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

7,963 篇 会议
81 篇 期刊文献
76 册 图书

馆藏范围

8,120 篇 电子文献
0 种 纸本馆藏

日期分布

学科分类号

5,060 篇 工学
- 3,923 篇 计算机科学与技术...
- 2,399 篇 信息与通信工程
- 1,795 篇 软件工程
- 1,360 篇 电气工程
- 645 篇 控制科学与工程
- 418 篇 动力工程及工程热...
- 374 篇 电子科学与技术（可...
- 313 篇 生物工程
- 222 篇 生物医学工程（可授...
- 218 篇 机械工程
- 206 篇 仪器科学与技术
- 173 篇 测绘科学与技术
- 166 篇 光学工程
- 125 篇 化学工程与技术
- 123 篇 材料科学与工程（可...
- 94 篇 建筑学
- 87 篇 土木工程
- 86 篇 网络空间安全
- 85 篇 石油与天然气工程
1,380 篇 理学
- 637 篇 数学
- 413 篇 物理学
- 359 篇 生物学
- 213 篇 统计学（可授理学、...
- 138 篇 化学
- 121 篇 系统科学
685 篇 管理学
- 393 篇 管理科学与工程(可...
- 307 篇 图书情报与档案管...
- 148 篇 工商管理
239 篇 医学
- 210 篇 临床医学
- 132 篇 基础医学(可授医学...
84 篇 法学
81 篇 农学
57 篇 经济学
23 篇 军事学
22 篇 教育学
15 篇 文学
1 篇 哲学

主题

1,596 篇 wireless sensor ...
501 篇 neural networks
329 篇 wireless communi...
300 篇 convolutional ne...
256 篇 deep learning
237 篇 sensor nodes
222 篇 routing
217 篇 feature extracti...
185 篇 monitoring
181 篇 image processing
177 篇 signal processin...
172 篇 wireless sensor ...
168 篇 energy consumpti...
166 篇 sensor networks
161 篇 sensors
158 篇 accuracy
149 篇 sensor systems
147 篇 real-time system...
141 篇 protocols
138 篇 routing protocol...

机构

15 篇 chitkara univers...
10 篇 univ chinese aca...
10 篇 school of inform...
10 篇 beijing universi...
10 篇 gla university m...
9 篇 south china univ...
9 篇 university of ch...
9 篇 beijing institut...
8 篇 department of co...
8 篇 department of el...
7 篇 school of inform...
7 篇 chinese academy ...
6 篇 univ wisconsin d...
6 篇 karnataka bangal...
6 篇 computer network...
6 篇 shanghai jiao to...
6 篇 school of comput...
6 篇 school of electr...
6 篇 amrita vishwa vi...
6 篇 shihezi universi...

作者

12 篇 wang wei
11 篇 chen chen
9 篇 liu yang
9 篇 li qiang
8 篇 zhang tao
8 篇 wang lei
7 篇 wei liu
7 篇 liu wei
7 篇 cao jiannong
6 篇 badache nadjib
6 篇 jiao licheng
6 篇 wei wang
5 篇 zhou jie
5 篇 li xin
5 篇 hui wang
5 篇 pitchaimanickam ...
5 篇 soman k. p.
5 篇 liu ying
5 篇 zhang sheng
5 篇 qiang li

语言

7,954 篇 英文
156 篇 其他
18 篇 中文
1 篇 俄文

检索条件"任意字段=5th International Conference on Informational Processing in Sensor Networks"

共 8120 条记录，以下是201-210 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：

Smart Energy Management Leveraging Twin Adaptive Pulse Coupled networks for Dynamic Energy Optimization in IoT-based Electrical WSN

Smart Energy Management Leveraging Twin Adaptive Pulse Coupl...

引用

Trends in Material Science and Inventive Materials (ICTMIM), international conference on

作者： Ravi Kumar M B. Md. Irfan Sugunadevi C Umang Soni Madhu B K Ramya Maranan Department of Electronics and Communication Engineering Cambridge Institute of Technology Bengaluru Karnataka Department of Information Technology Nalsar University of Law Hyderabad Telengana Department of Information Science and Engineering CMR Institute of Technology Bengaluru Karnataka Electronics & Communication Engineering Faculty of Engineering and Technology Parul Institute of Engineering and Technology Parul University Gujarat Department of Computer Science and Engineering Vidya Vikas Institute of Engineering and Technology Mysore Karnataka Department of Research and Innovation Saveetha School of Engineering SIMATS Chennai Tamil Nadu

ISBN: (数字)9798331501488

ISBN: (纸本)9798331501495

Internet of things (IoT)-driven Wireless sensor networks (WSNs) undergo fast growth hence requiring sophisticated energy optimization methods to keep the networks operational longer with reliable data handling. Traditional energy management practices lead to early node failure combined with inefficient network routes and non-even energy distribution which blocks network development and operational performance expansion. the three main factors that cause WSNs to be energy inefficient are improper node positioning along with excessive routing overhead and uneven distribution of power consumption across sensor nodes. the current network management approaches do not provide adequate dynamic energy distribution which results in premature network failure. this research establishes "Smart Energy Management leveraging Twin Adaptive Pulse Coupled networks for Dynamic Energy Optimization in IoT-Based WSN (MG-TwinAPC-ReP)" to address these challenges. the proposed framework MG-TwinAPC-ReP features four layers which (1) strategic node deployment coverage, (2) Cluster-Based Routing Protocol Using Modified Greylag-Goose Optimization, and (3) Energy management through adaptive load balancing using Twin Adaptive Pulse Coupled Network's dual synchronization model and (4) uses Reformed Poplar Optimization to optimize networking parameters. Experimental results indicate remarkable performance capabilities which lead to a 99.82% increase in network lifetime and 99.74% energy conservation together with 99.91% reliable data delivery and 99.65% reduced latency compared to traditional IoT-WSN systems. the proposed scalable self-adapting energy-efficient WSN model provides an optimal solution for smart cities together with healthcare and agriculture and industrial IoT applications which drives sustainable IoT-driven WSN deployment into the future.

关键词： Wireless sensor networks Adaptive systems Smart cities Medical services Routing Load management Mathematical models Reliability Optimization Industrial Internet of things

来源：评论

学校读者我要写书评

暂无评论

Optimized Deep Learning Model for Early Parkinson’s Disease Detection Using Speech Spectrograms

Optimized Deep Learning Model for Early Parkinson’s Disease...

引用

Innovative Research in Applied Science, Engineering and Technology (IRASET),conference on

作者： Oumaima Majdoubi Asma Ouabd Abdelilah Jilbab Achraf Benba Ahmed Hammouch E2SN Research Team ENSAM-R Mohammed V University in Rabat Rabat Morocco

ISBN: (数字)9798331532970

ISBN: (纸本)9798331532987

Parkinson’s disease (PD) is a progressive neurodegenerative disorder, and early detection is crucial for timely intervention and management. this study proposes an innovative approach for non-invasive PD detection using deep learning techniques applied to speech analysis. Speech recordings of Parkinson’s patients and healthy individuals were converted into spectrograms using the Short-Time Fourier Transform (STFT), which were then processed using Principal Component Analysis (PCA) for dimensionality reduction. We employed several convolutional neural network (CNN) architectures, including CNN, MobileNet, ResNet50, and Inception, to classify the data. A 5-fold cross-validation was applied. Among the models, CNN demonstrated superior performance, achieving 99.19% accuracy, 100% precision, and 99.21% F1 score without cross-validation, which improved to perfect scores across all metrics when cross-validation was applied. the results indicate that deep learning, coupled with speech signal processing and cross-validation, provides a powerful tool for the early, non-invasive detection of Parkinson’s disease. this approach holds significant potential for improving diagnosis accuracy and enabling timely medical intervention.

关键词： Deep learning Accuracy Speech analysis Convolutional neural networks Artificial intelligence Speech processing Spectrogram Diseases Principal component analysis Residual neural networks

来源：评论

学校读者我要写书评

暂无评论

Integration of Piezoelectric and Light-Dependent Resistor sensors for Efficient Generation and Utilization of Electricity for Pathways

Integration of Piezoelectric and Light-Dependent Resistor Se...

引用

Trends in Material Science and Inventive Materials (ICTMIM), international conference on

作者： Saranya G Kumaran K Daneshwaran M Shyam Venkatraman Jey Pradeep A Anish Anandhan A L School of Computer Science and Engineering Vellore Institute of Technology Chennai India

ISBN: (数字)9798331501488

ISBN: (纸本)9798331501495

the ever-increasing demand for energy in our modern world necessitates exploration of innovative and sustainable solutions. However, the research in the integration of piezoelectric materials has highlighted limitations with respect to scalability. this research investigates the potential of piezoelectric materials for harvesting energy from everyday human movement. We look into cost-effective system utilizing piezoelectric sensors embedded under flooring to capture the energy generated by footsteps. this harvested energy can be stored in and boosted for powering devices. this research explores the utilization of piezoelectric energy harvesting technology to create electricity-generating pathways, offering a sustainable solution for powering pathway lights in urban environments. Piezoelectric sensors strategically placed along the pathway surface capture kinetic energy from pedestrian movement, converting it into electrical energy. this energy is stored in rechargeable batteries and undergoes voltage conversion to power pathway lights effectively. A light-dependent resistor (LDR) sensor ensures lights only activate when necessary, optimizing energy usage. An Arduino Uno microcontroller orchestrates light operation based on ambient light conditions. the methodology focuses on efficient energy utilization and provides a practical solution for sustainable pathway lighting. Several prototypes and studies are discussed, highlighting the potential and limitations of piezoelectric energy harvesting technology. the results demonstrate consistent power generation, high energy conversion efficiency, and cost-effectiveness, underscoring the feasibility and effectiveness of the proposed approach.

关键词： Resistors Mechanical sensors Wireless sensor networks Pedestrians Costs Electricity Piezoelectric materials Lighting sensor systems Energy harvesting

来源：评论

学校读者我要写书评

暂无评论

An Optimized Technique for Feature Extraction and EEG Signal processing using MATLAB

An Optimized Technique for Feature Extraction and EEG Signal...

引用

Trends in Material Science and Inventive Materials (ICTMIM), international conference on

作者： Sangeetha C N G R Yashwanth Aniket Mirji Abhishek J Aashish thomas Oommen Lalith Narayan Department of Electrical and Electronics Engineering New Horizon College Of Engineering Bengaluru India

ISBN: (数字)9798331501488

ISBN: (纸本)9798331501495

Brain-Computer Interfaces (BCI), cognitive research, and medical diagnosis all make extensive use of electroencephalography (EEG) to analyze brain activity. However, issues with EEG signal processing include limited classification accuracy, ineffective feature extraction, and noise interference. With an emphasis on enhanced feature extraction and classification, this study uses MATLAB to optimize EEG signal processing. Enhanced preprocessing methods, Independent Component Analysis (ICA) for artifact removal, and Butterworth and Chebyshev filters for noise reduction are all part of the optimization process. Time-domain, frequency-domain, and time-frequency representations like Wavelet Transform and Power Spectral Density (PSD) are used to enhance feature extraction. Support Vector Machines (SVM) and Artificial Neural networks (ANN) are used for classification, which increases accuracy. Cross-validation and statistical analysis are used to verify the precision and accuracy of the results. A comparative analysis reveals advancements over current practices. In addition to discussing improvements in preprocessing clarity, the paper presents methods to improve cross-correlation (CC) and signal-to-noise ratio (SNR). Future research will integrate deep learning with real-time EEG streaming.

关键词： Support vector machines Time-frequency analysis Accuracy Signal processing Feature extraction Electroencephalography Real-time systems MATLAB Signal to noise ratio Principal component analysis

来源：评论

学校读者我要写书评

暂无评论

Research and Practice on a Water Environment Pollution Monitoring System Based on the 51 single chip microcomputer and wireless optical sensing technology 5

Research and Practice on a Water Environment Pollution Monit...

引用

5th international conference on Telecommunications, Optics, and Computer Science, TOCS 2024

作者： Yang, Fang School of Physics and Electronic Science Zunyi Normal University Guizhou Zunyi 563006 China

ISBN: (纸本)9781510691667

With the rapid development of technology, people's quality of life continues to improve. However, water environment pollution has emerged as a significant environmental challenge that urgently needs to be addressed. To this end, this paper investigates and designs a water environment pollution monitoring system based on the 51 microcontroller. the system adopts wireless optical sensing technology, integrates pH sensor and optical turbidity sensor, and realizes real-time collection, transmission and display of water quality data. the system visually displays water quality data through the LCD1602 display. the PH sensor is used to monitor the pH change of the water body in real time, and the optical turbidity sensor is used to detect the concentration of suspended matter in the water. the data collected by the two will be transmitted to 51 microcontroller for processing in real time. Using an analog-to-digital (AD) conversion module, the system converts analog signals into digital signals and displays the real-time water quality status on the LCD1602, enabling users to comprehensively understand the water environment. When the water quality parameter exceeds the set threshold, the system will issue an alarm in time and prompt the user to take appropriate environmental protection measures through sound and light. the water environment pollution monitoring system designed in this paper has high reliability and practicability. through the in-depth analysis of the system, the working principle and key technical points are further discussed, which provides a new idea and method for water quality monitoring. © 2025 SPIE.

关键词： microcontroller Microcontroller optical turbidity sensor STC89C52 water environment pollution Wireless optical sensor technology

来源：评论

学校读者我要写书评

暂无评论

Performance Analysis of Text Classification Algorithms for Dhivehi Language Documents

Performance Analysis of Text Classification Algorithms for D...

引用

Advanced Research in Computing (ICARC), international conference on

作者： Fathimath Rashma Mohamed Prasanna S. Haddela Mohamed Jamaaludhin School Maldives Faculty of Computing Sri Lanka Institute of Information Technology Sri Lanka

ISBN: (数字)9798331530983

ISBN: (纸本)9798331530990

this study examines the effectiveness of various machine learning algorithms in classifying text written in “Dhivehi,” the official language of the Maldives. As a low-resource language with limited research in text analytics, “Dhivehi” poses unique challenges due to its distinctive linguistic properties. To address these challenges, this research evaluates the performance of algorithms, including Support Vector Machines, Naive Bayes, Decision Trees, Neural networks, XGBoost, and Random Forest, leveraging a newly curated “Dhivehi” language dataset. the evaluation highlights that K-Neighbors achieved the highest performance, with an accuracy of 64.7% and F1 scores (macro: 0.640, weighted: 0.642), demonstrating a strong balance between precision and recall. Support Vector Machines (accuracy: 63.9%) and XGBoost (accuracy: 62.8%) also showed competitive results, with SVM slightly outperforming XGBoost in F1 metrics. Decision Tree exhibited the lowest performance across all metrics. the findings provide critical insights into improving text classification for low-resource languages and contribute to developing natural language processing tools adapted explicitly for “Dhivehi.” Furthermore, the dataset is publicly available on Mendeley data under the name “Dhivehi Categories data set” to foster future research and innovation in this domain.

关键词： Support vector machines Measurement Accuracy Computational modeling Text categorization Neural networks Nearest neighbor methods Bayes methods Decision trees Random forests

来源：评论

学校读者我要写书评

暂无评论

UWB-based 3D Localization using Least Squares Trilateration with Combination of Median Filter and Kalman Filter 5

UWB-based 3D Localization using Least Squares Trilateration ...

引用

5th international conference on Emerging Electrical Energy, Electronics and Computing Technologies, ICE4CT 2024

作者： Shukri, Muhamad Naqib Mohd Zakaria, Ammar Yeon, Ahmad Shakaff Ali Zakaria, Syed Muhammad Mamduh Syed Kamarudin, Latifah Munirah Visvanathan, Retnam Baharom, Muhammad Azri Ahmad Khalid, Hafizal Amin, Ahmad Helmi Mohd Centre of Excellence for Advance Sensor Technology Universiti Malaysia Perlis Malaysia Faculty of Electrical Engineering & Technology Universiti Malaysia Perlis Malaysia Faculty of Electronic Engineering & Technology Universiti Malaysia Perlis Malaysia IDERIA Sdn. Bhd. Perlis Malaysia Project Excellence PETRONAS Malaysia

this study investigates the implementation of Ultra-Wideband (UWB) based 3D localization using Least Squares Trilateration algorithm with using median filter and Kalman filter. Two types of experiments were conducted indoors. First, TOF measurements between a statically placed UWB tag and its surrounding anchors were collected. Secondly, TOF measurements were collected by moving the UWB tag within the environment. TOF measurements from both experiments were then pre-processed using median filter to remove outliers and Kalman filter for data smoothing before being processed by Least Squares Trilateration algorithm to obtain the UWB tag estimated position. From the first experiment, the results showed a 99.69% improvement in terms of maximum error reduction, an 84.48% improvement in average distance error reduction, and a 99.25% improvement in standard deviation error reduction across the x, y, and z axes. From the second experiment, results showed improved trajectory smoothness after filtering. However, from both experiments, the challenge of obtaining accurate estimates of the z-axis position is addressed in the results and discussion section. Future works will focus on advanced signal processing techniques and improve the calibration of sensor devices. © 2025 Institute of Physics Publishing. All rights reserved.

关键词： Least squares approximations

来源：评论

学校读者我要写书评

暂无评论

Optimized Clustering Approach for WSN Using WCLUST Algorithm

Optimized Clustering Approach for WSN Using WCLUST Algorithm

引用

Innovative Research in Applied Science, Engineering and Technology (IRASET),conference on

作者： Soukaina Bouarourou Chaimae Kanzouai Abderrahim Zannou El Habib Nfaoui Abdelhak Boulaalam Faculty of Sciences Mohamed V University Rabat Morocco LSATE Laboratory Faculty of Sciences Dhar El Mahraz Sidi Mohamed Ben Abdellah University Fez Morocco ERCI2A Faculty of Sciences and Techniques Al Hoceima Morocco Abdelmalek Essaâdi Morocco Computer Science Department L3IA Laboratory Faculty of Sciences Dhar El Mahraz Sidi Mohamed Ben Abdellah University Fez Morocco LSATE Laboratory National School of Applied Sciences Sidi Mohamed Ben Abdellah University Fez Morocco

ISBN: (数字)9798331532970

ISBN: (纸本)9798331532987

the proliferation of Internet of things applications has resulted in easy device integration in Wireless sensor networks, enabling real-time data collection and coordination. However, seamless integration is still plagued by issues such as energy constraints and high energy consumption due to inefficient data communication. Many studies explored clustering methods to address such issues. Here, we introduce the Whale-Based Algorithm for cluster establishment and a Selection Factor for Cluster Head selection—key steps that minimize paths and save energy. With the use of the proposed method, our approach improves clustering quality with the establishment of dense and energy-saving clusters. the Selection Factor provides dynamic selection of the most suitable Cluster Heads according to residual energy, neighboring nodes, and distance to the sink. the proposed method attains the clustering quality accuracy of 97% and drastically decreases the run time with respect to the Ant-Based Clustering algorithm.

关键词： Wireless sensor networks Energy consumption Accuracy Heuristic algorithms Clustering methods Clustering algorithms Data collection Real-time systems Internet of things Data communication

来源：评论

学校读者我要写书评

暂无评论

Utilization of Li-Fi Technology for Black Box in Ground Vehicles

Utilization of Li-Fi Technology for Black Box in Ground Vehi...

引用

Trends in Material Science and Inventive Materials (ICTMIM), international conference on

作者： Sabari L. Uma Maheswari Magesh T Sukhi Y Jayasree V Jeeva G Oviya B Department of EEE R. M. K. Engineering College Tiruvallur India

ISBN: (数字)9798331501488

ISBN: (纸本)9798331501495

Inspired by the aircraft flight data recorders, the study aims to invent a universal Black Box prototype for automobiles-for safe vehicle usage and accident analysis, plug on minimum circuitry and inexpensive model to provide complete security over the vehicle, better medical assistance for the casualty, and fast insurance claim process. It uses Li-Fi technology for enabling real-time, fast data delivery in vehicle and infrastructure communication without lag. Additionally, the Black Box also enables Car-to-Car Communication for the detection of probable collision threats through sudden movements of proximity vehicles. It also analyzes in real-time through simulation, which works towards collision risk reduction, and real-time safety improvement involves quality vehicle diagnosis and providing timely hazard information. With predictive analytics and rapid data sharing, this model gears up for intelligent transport networks that benefit emergency action and insurance processing while accident prevention is possible by proactive detection of hazards and creation of situational awareness. It is a very important breakthrough on road safety technology.

关键词： Electronic equipment Flight recording Vehicular ad hoc networks Prototypes Insurance Light fidelity Real-time systems Hazards Monitoring Accidents

来源：评论

学校读者我要写书评

暂无评论

High-Speed Moving Target Communication Technology in Shallow Sea Based on Random-OTFS

High-Speed Moving Target Communication Technology in Shallow...

引用

sensors and Information Technology (ICSI), international conference on

作者： Danying Zhang Cheng He Fei Sun Oceanography College Jiangsu University of Science and Technology Zhenjiang China

ISBN: (数字)9798331542887

ISBN: (纸本)9798331542894

Orthogonal Time Frequency Space (OTFS) modulation is a new type of signal modulation method proposed in recent years. It aims to address the problem of communication quality degradation caused by Doppler frequency shift in the typical high-mobility and multipath transmission scenarios of next-generation wireless communication networks. For underwater acoustic communication in high-speed mobile environments, the Doppler effect is very significant and complex, including frequency spreading and frequency offset. Meanwhile, the bandwidth of underwater acoustic communication is usually narrow, and the OTFS modulation uses broadband signals. When there is a Doppler effect in the channel, it will inevitably have additional impacts. To solve the above problems, based on the traditional OTFS modulation technology, this paper proposes a Random-OTFS modulation technology that uses complex Gaussian random sequences as carrier signals and directly modulates information in the Doppler time-domain stretching region. this technology can resist relatively strong Doppler interference, reduce signal distortion, and better adapt to the rapid changes of underwater acoustic channels, with stronger adaptability to channel characteristics.

关键词： Wireless communication Time-frequency analysis Underwater communication Frequency modulation Resists sensor phenomena and characterization Doppler effect Underwater acoustics Time-domain analysis Random sequences

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 << < 17 18 19 20 21 22 23 24 25 26 > >>

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：