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

21,411 篇 会议
16,488 篇 期刊文献
410 册 图书

馆藏范围

38,309 篇 电子文献
0 种 纸本馆藏

日期分布

学科分类号

22,095 篇 工学
- 12,850 篇 计算机科学与技术...
- 10,535 篇 软件工程
- 4,645 篇 信息与通信工程
- 3,426 篇 生物医学工程（可授...
- 3,360 篇 控制科学与工程
- 3,243 篇 电气工程
- 3,147 篇 生物工程
- 2,957 篇 电子科学与技术（可...
- 2,179 篇 光学工程
- 2,020 篇 化学工程与技术
- 1,708 篇 机械工程
- 1,532 篇 仪器科学与技术
- 1,405 篇 材料科学与工程（可...
- 1,401 篇 动力工程及工程热...
- 817 篇 安全科学与工程
- 787 篇 网络空间安全
14,610 篇 理学
- 5,887 篇 物理学
- 5,789 篇 数学
- 3,911 篇 生物学
- 2,183 篇 化学
- 1,966 篇 统计学（可授理学、...
- 1,262 篇 系统科学
5,427 篇 管理学
- 3,423 篇 管理科学与工程(可...
- 2,096 篇 图书情报与档案管...
- 1,707 篇 工商管理
3,991 篇 医学
- 3,210 篇 临床医学
- 2,633 篇 基础医学(可授医学...
- 1,697 篇 药学(可授医学、理...
- 1,253 篇 公共卫生与预防医...
894 篇 法学
- 764 篇 社会学
740 篇 经济学
708 篇 农学
445 篇 教育学
101 篇 文学
67 篇 军事学
48 篇 艺术学
5 篇 哲学
4 篇 历史学

主题

1,129 篇 accuracy
1,083 篇 deep learning
768 篇 machine learning
670 篇 feature extracti...
613 篇 internet of thin...
579 篇 training
566 篇 computational mo...
530 篇 real-time system...
507 篇 support vector m...
493 篇 computer science
486 篇 artificial intel...
436 篇 predictive model...
396 篇 optimization
373 篇 convolutional ne...
320 篇 data models
296 篇 image segmentati...
289 篇 reliability
269 篇 covid-19
249 篇 scalability
240 篇 security

机构

1,093 篇 cavendish labora...
1,027 篇 department of ph...
976 篇 physikalisches i...
969 篇 oliver lodge lab...
639 篇 infn laboratori ...
623 篇 infn sezione di ...
603 篇 infn sezione di ...
601 篇 fakultät physik ...
593 篇 infn sezione di ...
584 篇 university of ch...
562 篇 school of physic...
537 篇 horia hulubei na...
536 篇 department of ph...
534 篇 school of physic...
522 篇 iccub universita...
521 篇 imperial college...
512 篇 h.h. wills physi...
512 篇 nikhef national ...
510 篇 stfc rutherford ...
505 篇 school of physic...

作者

270 篇 barter w.
259 篇 a. gomes
251 篇 beiter a.
246 篇 c. alexa
244 篇 j. m. izen
241 篇 bellee v.
240 篇 g. bella
239 篇 j. strandberg
238 篇 c. amelung
236 篇 d. calvet
234 篇 bowcock t.j.v.
234 篇 blake t.
233 篇 g. spigo
232 篇 brundu d.
231 篇 s. chen
229 篇 f. siegert
221 篇 betancourt c.
220 篇 amato s.
219 篇 borsato m.
216 篇 r. ströhmer

语言

32,957 篇 英文
4,932 篇 其他
300 篇 中文
84 篇 日文
53 篇 德文
51 篇 法文
6 篇 俄文
6 篇 斯洛文尼亚文
5 篇 荷兰文
3 篇 西班牙文
2 篇 波兰文
1 篇 阿拉伯文
1 篇 意大利文
1 篇 朝鲜文
1 篇 葡萄牙文

检索条件"机构=Computer Science And Medical Engineering Faculty of Engineering and Technology"

共 38309 条记录，以下是4591-4600 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：

Integrating IoT and Machine Learning for Real-Time Patient Health Monitoring with Sensor Networks 4

Integrating IoT and Machine Learning for Real-Time Patient H...

引用

4th International Conference on Smart Electronics and Communication, ICOSEC 2023

作者： Vimal, S.P. Vadivel, M. Baskar, V. Vijaya Sivakumar, V.G. Srinivasan, C. Sri Ramakrishna Engineering College Department of Electronics and Communication Engineering Tamil Nadu Coimbatore India Vidya Jyothi Institute of Technology Department of Electronics and Communication Engineering Telangana Hyderabad India School of Electrical and Electronics Engineering Sathyabama Institute of Science and Technology Tamil Nadu Chennai India Saveetha School of Engineering Saveetha Institute of Medical and Technical Sciences Saveetha University Department of Computer Science and Engineering Tamil Nadu Chennai India

ISBN: (纸本)9798350300888

An innovative approach for continuous health monitoring in medical applications is presented in this research. The proposed system is composed of Raspberry Pi, cloud storage, machine learning, and IoT sensor. The IoT sensor monitors patients' vitals in real time and quickly identifies any anomalies. The patient wearing the sensors transmit the real-time data with Raspberry Pi processors. The Raspberry Pi collects the real time data from sensors such temperature, blood pressure, heart rate, and pulse oximeter. Then the IoT transmits the data collected to a cloud server. K-Nearest Neighbors (KNN) is a data processing and analysis method used in the cloud server. The KNN algorithm categorizes and analyzes the data collected, discovers the trend and anomalies present in the patient's vital signs. The proposed system has a simple user interface that can be accessed via a web or mobile application, allowing doctors and nurses to remotely look at the patient's data and generate real-time alerts in case of severe health situations. While cloud technology ensures scalability, data storage, and advanced analytics, the integration of Raspberry Pi devices makes it possible to process data locally and reduce latency. © 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

Advancing Underwater Communication with NBO-MFO Hybrid Routing in UWSNs

Advancing Underwater Communication with NBO-MFO Hybrid Routi...

引用

International Conference on Communications and Signal Processing

作者： S.A. Kalaiselvan M.Lenin Kumar M. Amanullah T.R. Mani Chigurupati Department of Computer Science and Engineering Rajalakshmi Engineering College Chennai India Department of Electronics and Communications Engineering Vignan Institute of Technology and Science Telangana India Department of Computer Science and Engineering Saveetha School of Engineering Saveetha Institute of Medical and Technical Sciences Chennai India Department of Computer Science and Engineering TKR College of Engineering and Technology Telangana India

ISBN: (数字)9798350353068

ISBN: (纸本)9798350353075

In this research provides a solution for optimizing routing path selection in Underwater Wireless Sensor Networks (UWSNs). The algorithm combines Namib Beetle Optimization (NBO) and Moth-Flame Optimization (MFO), integrating them into the ILEACH methodology for efficient routing path selection. The algorithm operates in an iterative manner, commencing with NBO’s feature selection process, evaluating fitness through average classification error and feature selection ratio. Simultaneously, MFO mimics moth behavior, updating positions via a logarithmic spiral function based on flame locations. The mutual learning phase facilitates information exchange between NBO and MFO, enhancing their collective intelligence and refining the routing path selection process. ILEACH’s contribution lies in its fitness aggregation and selection methods. It amalgamates various criteria, including energy levels, distances, and node conditions, into a comprehensive fitness metric. Subsequently, ILEACH selectively identifies optimal routing paths aligned with energy-efficient criteria and node statuses, ensuring efficient data transmission and energy conservation within UWSNs. This integrated approach fosters a comprehensive strategy for routing path selection in UWSNs, ensuring sustainability and efficiency in data transmission within challenging underwater environments.

关键词： Wireless sensor networks Machine learning algorithms Scalability Signal processing algorithms Routing Feature extraction Energy efficiency

来源：评论

学校读者我要写书评

暂无评论

Multi-objective de novo Drug Design using Bidirectional Recurrent Neural Networks and Nondominated Sorting 2

Multi-objective de novo Drug Design using Bidirectional Recu...

引用

2nd International Conference on Data science and Information System, ICDSIS 2024

作者： Dineshkumar, R. Sunil Kumar, V. Reddy, R. Archana Shnain, Ammar Hameed Sachinkumar Saveetha University Saveetha School Of Engineering Saveetha Institute Of Medical And Technical Sciences Department Of Ece Chennai India Nitte Meenakshi Institute Of Technology Department Of Aiml Bengaluru India Sr University School Of Computer Science And Engineering Telangana Warangal India The Islamic University College Of Technical Engineering Department Of Computers Techniques Engineering Najaf Iraq Navodaya Institute Of Technology Department Of Cse Raichur India

ISBN: (纸本)9798350381665

Drug Design (DD) is a significant field for pharmaceutical businesses study. Deep Learning (DL) approaches are evolving as an auspicious solution to employ de novo drug design, such as to develop drug-like molecules personalized to particular requirements. In DD, the design as well as production of safe and effective compounds is a long-term, complex, as well as difficult process. Hence, this research proposes the Bidirectional Recurrent Neural Network (BiRNN) for the design of multi-objective de novo drug. Initially, the CheMBL and KIBA datasets are utilized to estimate the effectiveness of the proposed method. Then, the data are proprocessed by utilizing Fragment similarity calculations to design various ligands sets and particular target collections. The proposed BiRNN attains the accuracy of 0.9742, and 0.0632 on CheMBL dataset, as well as Mean Square Error (MSE) of 0.213 and 0.024 on KIBA dataset respectively. These obtained results are better and effective when compared to the existing methods like Transformer-Decoder Generator, A2C Reinforcement Learning (RL) and Recurrent Neural Network (RNN). © 2024 IEEE.

关键词： Mean square error

来源：评论

学校读者我要写书评

暂无评论

Cloud Computing-Enhanced and Raspberry Pi-powered Solution for Remote Ear, Nose, and Throat Consultations with AI-Driven Diagnostics 5

Cloud Computing-Enhanced and Raspberry Pi-powered Solution f...

引用

5th IEEE International Conference for Emerging technology, INCET 2024

作者： Giriprasad, S. Karpagam, T. Nalini, V. Mishra, Nilamadhab Mohankumar, N. Malathi, N. Department of Electronics and Communication Engineering SRM Institute of Science and Technology Kattankulathur Tamil Nadu Chennai India Department of Artificial Intelligence and Data Science R.M.K College of Engineering and Technology Tamil Nadu Chennai India Department of Mathematics Vel Tech Multi Tech Dr Rangarajan Dr Sakunthala Engineering College Tamil Nadu Chennai India School of Computing Science and Engineering VIT Bhopal University Madhya Pradesh India Department of Electronics and Communication Engineering B.V. Raju Institute of Technology Telangana India Department of Computer Science and Engineering Saveetha School of Engineering Saveetha Institute of Medical and Technical Sciences Saveetha University Tamil Nadu Chennai India

ISBN: (纸本)9798350361155

The cutting-edge telemedicine program presents a game-changing alternative for patients seeking ENT (ear, nose, and throat) consultations from a distant location. Utilizing the capabilities of Raspberry Pi devices, powerful artificial intelligence, and cloud computing, the system allows otoscopic tests to be performed without interruption while securely transmitting data to the cloud. On a web-based platform, interactive patient-professional consultations are made possible via real-time communication, which is made possible by WebRTC. Cloud services are very important because of their ability to provide scalable storage as well as AI-driven diagnostics for accurate evaluations. The system complies with the requirements for healthcare compliance, emphasizes security and privacy, and features encryption from beginning to finish. This integrated approach promises scalability, reliability, and advanced diagnostic capabilities, and it reshapes the landscape of remote ENT care with accessible and technologically advanced healthcare solutions. With a user-friendly interface for patients and a cloud-hosted application for healthcare professionals, this integrated approach provides patients with advanced healthcare solutions. © 2024 IEEE.

关键词： Artificial intelligence

来源：评论

学校读者我要写书评

暂无评论

Sharding:A Scalability Solutions for Blockchain Networks 3

Sharding:A Scalability Solutions for Blockchain Networks

引用

3rd IEEE International Conference on Blockchain and Distributed Systems Security, ICBDS 2024

作者： Kale, Dattatray Raghunath Jadhav, Amolkumar N. Kruishna Prasad, K. Salunkhe, Somanath Janardan Hirve, Sumit Goswami, Chandrashekhar Mit Art Design and Technology University Mit School of Computing Department of Computer Science & Engg Pune India Annasaheb Dange College of Engineering and Technology Department of Computer Science & Engg Ashta India Shrinivas University Department of Computer Science & Engg Mangalore India D Y Patil Agriculture and Technical University Department of Computer Science & Engg Talsande India Sir Padampat Singhania University Faculty of Computing and Informatics Rajasthan Udaipur India

ISBN: (纸本)9798350354348

Blockchain technology's decentralized and immutable data storage has changed a number of sectors. But typical blockchain networks scalability issues prevent them from being widely used for large-scale applications. By dividing the blockchain network into smaller, more controllable sections known as shards, sharding has become a viable remedy for scalability issues. This paper offers a thorough introduction to sharding as a blockchain network scalability solution. We explore the basic ideas of sharding as well as its advantages, drawbacks, and several sharding strategies. We also analyze experimental results and real-world implementations to assess how well sharding contributes to increased blockchain scalability. Lastly, we talk about possible developments in sharding approaches and future research paths to further improve the scalability of blockchain networks. © 2024 IEEE.

关键词： Distributed ledger

来源：评论

学校读者我要写书评

暂无评论

Optimizing Early Detection of Lung Disease Through Data-Driven Approaches

Optimizing Early Detection of Lung Disease Through Data-Driv...

引用

International Conference on Electronics, Materials engineering and Nano-technology (IEMENTech)

作者： S. Balapriya Anandaraj B Sathish Kumar P. J Surendran R K S Balamurugan Department of Computer Science and Engineering Sathyabama Institute of Science and Technology Chennai Tamil Nadu India Department of Computer Science and Engineering Madnapalle Institute of Technology & Science Madanapalle Andhra Pradesh India Department of Computer Science and Engineering Panimalar Engineering College Chennai India Department of Computer Science and Engineering Saveetha School of Engineering Saveetha Institute of Medical and Technical Sciences Chennai India Department of Electronics and Communication Engineering Karpaga Vinayaga College of Engineering and Technology Chengalpattu Tamil Nadu India

ISBN: (数字)9798331520762

ISBN: (纸本)9798331520779

Lung illness is any condition that impairs the lungs' capacity to function normally; diabetes, in particular, can have a variety of effects on the lungs and increases the risk of respiratory infections such as pneumonia and TB in those who have it. According to recent studies, 384 million individuals have chronic obstructive pulmonary disease (COPD), and 3 million of them pass away each year as a result of delayed diagnosis. Early detection of any disease can lessen its severity, which will lower the death rate and number of lung disease sufferers. Used deep learning methods for lung detection diagnostics, such as improved fish bee (IFB) and chaotic bird swam optimization (CBSO), despite the prediction rate's high false rate and lack of accuracy. Introduced a technique using machine learning methods, such as the Principal Component Analysis (PCA) algorithm for extraction of features, the Decision Tree approach for sample categorization, and the Support Vector Machine (SVM) for very accurate early illness diagnosis. The results of the suggested approach for early lung tumor identification with a low incorrect rate showed an accuracy of 98.07.

关键词： Support vector machines Accuracy Machine learning algorithms Pulmonary diseases Lungs medical services Prediction algorithms Diabetes Decision trees Principal component analysis

来源：评论

学校读者我要写书评

暂无评论

SECURING COMPLEX IOT PLATFORMS WITH TOKEN BASED ACCESS CONTROL AND AUTHENTICATED KEY ESTABLISHMENT

SECURING COMPLEX IOT PLATFORMS WITH TOKEN BASED ACCESS CONTR...

引用

2024 International Conference on Sustainable Computing and Integrated Communication in Changing Landscape of AI, ICSCAI 2024

作者： William, P. Kotiyal, Arnav Al-Jawahry, Hassan M. Shrivastava, Anurag Yadav, Kanchan Aswini, Kilaru Department of Information Technology Sanjivani College of Engineering SPPU Kopargaon Pune India Department of Computer Science & Engineering Graphic Era Deemed to be University Dehradun India Department of Computers Techniques Engineering College of Technical Engineering The Islamic University Najaf Iraq Saveetha School of Engineering Saveetha Institute of Medical and Technical Sciences Tamilnadu Chennai India Department of Electrical Engineering GLA University Mathura India Institute of Aeronautical Engineering Dundigal Hyderabad India

ISBN: (纸本)9798350355338

The functionality of a security architecture for advanced Internet of Things (IoT) devices is discussed in this article. Validated key configuration and access control that is based on tokens are absolutely necessary in order to guarantee the safety of this idea. In order to keep up with the rapid proliferation of the IoT ecosystem, it is imperative that the availability, integrity, and security of data be maintained at all times. Token-based access control is an opportunity to provide a workable solution to one of the most common concerns raised about the safety of the internet of things (IoT). This article's objective is to improve the safety of the Internet of Things (IoT) by analyzing the guiding principles, implementation tactics, and benefits offered by a variety of security measures that may be included into complex IoT systems. In this article, we explain how token-based access control and verified key generation may be merged into a single, all-encompassing method to strengthen the safety of platforms used for the internet of things (IoT). Token-based access control provides flexibility and adaptability when it comes to regulating rights in dynamic settings that are linked to the Internet of Things. In order to shield oneself from potential dangers such as man-in-the-middle attacks, one must take the necessary precautions, such as generating authorized keys to keep the privacy of one's communication routes secret. This research uses performance measurements, comparisons of code sizes, and statistical analysis to evaluate and examine the efficacy and efficiency of a variety of different security methods. The findings demonstrate how readily the recommended methodology may be adapted to meet the requirements of a wide variety of Internet of Things (IoT) systems. This paper is a helpful resource for enterprises and developers who work in dynamic situations and are interested in strengthening the security of Internet of Things deployments. © 2024 IEEE.

关键词： Access control

来源：评论

学校读者我要写书评

暂无评论

Enhancing Railway Safety with an IoT Based System for Real Time Fault Detection and Crack Monitoring

Enhancing Railway Safety with an IoT Based System for Real T...

引用

Information technology and Digital Applications (ICITDA), IEEE International Conference on

作者： Rajermani Thinakaran Somasekar Jalari Vikram Neerugatti Madhusudana Rao Nalluri Santhaiah Chukka Ravindra Raman Cholla Faculty of Data Science and Information Technology INTI International University Malaysia Department of Computer Science and Engineering Faculty of Engineering and technology Jain (Deemed-to-be University) Bangalore India Department of Computer Science and Engineering ICFAI Foundation for Higher Education Hyderabad Telangana India Department of Computer Science and Engineering S V College of Engineering Tirupati Andhra Pradesh India

ISBN: (数字)9798331510732

ISBN: (纸本)9798331510749

Safety of railway is the major problem worldwide. It has problems like cracks or any fault in the railway tracks. These problems can cause severe accidents if it is not detected regularly and early. In traditional fault finding and crack detecting method, the manual method is involved which is very slow and consist of many errors. By considering all these challenges and issues in track detection method, we have implemented an advanced IoT based railway crack and fault-finding system. It uses advanced sensors, microcontroller, GPS and GSM module which can detect and report faults of the railway track. The system uses real time mechanism. The system is implemented and tested on a prototype railway track to detect crack or any fault. The internet of things technology added modern and accurate fault-finding feature in the system. The IoT plays an important role in implementing advance technologies, as it uses sensors and advance microcontroller. The accuracy rate of fault and crack detection is around 97%, which is for 2 mm crack. Along with this GPS module accurately track fault location. GSM module successfully send the alert message quickly after detecting the fault in the track. Hence the response time is very less and accurate. This system is implemented in order to ensure safety for the railway track and prevent the accidents. Hence the system is useful for improving overall transport safety.

关键词： GSM Accuracy Microcontrollers Fault location Rail transportation Real-time systems Sensors Safety Internet of Things Global Positioning System

来源：评论

学校读者我要写书评

暂无评论

Assessing the Effectiveness of Machine Learning Algorithms in Vehicle Insurance Fraud Prediction: A Comparative Approach

Assessing the Effectiveness of Machine Learning Algorithms i...

引用

Electronics and Renewable Systems (ICEARS), International Conference on

作者： Aditya P. Satone Subodh Daronde Department of Computer Science and Medical Engineering Faculty of Engineering and Technology Datta Meghe Institute of Higher Education and Research (DU) Wardha Maharashtra India Department of Biomedical Engineering Faculty of Engineering and Technology Datta Meghe Institute of Higher Education and Research (DU) Wardha Maharashtra India

ISBN: (数字)9798331509675

ISBN: (纸本)9798331509682

Due to the wealth of information accessible on many insurance issues, including travel and auto insurance, individuals are becoming more and more impacted by these kinds of insurance in today's society. But this tendency also makes room for dishonest practices. Insurance fraud is harmful and unlawful, regardless of who commits it—the vendor or the customer. Fraud can come from both the customer and the vendor. The consumer may commit fraud by filing exaggerated claims or using out-of-date policies, while the vendor may market insurance from phoney firms or neglect to submit premiums. This paper presents a comparative analysis of various classification algorithms, including Support Vector Machine (SVM), Random Forest (RF), Decision Tree (DT), Linear Regression (LR), and Polynomial Regression, for detecting insurance fraud. The performance of these algorithms is evaluated using key metrics such as Precision, Recall, and F1-Score. The analysis reveals that the bestperforming model is the Random Forest, with a Mean Squared Error (MSE) of 6.50, outperforming the other techniques.

关键词： Support vector machines Analytical models Machine learning algorithms Insurance Predictive models Data science Data models Fraud Classification algorithms Random forests

来源：评论

学校读者我要写书评

暂无评论

Performing Aerobatic Maneuver with Imitation Learning 23rd

Performing Aerobatic Maneuver with Imitation Learning

引用

23rd International Conference on Computational science, ICCS 2023

作者： Freitas, Henrique Camacho, Rui Silva, Daniel Castro Department of Informatics Engineering Faculty of Engineering University of Porto Rua Dr. Roberto Frias s/n. Porto4200-465 Portugal LIAAD/INESC TEC - Artificial Intelligence and Decision Support Laboratory/Institute for Systems and Computer Engineering Technology and Science Porto Portugal LIACC - Artificial Intelligence and Computer Science Laboratory Porto Portugal

ISBN: (纸本)9783031359941

The work reported in this article addresses the challenge of building models for non-trivial aerobatic aircraft maneuvers in an automated fashion. It is built using a Behavioural Cloning approach where human pilots provide a set of example maneuvers used by a Machine Learning algorithm to induce a control model for each maneuver. The best examples for each maneuver were selected using a set of objective evaluation metrics. Using those example sets, robust models were induced that could replicate (and in some cases outperform) the human pilots that provided the examples (the clean-up effect). Complete complex maneuvers were performed using a meta-controller capable of sequencing the basic ones learned by imitation. This endeavor was rewarded by the results that show several Machine Learning models capable of performing highly complex aircraft maneuvers. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Cloning

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 << < 456 457 458 459 460 461 462 463 464 465 > >>

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：