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

1,020 篇 会议
37 篇 期刊文献
10 册 图书

馆藏范围

1,067 篇 电子文献
0 种 纸本馆藏

日期分布

学科分类号

673 篇 工学
- 443 篇 计算机科学与技术...
- 238 篇 软件工程
- 192 篇 电气工程
- 191 篇 信息与通信工程
- 96 篇 控制科学与工程
- 58 篇 电子科学与技术（可...
- 52 篇 生物工程
- 49 篇 仪器科学与技术
- 39 篇 光学工程
- 39 篇 生物医学工程（可授...
- 32 篇 动力工程及工程热...
- 31 篇 机械工程
- 30 篇 材料科学与工程（可...
- 20 篇 化学工程与技术
- 20 篇 安全科学与工程
- 19 篇 交通运输工程
- 16 篇 网络空间安全
307 篇 理学
- 185 篇 物理学
- 81 篇 数学
- 54 篇 生物学
- 27 篇 系统科学
- 27 篇 统计学（可授理学、...
- 24 篇 化学
79 篇 管理学
- 56 篇 管理科学与工程(可...
- 27 篇 图书情报与档案管...
- 21 篇 工商管理
54 篇 医学
- 47 篇 临床医学
- 31 篇 基础医学(可授医学...
- 22 篇 公共卫生与预防医...
22 篇 法学
- 15 篇 社会学
11 篇 农学
7 篇 经济学
3 篇 文学
1 篇 教育学

主题

71 篇 internet of thin...
62 篇 cloud computing
44 篇 machine learning
42 篇 computational mo...
39 篇 machine learning...
38 篇 edge computing
35 篇 real-time system...
30 篇 performance eval...
28 篇 quantum computin...
27 篇 security
26 篇 heuristic algori...
25 篇 prediction algor...
25 篇 accuracy
22 篇 computer archite...
22 篇 wireless sensor ...
21 篇 sensors
20 篇 deep learning
20 篇 photonic band ga...
20 篇 photonics
20 篇 mobile computing

机构

9 篇 lovely professio...
8 篇 institute of aer...
4 篇 chitkara univers...
4 篇 the islamic univ...
4 篇 department of bi...
4 篇 acad sinica shan...
4 篇 department of co...
3 篇 department of co...
3 篇 centre of resear...
3 篇 natl res tomsk s...
3 篇 moscow
3 篇 ire nas of ukrai...
3 篇 department of el...
3 篇 national researc...
3 篇 department of ec...
3 篇 department of cs...
3 篇 department of ap...
3 篇 department of co...
3 篇 mirea – russian ...
3 篇 univ british col...

作者

5 篇 krishnamoorthy a...
5 篇 alam ms
5 篇 qian f
5 篇 zheng xuezhe
4 篇 tsao shyh-lin
4 篇 li guoliang
4 篇 feng dazeng
4 篇 pronin c.b.
4 篇 chiang chia-chin
4 篇 lexau jon
4 篇 asghari mehdi
4 篇 li gq
4 篇 ho ron
4 篇 yao jin
4 篇 luo ying
4 篇 ostroukh a.v.
4 篇 raj kannan
4 篇 lindenstruth v.
3 篇 ploskon m.
3 篇 patil dinesh

语言

1,015 篇 英文
46 篇 其他
7 篇 中文

检索条件"任意字段=Conference on Photonic Devices and Algorithms for Computing V"

共 1067 条记录，以下是141-150 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 FFT Accelerator Using Deeply-coupled RISC-v Instruction Set Extension for Arbitrary Number of Points 34

An FFT Accelerator Using Deeply-coupled RISC-V Instruction S...

引用

34th IEEE International conference on Application-Specific Systems, Architectures and Processors (ASAP)

作者： Jiang, Shijie Zou, Yi Wang, Hao Li, Wanwan South China Univ Technol Sch Microelect Guangzhou Peoples R China

ISBN: (纸本)9798350346855

Fast Fourier Transform (FFT) is one of the most widely used algorithms in digital signal processing (DSP). Many Internet of Things (IoT) devices include dedicated FFT hardware accelerators at the price of both extra hardware resources and power consumption. Limited by constrained resources for IoT applications at the edge, it is favorable as well as crucial to reduce such overhead as much as possible without sacrificing FFT performance. Meanwhile, open-source RISC-v microprocessors have become serious contenders to ARM or x86 alternatives, especially in IoT applications. Recent studies have shown that Application-specific Instruction-set Processors (ASIP) can achieve considerable acceleration performance with low overhead. This paper proposes a fine-grained RISC-v Instruction Set Architecture (ISA) extension scheme for efficient FFT operations with 12 new instructions, using four 16-bit multipliers and adders as computing units to minimize overhead. Our extended instructions are deeply coupled with the CPU pipeline, thus significantly reducing the hardware overhead of decoding and executing logic, and theoretically can accelerate the calculation of FFT with an arbitrary number of points. We demonstrate the proposed scheme on a Xilinx PYNQ-Z2 FPGA using the open-source RISC-v NutShell soft IP core, with data loading from either specially designed vector registers (v-mode) or RAM off-the-core (R-mode). The evaluation shows the proposed FFT acceleration scheme achieves a performance gain of 118 times in v-mode and 6.5 times in R-mode respectively, with only 16% power consumption required as compared to the vanilla NutShell RISC-v microprocessor.

关键词： ISA Extension FFT Accelerator ASIP RISC-v

来源：评论

学校读者我要写书评

暂无评论

Advancements in Computer vision-based Assistive Technologies for visually Impaired

Advancements in Computer Vision-based Assistive Technologies...

引用

International conference on Green Energy, computing and Intelligent Technology 2024, GEn-CITy 2024

作者： Aduri, Kishore Reddy Naganjaneyulu, P.v. Mizoram Aizawl796004 India

ISBN: (纸本)9781837242689

The advancement of assistive technologies for visually impaired individuals has seen significant strides, leveraging the power of computer vision-based object recognition and detection. This literature review explores various approaches aimed at enhancing navigation, obstacle detection, and overall mobility for the visually impaired. By utilizing methods such as real-time object detection, deep learning algorithms, and wearable devices, these technologies convert visual information into comprehensible formats through image-to-text and text-to-speech processes. Recent research efforts have focused on integrating these technologies to provide real-time auditory feedback, thereby enhancing spatial awareness and safety. For instance, mobile applications like "Smart_Eye" and wearable devices based on platforms such as Raspberry Pi employ advanced sensors and machine learning to identify and describe objects, providing crucial auditory cues to users. Systematic reviews of wearable electronic aids and technologically advanced guidance systems underline the importance of consistent detection accuracy and user adaptability. Despite the promising developments, challenges such as spatial biases, computational intensity, and user interface complexities remain. This review consolidates the findings from various studies, presenting methods used, limitations encountered, and the potential impact of computer vision-based recognition systems to assist visually impaired users. By converting image data to textual descriptions and subsequently into speech, these technologies offer comprehensive support, significantly improving the independence and quality of life for visually impaired individuals. Overall, the integration of computer vision, deep learning, and real-time feedback systems marks a transformative phase in assistive technology, providing visually impaired individuals with enhanced tools to navigate and interact with their environments effectively. © The Institution of Engin

关键词： Obstacle detectors

来源：评论

学校读者我要写书评

暂无评论

Efficient Machine Learning Methods for Real-Time Transport System Optimization and Predictive Maintenance

Efficient Machine Learning Methods for Real-Time Transport S...

引用

2024 Intelligent Technologies and Electronic devices in vehicle and Road Transport Complex, TIRvED 2024

作者： Kuftinova, N.G. Ostroukh, A.v. Maksimychev, O.I. Pronin, C.B. Ostroukh, I.A. Moscow Russia Moscow Russia

ISBN: (纸本)9798331518707

This research explores the application of machine learning techniques to enhance real-time transport system optimization and predictive maintenance. By leveraging advanced algorithms and data analysis methods, we aim to create high-performance applications capable of efficiently processing large volumes of traffic data. Our approach involves developing intelligent systems that can automatically adapt to changing conditions and predict potential issues on transport routes. We implement clustering methods, such as k-means, for effective data grouping and pattern recognition. Sophisticated data reduction techniques are employed to optimize dataset management and improve system performance. Specialized technologies like GPUs and cloud platforms are integrated to enhance computational capabilities. We focus on implementing efficient data cleaning processes to filter noisy data tracks and anomalies. The Davis-Boldin index is utilized to assess the quality of clustering in transport nodes. Application-level data transfer protocols are developed for distributed computing environments. TCP stream control algorithms are optimized for improved web service performance. Our methodology addresses challenges in real-time data processing, traffic flow prediction, and system stability. These approaches contribute to the development of more efficient and responsive transport infrastructure management solutions. The proposed methods demonstrate significant potential for improving transportation network performance and reducing operational costs through enhanced predictive maintenance capabilities. © 2024 IEEE.

关键词： Cloud platforms

来源：评论

学校读者我要写书评

暂无评论

Review on Energy Harvesting Techniques for Future Wireless Generation Networks 8

Review on Energy Harvesting Techniques for Future Wireless G...

引用

8th International conference on Advanced computing and Communication Systems, ICACCS 2022

作者： Ashok, K. Santhosh Krishna, B.v. Nagras, Aishwarya Halli, Aishwarya M Gowthami, B. Chandana, C. New Horizon College of Engineering Department of Electronics and Communication Engineering Karnataka Bangalore India

ISBN: (纸本)9781665408165

World is experiencing an explosive growth in wireless communication and wireless networks which has led to a huge increase in the energy consumption. In low-power scenarios like wireless sensors and networks, it is highly impractical or expensive to replace batteries of low-cost devices. To overcome these problems, relying on energy harvesting has proved to be the best solution and this is due to the potential for mobile devices to scan power from their surrounding that is solar, wind, vibration, thermo-electric effects, ambient radio power and so on. The use of Energy harvesting nodes in wireless communication is a promising approach for maximizing the energy efficiency. However, it requires signal processing algorithms and allied architectures to harvest the energy along with the information transfer. This paper deals with a comprehensive presentation of new research contributions on Wireless Energy Harvesting techniques, algorithms, architectures, performance metrics, and applications which are suitable for future wireless networks. Different architectures are examined in this paper that imposes optimization targets on various parameters that are very much essential to design energy efficient high speed wireless systems. © 2022 IEEE.

关键词： Energy harvesting

来源：评论

学校读者我要写书评

暂无评论

Brain Tumor Segmentation and Survival Prediction using Multimodal MRI Scans with Deep learning algorithms

Brain Tumor Segmentation and Survival Prediction using Multi...

引用

2022 International conference on Innovative computing, Intelligent Communication and Smart Electrical Systems, ICSES 2022

作者： Anjanayya, S. Gayathri, v.M. Pitchai, R. SRM Institute of Science and Technology School of Computing Tamilnadu Kattankulathur India B v Raju Institute of Technology Department of Computer Science and Engineering Narsapur India

ISBN: (数字)9781665474139

ISBN: (纸本)9781665474139

Brain tumours developed by the brain's abnormal cell growth. Medical imaging devices are classified into two types: MRI and CT are widely used to scan brain tumors. MRI images are used to scan the interior components of the brain. There are two types of brain tumours: benign and malignant. A benign brain tumour is one that can be cured, whereas a malignant brain tumour is one that cannot be cured. Gliomas and astrocytomas are two types of malignant brain tumours. A radiologist using conventional procedures to detect and diagnose a brain tumour. Errors and delays are all too common. Because neurosurgeons generate a large number of brain tumour images, imaging technicians are unable to manually categorise and segment them. It is not suitable for densely populated emerging markets. As a result, computer-aided automatic brain tumour detection and diagnosis is preferred. Learning algorithms, such as neural networks, are hampered by a lack of hyperparameter modification, several local optima, and higher computing time. Optimizing network architecture and hyperparameters is critical for avoiding these challenges. Deep learning optimization approaches are commonly employed in healthcare. This research proposed using Deep Learning Optimization algorithms to detect and diagnose Meningioma brain cancer. This intended study addresses the extraction, categorization, and diagnosis of tumor picture segments. © 2022 IEEE.

关键词： Learning algorithms

来源：评论

学校读者我要写书评

暂无评论

Least Square Support vector Machine based Intrusion Detection System in IoT 7

Least Square Support Vector Machine based Intrusion Detectio...

引用

7th International conference on Intelligent computing and Control Systems, ICICCS 2023

作者： Akhther, Parveen Maryposonia, A. Prasanth, v.S. Sathyabama Institute of Science & Technology Department of Computer Science & Engineering Tamilnadu Chennai India Sree Sakthi College of Engineering Department of Computer Science & Engineering Tamilnadu Coimbatore India

ISBN: (纸本)9798350397253

The IoT (Internet of Things) is an ever-expanding system of interconnected computing devices. It's a term for when real-world items can communicate with one another via data transfers. The availability and dependability of its activities are crucial to the day-to-day functioning of modern society. As a result, it's important to find a solution to the problem of ensuring secured data transmission across Internet of Things. An Intrusion Detection System (IDS) is a piece of software designed to keep an eye on a network or computer system and to address any suspicious activity. New threats and countermeasures must be incorporated into the network's protected evolution. The primary function of IDS is to protect valuable resources against intrusion. Intruders can be spotted using various intrusion detection techniques, strategies, and algorithms. This major purpose of this study is to propose a comprehensive system for identifying intrusion risks by applying Least Squares Support vector Machine approach. After receiving input, the following step is preprocessing, which was accomplished via Normalization, Discretization, and Feature selection in this study. These techniques are used for data preprocessing and feature selection. Training the model using LSSvM is the final stage. As compared to other models like SvM and RF, the proposed model attains an accuracy of roughly 97.7%. © 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

Deployment of Federated Learning on a Low-Cost Distributed Infrastructure 2

Deployment of Federated Learning on a Low-Cost Distributed I...

引用

2nd IEEE International conference on Federated Learning Technologies and Applications, FLTA 2024

作者： Izquierdo, víctor Hidalgo Carrión, Carmen Caminero, Blanca Instituto de Investigación Informática de Albacete Universidad de Castilla-La Mancha Spain Departamento de Sistemas Informáticos Universidad de Castilla-La Mancha Spain

ISBN: (纸本)9798350354812

Machine learning has made significant advancements, driving the creation of new technologies that extend its reach into novel domains, including the Internet of Things (IoT). These applications prove highly valuable in various fields, such as improving medical diagnoses, enabling facial recognition, and enhancing image classification. To address privacy concerns arising from the need to process sensitive data, decentralized learning environments have emerged. One such approach is Federated Learning (FL), where multiple participants collaboratively solve machine learning problems. In FL, a central coordinator synchronizes the training process while ensuring that individual device data remains isolated. This approach allows neural network training without sensitive data leaving the control of its owner. This work focuses on the implementation and deployment of an FL tool within a low-cost, heterogeneous fog computing infrastructure. This infrastructure harness limited computational resources. These constraints arise from the nature of devices commonly employed in fog computing, including routers, switches, and other IoT devices, which are not as powerful as traditional cloud servers. The goal is to analyze its performance, considering both the quality of the learning process and the efficient utilization of underlying resources. Results show that FL algorithms exhibit a statistically consistent behavior along time, while the system resource usage does not show the same behavior. In particular, memory (RAM and swap) is the resource that most impacts the FL processes, producing occasional execution failures, specially in the most constrained resource nodes. ©2024 IEEE.

关键词： Federated learning

来源：评论

学校读者我要写书评

暂无评论

Smart Climate Comfort System for Good Sleep 15

Smart Climate Comfort System for Good Sleep

引用

15th International conference on computing Communication and Networking Technologies, ICCCNT 2024

作者： Sathesh, S. Maheswaran, S. Mahendran, S. Hariharini, v.P.K. Indhu Priya, D. Hemamalini, M. Shubha Shree, T. Kongu Engineering College Department of Electronics and Communication Engineering Erode Tamil Nadu Perundurai638060 India KGiSL Institute of Technology Department of Electronics and Communication Engineering Tamil Nadu Coimbatore India

ISBN: (纸本)9798350370249

Sleep is essential to human health and has a significant role in many aspects of our lives. Improving sleep quality requires the right sleeping environment, and indoor temperature is a major factor in this. Personalized comfort is frequently not achieved by traditional means of controlling room temperature and ventilation, such as manually operating fans or depending on fixed HvAC systems. This shortfall is especially noticeable for people with physical limitations, such as the elderly or the disabled, who may find it difficult to manually regulate fans, which can cause disturbances in their sleep cycles. Wearable technology has made significant progress recently, providing encouraging answers to this problem. The ability to measure body temperature and vital indicators like heart rate in real-time makes thermal comfort and sleep quality assessments possible. These devices are lightweight and flexible. These gadgets use wireless communication protocols to send data to automated systems that change the temperature and airflow in the room in response, providing ideal sleeping conditions without the need for human interaction. In addition, the use of artificial intelligence algorithms facilitates proactive actions to mitigate disruptions in sleep. For instance, interventions like playing soft tunes to encourage relaxation and increase sleep onset can be triggered by unusual heart rate patterns that indicate anxiety or tiredness. These specific strategies reduce the negative impacts of stress and sleep deprivation, improving the quality of sleep while also improving general well-being. Moreover, the integration of electronic devices into ceiling fans presents a more dynamic method of temperature control. Through smart regulation of fan speed and airflow in response to current temperature fluctuations, these systems maximize thermal comfort levels while reducing energy usage. This reduces the financial burden associated with excessive energy consumption and lowers the en

关键词： Automated system Communication protocols Flexible IoT Lightweight Microcontroller Physical disabilities Sleep Smart regulation of fan speed Temperature control

来源：评论

学校读者我要写书评

暂无评论

Comprehensive Fault Handling and Resource Management Strategies for FOG Infrastructure

Comprehensive Fault Handling and Resource Management Strateg...

引用

2024 IEEE International conference on Recent Advances in Science and Engineering Technology, ICRASET 2024

作者： Kalra, Simran Gayathri, C. Aggarwal, Prateek Jamuna, K.v. Deshmukh, Gopal B. Gajendran, P. Chitkara University Centre of Research Impact and Outcome Punjab Rajpura140417 India Prince Shri Venkateshwara Padmavathy Engineering College Department of S&h Chennai127 India Chitkara University Chitkara Centre for Research and Development Himachal Pradesh 174103 India School of Sciences Forensic Science Karnataka Bangalore India Vishwakarma Institute of Technology Pune India Karpagam College of Engineering Department of Electrical and Electronics Engineering Coimbatore641032 India

ISBN: (纸本)9798350388602

An exciting new development, fog computing makes use of existing cloud infrastructure to fulfil service demands from edge devices connected to IoT. Due to highly dynamic and diverse nature of infrastructure situated at the periphery of the web, breakdowns are common occurrences, making fault tolerance an essential need. Prior iterations of scheduling and fault-tolerant algorithms paid little attention to requests with a tight deadline. Unfavourable consequences, such as longer wait times for certain requests, are more likely as a result. This work presents a FTSM for distributing service gadget queries in fog cloud Connectivity settings that are well equipped to handle them. Reducing service overhead and latency while increasing cloud stability and capacity is the primary goal of the suggested solution. Sorting request-making devices into one of three groups based on the service type is important to the approach. You may categorise these classes as core, time-sensitive, and time-tolerant. Every time an application is timed-sensitive, it is immediately mapped to any number of edge gadgets using an executive directory of equipment that has already been generated. Any cloud-based device, whether it's at the network's periphery or its heart, can handle time-sensitive demands. Applications for services in the cloud's foundation are handled there. Achieving a maximum availability of 95%, the suggested technique FTSM consistently outperforms the other methods, CKM and RM, across numerous circumstances. While CKM and RM maintain lower availability percentages, FTSM proves to be the most dependable strategy when considering availability. This ongoing benefit demonstrates how much better the suggested approach is than the alternatives. © 2024 IEEE.

关键词： Fog computing

来源：评论

学校读者我要写书评

暂无评论

Approaches for Advanced Spectrum Sensing in Cognitive Radio Networks 7

Approaches for Advanced Spectrum Sensing in Cognitive Radio ...

引用

7th International conference on Intelligent computing and Control Systems, ICICCS 2023

作者： Chaturvedi, Abhay Prasad, K.D.v. Jha, Sudhanshu Kumar Srinivas, ved Anil Kumar, N. Dankan Gowda, v. GLA University Department of Electronics and Communication Engineering Uttar Pradesh Mathura India Off Bangalore Highway Kothur Mandal Village Mahabubnagar Telangana Hyderabad India University of Allahabad Department of Electronics and Communication Uttar Pradesh Prayagraj India Public Policy Thiagarajar School of Management Tamilnadu Madurai India Department of Electronics and Instrumentation Engneering A. Andhra Pradesh Rangampet India BMS Institute of Technology and Management Department of Electronics and Communication Engineering Karnataka Bangalore India

ISBN: (纸本)9798350397253

Intelligent learning and adaptation allow cognitive radios (CRs) to maximise available spectrum while maintaining stable connections. Cognitive radio technology may detect unused channels of radio frequency space via a process called "spectrum sensing,"and then get rapid and easy access to such channels. An important aspect of CR technology is spectrum sensing, which allows CRs to detect gaps in the spectrum. It's the practise of keeping tabs on a certain radio spectrum band on a regular and changing basis to see if there are any interference issues that might prevent its utilisation. Noise power and signal fading in a wireless channel have a significant impact on the efficiency of spectrum sensing techniques in noisy situations. Another difficulty for sensing algorithms involving a single secondary user is the dilemma of a hidden main user in shadowed areas. algorithms for cooperative spectrum sensing must take into account a number of aspects, including sensing time, speed, cooperation overheads, and decision fusion methods. In order to provide efficient and adaptable IoT networking, many wireless technologies have emerged in recent years. One of the primary technologies that provides opportunistic connection to a wide variety of interconnected IoT devices is cognitive radio (CR), which makes software-defined radio possible. An unmanaged and unregulated invasion of privacy through low-powered wireless sensors into the Internet of Things (IoT). The output of such networks is dependent on the main consumer's observed spectrum pattern because of the networks' opportunistic nature. © 2023 IEEE.

关键词： Cognitive radio

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107页 << < 11 12 13 14 15 16 17 18 19 20 > >>

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：