程及工程热...
- 267 篇 机械工程
- 254 篇 光学工程
- 251 篇 电子科学与技术（可...
- 240 篇 安全科学与工程
- 219 篇 化学工程与技术
- 214 篇 环境科学与工程（可...
2,076 篇 理学
- 942 篇 数学
- 830 篇 生物学
- 413 篇 物理学
- 399 篇 统计学（可授理学、...
- 278 篇 系统科学
- 222 篇 化学
1,415 篇 管理学
- 784 篇 管理科学与工程(可...
- 774 篇 图书情报与档案管...
- 514 篇 工商管理
615 篇 医学
- 580 篇 临床医学
- 555 篇 基础医学(可授医学...
- 331 篇 药学(可授医学、理...
- 302 篇 公共卫生与预防医...
359 篇 法学
- 266 篇 社会学
208 篇 农学
- 199 篇 作物学
197 篇 经济学
- 196 篇 应用经济学
132 篇 教育学
23 篇 军事学
13 篇 文学

主题

278 篇 internet of thin...
262 篇 machine learning
253 篇 cloud computing
230 篇 big data
219 篇 computational mo...
207 篇 deep learning
182 篇 data mining
157 篇 data models
137 篇 predictive model...
135 篇 artificial intel...
133 篇 training
130 篇 feature extracti...
122 篇 real-time system...
119 篇 blockchain
108 篇 support vector m...
107 篇 accuracy
107 篇 machine learning...
102 篇 convolutional ne...
100 篇 forecasting
96 篇 medical services

机构

54 篇 graphic era deem...
44 篇 chitkara univers...
24 篇 department of co...
24 篇 department of co...
21 篇 department of en...
19 篇 school of comput...
19 篇 teerthanker maha...
18 篇 school of inform...
17 篇 jaipur national ...
16 篇 university of ch...
16 篇 uttaranchal inst...
15 篇 fujian provincia...
14 篇 srm institute of...
14 篇 department of co...
14 篇 uttaranchal inst...
13 篇 computer science...
13 篇 school of comput...
11 篇 uttaranchal inst...
10 篇 college of compu...
10 篇 school of manage...

作者

21 篇 pant bhasker
20 篇 chang kuo-chi
13 篇 tripathi vikas
12 篇 kukreja vinay
12 篇 vinay kukreja
11 篇 jacob lija
11 篇 joshi kapil
11 篇 gangodkar durgap...
10 篇 iwendi celestine
10 篇 lourens melanie
10 篇 chu kai-chun
10 篇 sujithra m.
10 篇 alanya-beltran j...
9 篇 rajeswari d.
9 篇 chang fu-hsiang
9 篇 singh rajesh
8 篇 kapil joshi
8 篇 kapila dhiraj
8 篇 pavithra g.
8 篇 sanjay misra

语言

6,395 篇 英文
184 篇 其他
15 篇 中文

检索条件"任意字段=International Conference on Advances in Data Science and Computing Technologies, ASDC 2022"

共 6585 条记录，以下是151-160 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：

Multi-Camera Trajectory Based Vehicle Re-Identification for Robust Traffic Monitoring

Multi-Camera Trajectory Based Vehicle Re-Identification for ...

引用

advances in Electrical, computing, Communication and Sustainable technologies (ICAECT), international conference on

作者： R. Athilakshmi Emandi Venkata Sanjeevi Sai Prasanna Syed Yasir Department of Computational Intelligence Faculty of Engineering and Technology SRM Institute of Science and Technology Kattankulathur Chennai

ISBN: (数字)9798350356236

ISBN: (纸本)9798350356243

Vehicle Re-Identification (ReID) is the challenging task of identifying the same vehicle across multiple cameras in urban environments. In this paper, we propose a novel MultiCam TrajectoryID model that leverages trajectory-based features, addressing the limitations of single-image-based ReID methods. The system combines feature extraction methods like SIFT with the Kalman filter and You Only Look Once (YOLO) algorithms for trajectory prediction to guarantee accurate and effective tracking of objects across several camera views. This MultiCam TrajectoryID approach enhances traditional single-image vehicle ReID by focusing on the continuity of object movement, improving the robustness of identification in complex, real-world traffic environments. We evaluate the performance of our model on the challenging VeRi-776 dataset and compare it with state-of-the-art methods. The proposed model achieves a mean average Precision (maP) of 86% on VeRi-776 data, outperforming recent approaches such as Multi-Branch Enhanced Discriminative Network and Multi-Fine Grained Network models. This significant improvement demonstrates the effectiveness of trajectory-based re-identification in multi-camera setups and its contribution to vehicle ReID and real-time surveillance systems.

关键词： YOLO Adaptation models Accuracy Surveillance Computational modeling Feature extraction Real-time systems Robustness Trajectory Kalman filters

来源：评论

学校读者我要写书评

暂无评论

Consumer Behavior in the Post-Pandemic Era: Insights from Machine Learning and AI-Driven Analytics

Consumer Behavior in the Post-Pandemic Era: Insights from Ma...

引用

advances in Electrical, computing, Communication and Sustainable technologies (ICAECT), international conference on

作者： Divya Nimma Ch. Anudeep Tripti Sahu Nusrat Hamid Shah Lubna Hamid Shah B Kiran Bala PhD in Computational Science University of Southern Mississippi Data Analyst in UMMC USA Department of Management studies Shri Vishnu Engineering college for women (A) Bhimavaram India MIMA Institute of Management Pune Maharashtra India College of Engineering and Computer Science Jazan University Kingdom of Saudi Arabia Department of Management and Marketing College of Business Jazan University Kingdom of Saudi Arabia Department of AI & DS K.Ramakrishnan College of Engineering Trichy India

ISBN: (数字)9798350356236

ISBN: (纸本)9798350356243

COVID-19 has been the disruptor in the world, and the society has been changed from one perspective of the consumer behavior in terms of digital platforms and their preferences for safety, convenience and sustainability. It is therefore very important for any business to acquaint itself with these changes so that may be in a position to effectively compete for the market within the current ever-changing business environment. Conventional consumer behavior models, on the other hand, rely on fragmented data sources and analytical tools that may not reflect the current post-pandemic consumption patterns. Such models are also incapable of incorporating multiple data types and can also fail to address changing social factors. In response, a Multi-Modal Consumer Behavior Prediction Framework (MCBP) that considers a vast array of data sources is introduced. BERT and GNNs are used to give a detailed, real-time interpretation of consumer behaviour accomplished by the MCBP framework. It uses BERT to extract and analyze sentiment and topics of the textual data and GNNs to capture influence and peer effects on purchase decisions. The findings of the study show the effectiveness of the proposed framework with an accuracy of 99%. 5% and the implementation is done using Python. The high level of accuracy shown assures the success of the MCBP model in measuring and forecasting consumers' behaviors in the post-pandemic world.

关键词： Consumer behavior Accuracy Soft sensors Predictive models data models Social factors Real-time systems Safety Sustainable development Business

来源：评论

学校读者我要写书评

暂无评论

Estimation of Response Time with Neural Networks in Cloud computing System

Estimation of Response Time with Neural Networks in Cloud Co...

引用

advances in Computer science, Electrical, Electronics, and Communication technologies (CE2CT), international conference on

作者： Rajesh More Sanjna Suresh Sathish Kumar Veerappampalayam Easwaramoorthy Haider Ali Rizvi Kannan Kunnathully Sahil K. Gupta Departmen of AIML Cloudwerx Wordwide Hyderabad Department of Computer Science and Engineering Amrita Vishwa Vidyapeetham Coimbatore School of Engineering and Technology Sunway University Selangor Darul Ehsan Malaysia Department of Artificial Intelligence and Machine Learning Yogananda School of Artificial Intelligence Shoolini University Department of Research Veltech University Chennai Department of Computer Science and Engineering Tula's Institute Dehradun India

ISBN: (数字)9798331518578

ISBN: (纸本)9798331518585

Resource allotment, responsiveness, connection, research of unexplored assets, related resource modeling, and asset scheduling are just a few of the numerous factors and concerns that need to be considered to enhance cloud computing efficiency. The functionality of the cloud has a significant impact on the propagation of cloud architecture. Consequently, it is important to determine the components that influence cloud function to analyze it. Response duration is the primary aspect that significantly affects cloud computation functioning, according to the research. The response duration assistance is among the numerous different variables that may be used to organize resource applications. Artificial neural networks (ANNs) were employed as a technique for evaluating the parameter of pursuit, and a fork-join framework or an architecture with demand partitioning was selected as the queuing paradigm. As a result, this study suggests a load-managing method depending on cloud demand response duration using the ARIMA Estimation of Response Duration Method. The fundamental concept is to employ ARIMA methods to estimate the future response duration, providing a more efficient method of allocating resources with limited values. The results of the investigation demonstrated that the estimations were more precise compared to those that had been recently established. The results of the study indicate that estimation is an outstanding path for load balance and has possibility and value for load balance with displayed response duration. Additionally, the suggested method makes it feasible to acquire estimations for a wider range of cloud structure functioning signs compared to earlier feasible and also to extend the evaluation of the cloud platform to the instance of a structure with a non-Poisson data flow and non-exponential assistance duration.

关键词： Computer science Cloud computing Processor scheduling Estimation Computer architecture Artificial neural networks Load management Scheduling Demand response Time factors

来源：评论

学校读者我要写书评

暂无评论

Cloud Based Automated Control System Workshops and Rooms for Controlling Parameters

Cloud Based Automated Control System Workshops and Rooms for...

引用

advances in Computer science, Electrical, Electronics, and Communication technologies (CE2CT), international conference on

作者： Dinesh Kumar Ravinder Singh Kuntal Pragya Deep Anup Shekhar Chamoli Pinki Singh Rishabh Mandal Department of Computer Science and Engineering SRM Institute of Science & Technology Ghaziabad UP Department of Mathematics Nitte Meenakshi Institute of Technology Bangalore Karnataka India Department of AI & DS IIMT College of Engineering Greater Noida India Uttaranchal School of Computing Sciences Uttaranchal University Dehradun India Department of Computer Science and Engineering Accurate College of Engineering & Management Greator Noida India Department of Computer Science and Engineering Tula's Institute Dehradun UK India

ISBN: (数字)9798331518578

ISBN: (纸本)9798331518585

Across all industries, cloud-based automated control systems have completely changed how operational and environmental parameters are tracked and controlled. With cloud-integrated systems for real-time data collection, processing, and control, this concept presents intelligent, remote-controlled workshops and control rooms. To guarantee accurate control of crucial variables like temperature, humidity, pressure, and equipment efficiency, these systems make use of IoT devices, AI techniques, and big data analytics. Through sophisticated data perspectives, the cloud-based strategy enables predictive maintenance, improves flexibility, and lowers operating expenses. Stakeholders may make prompt, data-driven choices from anywhere with remote access to control rooms. These seminars provide practical experience with cloud-controlled settings and function as training and development centres. The system's flexibility to meet a range of industrial demands is further enhanced by its compatibility with external tools and equipment. The design, deployment, and possible uses of cloud-based control systems are covered in this paper, with an emphasis on how they might promote operational excellence, energy efficiency, and smart manufacturing.

关键词： Knowledge engineering Machine control Clouds Control systems Software Machine tools Security Time factors Personnel Standards

来源：评论

学校读者我要写书评

暂无评论

Design and Implementation of a data Encryption Framework Simulink Model for Protecting Sensitive Organizational data

Design and Implementation of a Data Encryption Framework Sim...

引用

advances in Computer science, Electrical, Electronics, and Communication technologies (CE2CT), international conference on

作者： Veera Lakshmayya Patchigolla

ISBN: (数字)9798331518578

ISBN: (纸本)9798331518585

Internet-of-Medical-Things (IoMT) based sensitive data protection has become a critical problem lately. IoMT-sensitive data are used to connect patients with adults. Since every record, data, and healthcare signal is transmitted over these systems, they need strong and safe access methods for individuals to transmit their essential statistics or documents. Because of this, breaching these systems could have negative impacts on patients. An emerging pattern in biometric verification is to prevent using authentic biometrics for security purposes. Cancelable digital fingerprints can be created using a data encryption framework or non-invertible transformations. This study presents an integrated structure for cancelable ECG signal detection that is suitable for use in IoMT networking access steps. The suggested system uses fuzzy reasoning to perform a non-invertible transition on ECG data, altering its shifting spectrum. Cancellable biometric platforms aim to retrieve original ECG data from processing variants, but the procedure is non-invertible and hinders this goal. Next, customized trends are used to build compact encryption using XOR. This eliminates the complication of comprehensive encryption systems requiring significant computing resources. By combining encryption techniques and non-invertible transformations, the encryption phase improves the safety of cancelable biometrics features and permits the mixed nature of the suggested cancelable biometrics architecture. For the actual adoption of the suggested ECG-based cancelable biometrics identification structure, hardware adaptation is also shown. According to empirical findings, the suggested structure performs well, with an Equivalent Error Rate (EER) of 0.059%.

关键词： Software packages Internet of Medical Things Electrocardiography Market research Hardware Encryption Safety Security Signal detection Fuzzy reasoning

来源：评论

学校读者我要写书评

暂无评论

Augmented Reality-Assisted Pediatric Surgery: A Machine Learning-Based Approach for Enhancing Accuracy

Augmented Reality-Assisted Pediatric Surgery: A Machine Lear...

引用

advances in Computer science, Electrical, Electronics, and Communication technologies (CE2CT), international conference on

作者： Sumedha Bhardwaj Swapna Narla Md Nurul Absur Shuvo Dutta J B Hyzil S M Krishna Ganesh Department of School of Computing DIT University Dehradun Uttarakhand India Tek Yantra Inc California USA Computer Science CUNY Graduate Center New York New York USA Department of Physics Western Michigan University USA Department of Zoology Govt College for Women Affiliated to University of Kerala Thiruvananthapuram Department of Artificial Intelligence and Data Science New Prince Shri Bhavani College of Engineering and Technology Chennai India

ISBN: (数字)9798331518578

ISBN: (纸本)9798331518585

Numerous advancements have been identified as potentially disruptive innovations in the surgical workplace as surgical workflow continues to improve in the digital age. The application of virtual reality (VR) and augmented reality (AR) within health care to enhance the use of data for medical reasons is unavoidable given their rapid expansion in availability, affordability, and accessibility. Using augmented reality may help paediatric orthopaedic and trauma surgeons overcome the difficult problem of comprehending the spatial linkages among the implants, anatomy, and their instruments. As needs be, the current examination proposes another AR of the surgical scene that deftly incorporates the various information sources given by a mobile C-arm and a Kinect RGB-depth sensor. This paper present a learning-based worldview to perceive the significant items or life structures in both Kinect and data of X-ray, and to produce an object unambiguous pixel-wise alpha guide that permits importance based combination of the X-ray pictures and the video inside a solitary view. We demonstrate very encouraging results in 10 simulated procedures with the goal of giving physicians a better grasp of the surgical environment and an enhanced perception.

关键词： Pediatrics Accuracy Navigation Instruments Surgery Medical services Information age Object recognition Augmented reality X-ray imaging

来源：评论

学校读者我要写书评

暂无评论

A Survey of Federated Learning Orchestration Using Kubeflow: Challenges, advances, and Future Directions

A Survey of Federated Learning Orchestration Using Kubeflow:...

引用

advances in Computer science, Electrical, Electronics, and Communication technologies (CE2CT), international conference on

作者： Prashanth Josyula Sethuraman Ulaganathan Sai Kumar Arava Salesforce San Francisco USA Adobe San Francisco USA

ISBN: (数字)9798331518578

ISBN: (纸本)9798331518585

In distributed machine learning, Federated Learning (FL) has become a game-changing paradigm that allows for cooperative model training while protecting data privacy and taking regulatory compliance into account and with a focus on edge computing integration and privacy protection techniques. This paper offers a systematic assessment of federated learning orchestration using Kubeflow, looking at architectural approaches and implementation issues in Kubernetes-native contexts and includes thorough technical evaluation and code-driven solutions, identifies a number of crucial implementation challenges for Federated Learning processes, such as edge gateway service design, dynamic device management, and adaptive privacy methods. We explore exciting research avenues like context-aware federation protocols, adaptive privacy mechanisms, and dynamic privacy preservation. We also point out important research gaps in existing implementations, particularly with regard to standardized performance metrics, sophisticated fault tolerance mechanisms, and machine learning-optimized orchestration strategies. For researchers and practitioners working on Kubeflow-based federated learning deployments, this paper offers conceptual examples for managing heterogeneous device capabilities, secure model exchange, and adaptive training configurations in Kubeflow-based FL systems highlighting important areas that need further research for enterprise-grade implementations.

关键词： Training Surveys Measurement Privacy Fault tolerance Systematics Protocols Federated learning Fault tolerant systems Logic gates

来源：评论

学校读者我要写书评

暂无评论

Enhanced Security Through Honeywords and Video CAPTCHA: An Innovative Authentication and Tracking Mechanism

Enhanced Security Through Honeywords and Video CAPTCHA: An I...

引用

advances in Electrical, computing, Communication and Sustainable technologies (ICAECT), international conference on

作者： Madhuri Gurale Komal Borate Rachana R. Sangitrao Garima Tiwari Information Technology Department D. Y. Patil College of Engineering Akurdi Pune India Artifical Intelligency and Data Science Department D. Y. Patil College of Engineering Akurdi Pune India Department of Instrumentation and Control D. Y. Patil College of Engineering Akurdi Pune India Department of Electronics & Communication D. Y. Patil College of Engineering Akurdi Pune India

ISBN: (数字)9798350356236

ISBN: (纸本)9798350356243

In recent years, activities across countries have increasingly been carried out digitally, with information being shared over networks to boost speed and efficiency. However, this digital transformation poses security threats. Cybercrime has consistently evolved, necessitating improved network security measures to combat digital scams. To maintain security, users are assigned unique identification passwords, which they are instructed to keep secret. Despite this, attackers often manage to steal passwords. To counter these threats, we propose using honeywords, which are decoy passwords created from the existing user password. If an attacker inputs a honeyword, an alert is activated for the administrator. Moreover, we implement IP and location monitoring for users and introduce a approach known as the video click-based CAPTCHA system. This scheme authenticates users by distinguishing between humans and bots, addressing issues in traditional graphic password CAPTCHA schemes. This architecture significantly enhances protection and security of data and applications over online networks.

关键词： Resistance Authentication Passwords Network security Reliability Protection Computer crime Usability Monitoring CAPTCHAs

来源：评论

学校读者我要写书评

暂无评论

Advanced Deep Learning Framework for Diagnosing Autism Spectrum Disorder Through Facial Expression Analysis

Advanced Deep Learning Framework for Diagnosing Autism Spect...

引用

advances in Electrical, computing, Communication and Sustainable technologies (ICAECT), international conference on

作者： Jagadesh Balasubramani Surendran R Department of Computer Science and Engineering Saveetha School of Engineering Saveetha Institute of Medical and Technical Sciences Chennai India

ISBN: (数字)9798350356236

ISBN: (纸本)9798350356243

Autism Spectrum Disorder is a neurodevelopmental disorder that presents with persistent deficits in social communication and social or emotional reciprocity. Timely intervention may result from an early and precise diagnosis of autism spectrum disorder (ASD). This study proposes a paradigm that uses deep learning systems to analyze facial expressions and emotions to classify children with autism spectrum disorder. The proposed framework utilizes a hybrid model combining Convolutional Neural Networks (CNNs) and Long Short-Term Memory (LSTM) networks (CNN-BiLSTM) model to learn and perform classification tasks, To enhance image quality, input data undergoes pre-processing techniques, including histogram equalization, which improves contrast, and adaptive median filtering, which reduces noise while preserving essential details. Model optimization is a self-adaptive Black-Winged kite optimization method for hyperparameter tuning, ensuring that the model's parameters are optimal for improved classification accuracy. Performance measurement results such as Accuracy, recall, precision, specificity, and confusion matrix shown from evaluating the framework in ASD datasets obtained from the Kaggle repository are implemented in Python. This approach enhances the speed and precision of Autism Spectrum Disorder diagnosis accordingly and gives a very powerful instrument for real-time clinical application.

关键词： Deep learning Image quality Autism Adaptation models Histograms Accuracy Filtering Real-time systems Tuning Long short term memory

来源：评论

学校读者我要写书评

暂无评论

Optimization of Parameters of the OWC Wave Energy Converter Device Using a Machine Learning Approach

Optimization of Parameters of the OWC Wave Energy Converter ...

引用

advances in Electrical, computing, Communication and Sustainable technologies (ICAECT), international conference on

作者： Kush Karnavat Nilansh Vadodaria Kshma Trivedi Prashant Patel School of Computer Science and Engineering Vellore Institute of Technology Chennai India Department of Mathematics School of Advanced Sciences VIT-AP University Amaravati India

ISBN: (数字)9798350356236

ISBN: (纸本)9798350356243

In this study, the performance of an L-shaped front wall OWC (Oscillating Water Column) device is investigated in the presence of irregular incident waves. To efficiently explore the complex interactions between input features and the target variable, two supervised machine learning models: (i) a decision tree model and (ii) an XGBoost model are considered. The input parameters selected for this analysis are: OWC Front wall Draft, OWC Duct Length, Chamber Length, ripple Number, and ripple amplitude of the sinusoidal seabed. The output attribute is the maximum power extracted by the OWC device. The XG Boost model is used to identify critical input regions where power extraction peaks, while the decision tree model further aids in understanding the parameter influences on power extraction. A dataset of 3125 samples was generated for training, validation, and testing. By employing accumulated local effect plots with the XG Boost model, five specific regions in the input space were identified that maximize annual average power extraction. The results indicate that optimal power extraction is achieved for a specific value of each parameter, thereby validating the influence of each on OWC device performance.

关键词： Training Computational modeling Ducts Predictive models Feature extraction data models Decision trees Wave energy conversion Optimization Testing

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500页 << < 12 13 14 15 16 17 18 19 20 21 > >>

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：