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

1,204,919 篇 会议
7,547 篇 期刊文献
678 册 图书
12 篇 学位论文
5 件 标准
3 篇 科技报告

馆藏范围

1,213,160 篇 电子文献
7 种 纸本馆藏

日期分布

学科分类号

751,734 篇 工学
- 398,712 篇 计算机科学与技术...
- 303,367 篇 软件工程
- 199,461 篇 电气工程
- 161,166 篇 控制科学与工程
- 154,389 篇 信息与通信工程
- 116,934 篇 电子科学与技术（可...
- 95,610 篇 机械工程
- 71,930 篇 动力工程及工程热...
- 59,359 篇 仪器科学与技术
- 54,010 篇 生物医学工程（可授...
- 51,846 篇 生物工程
- 47,656 篇 化学工程与技术
- 38,474 篇 材料科学与工程（可...
- 36,659 篇 交通运输工程
- 36,322 篇 光学工程
- 34,219 篇 安全科学与工程
- 31,241 篇 土木工程
- 28,226 篇 力学（可授工学、理...
328,016 篇 理学
- 159,044 篇 数学
- 104,447 篇 物理学
- 54,818 篇 生物学
- 45,237 篇 系统科学
- 43,711 篇 统计学（可授理学、...
- 43,687 篇 化学
169,881 篇 管理学
- 128,691 篇 管理科学与工程(可...
- 61,857 篇 工商管理
- 49,573 篇 图书情报与档案管...
42,140 篇 医学
- 33,573 篇 临床医学
- 30,907 篇 基础医学(可授医学...
29,811 篇 经济学
- 29,151 篇 应用经济学
23,688 篇 法学
16,588 篇 教育学
15,772 篇 农学
6,222 篇 文学
4,027 篇 军事学
1,992 篇 艺术学
99 篇 哲学
94 篇 历史学

主题

24,835 篇 control systems
19,276 篇 mathematical mod...
18,074 篇 feature extracti...
18,050 篇 computational mo...
16,552 篇 accuracy
15,681 篇 monitoring
15,490 篇 training
14,752 篇 costs
13,424 篇 real-time system...
12,789 篇 neural networks
12,702 篇 optimization
12,548 篇 testing
12,330 篇 biological syste...
12,326 篇 predictive model...
12,118 篇 analytical model...
11,761 篇 hardware
11,584 篇 switches
11,381 篇 humans
11,193 篇 internet of thin...
11,130 篇 robustness

机构

3,046 篇 chitkara univers...
1,431 篇 ieee
1,272 篇 school of electr...
1,247 篇 university of ch...
934 篇 school of electr...
901 篇 china electric p...
860 篇 school of automa...
783 篇 school of comput...
767 篇 school of electr...
684 篇 department of el...
653 篇 school of comput...
611 篇 college of elect...
602 篇 school of electr...
592 篇 department of el...
578 篇 university of sc...
577 篇 harbin institute...
547 篇 school of electr...
541 篇 school of inform...
520 篇 lovely professio...
510 篇 school of electr...

作者

1,211 篇 wang wei
883 篇 liu yang
856 篇 li li
819 篇 zhang wei
783 篇 wang lei
729 篇 wei wang
700 篇 zhang lei
693 篇 li wei
667 篇 li yang
598 篇 yang yang
586 篇 liu wei
558 篇 wei li
542 篇 lei wang
541 篇 singh bhim
521 篇 yang liu
509 篇 china
493 篇 wei zhang
467 篇 wang jian
448 篇 wang jing
443 篇 wei liu

语言

1,174,348 篇 英文
23,032 篇 其他
15,529 篇 中文
336 篇 俄文
109 篇 西班牙文
54 篇 土耳其文
50 篇 法文
20 篇 葡萄牙文
13 篇 乌克兰文
6 篇 德文
5 篇 阿拉伯文
5 篇 日文
2 篇 捷克文
1 篇 丹麦文
1 篇 朝鲜文
1 篇 荷兰文

检索条件"任意字段=IEEE International Conference on System Engineering and Technology"

共 1213164 条记录，以下是4801-4810 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：

Assessment of cross-flow indirect evaporative heat and mass exchanger performance using numerical methods

Assessment of cross-flow indirect evaporative heat and mass ...

引用

international conference on Energy, Power, Environment, Control and Computing (ICEPECC 2025)

作者： Sabir Rasheed Muzaffar Ali Hassan Ali Muhammad Usman Institute of Refrigeration and Cryogenics Shanghai Jiao Tong University Shanghai 200240 People's Republic of China Department of Thermal Science and Energy Engineering University of Science and Technology of China Hefei 230026 People's Republic of China School of Chemical Engineering University of Birmingham Dubai UAE Energy Engineering Department University of Engineering and Technology Taxila 47050 Pakistan

ISBN: (数字)9781837243150

Indirect evaporative air-cooling system is an environmentally sustainable substitute for air-cooling interior spaces especially in hot and dry climates. In this work, a system is numerically simulated which is a heat and mass exchanger comprised of polymeric materials such as polypropylene and non-woven fabric cloth. The numerical simulation is carried out by using COMSOL Multiphysics to pretend the heat and mass exchanger in order to identify the ideal thermal comfort under actual climate conditions. It is noted that the system may higher values of energy efficiency ratio and coefficient of performance, as high as 22.3 and 6.55, respectively. The predicted results demonstrated in the dew-point effectiveness, wet-bulb effectiveness, and cooling capacity where the maximum determined values are 0.6, 0.73, and 471 W, respectively. These predicted findings were validated with experimental results which showed a maximum deviation of around 4.78 %. Based on the numerical simulation study and validation, the indirect evaporative air-cooling system be capable of the designed for different operational conditions and climatic zones as per the requirements of end users.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Research on the Collaborative Mechanism of P4Runtime and SAI in White Box Switches Based on the SONiC system

Research on the Collaborative Mechanism of P4Runtime and SAI...

引用

Power Electronics, Computer Applications (ICPECA), ieee international conference on

作者： Zhuyu Pan Hongchao Wang Chen Yan Zishi Zhang School of Electronic and Information Engineering Beijing Jiaotong University Beijing China

ISBN: (数字)9798331533694

ISBN: (纸本)9798331533700

With the advancement of Software-Defined Networking (SDN) technology, network programmability and flexibility have been significantly enhanced. However, effectively integrating traditional network systems with emerging programmable platforms remains a critical research challenge. This paper proposes a fusion architecture based on the P4Runtime protocol to achieve deep integration of SONiC white box switches and the P4 platform. By introducing SDN programmability, we design and implement a hybrid model that enables traditional network architectures to achieve advanced functionalities with the assistance of external SDN controllers. This paper provides a detailed discussion of the architecture design and implementation process, including P4 code development, compilation, target configuration file generation, and interaction mechanisms between the control plane and the data plane. Furthermore, we validate the applicability and performance of the architecture in various scenarios, offering robust support for future research and applications in programmable networks.

关键词： Protocols Process control Computer architecture Switches Network architecture Programming Control systems Power electronics Software defined networking Glass box

来源：评论

学校读者我要写书评

暂无评论

Design Of An IoT Based Model For Milk Quality Measurement Using Fringing Field Interdigital Capacitive Sensing and Dielectric Property Analysis

Design Of An IoT Based Model For Milk Quality Measurement Us...

引用

Interdisciplinary Approaches in technology and Management for Social Innovation (IATMSI), ieee conference on

作者： Divya Palakaluri Praveen Maurya School of Electronics and Communication Engineering VIT - AP University Amaravati Amaravati India

ISBN: (数字)9798331521691

ISBN: (纸本)9798331521707

The proposed paper highlights the need for advanced milk quality measurement systems to enhance food safety and ensure quality assurance. Conventional methods are inefficient and incapable of monitoring real-time quality changes, thereby posing potential risks. This work focuses on a milk quality measurement system incorporating a fringing field interdigital capacitive sensor, consisting of three key models: Capacitive Sensing with signal conditioning, Dielectric Property Analysis, and Predictive Quality Assessment. The IoT-based Capacitive Sensing Model detects minute changes in milk quality by measuring capacitance variations caused by dielectric properties. It includes temperature compensation for accurate results. The Dielectric Property Analysis Model correlates dielectric constants with milk quality parameters such as fat, protein, and contamination levels. The Predictive Quality Assessment Model uses machine learning algorithms to detect trends and provide alerts for deviations. Together, these models enable real-time monitoring, enhancing accuracy, reliability, and predictive capabilities, significantly improving food safety and quality assurance practices.

关键词： Temperature measurement Analytical models Dairy products Quality assurance Predictive models Real-time systems Dielectric measurement Sensors Pollution measurement Quality assessment

来源：评论

学校读者我要写书评

暂无评论

Advanced Pest Identification: An Efficient Deep Learning Approach Using VGG Networks

Advanced Pest Identification: An Efficient Deep Learning App...

引用

Interdisciplinary Approaches in technology and Management for Social Innovation (IATMSI), ieee conference on

作者： K. Lakshminadh Divvela Chandu Venkateswara Guptha Jujjuri Sai Kandula Rajesh Sireesha Moturi Yaragani Neelima Dodda Venkata Reddy Department of CSE Narasaraopeta Engineering College Narasaraopeta India

ISBN: (数字)9798331521691

ISBN: (纸本)9798331521707

Accurate pest identification is crucial for both effective pest management and crop protection. Pests must be found early in order to minimise damage and guarantee crop security. Conventional techniques typically entail visual examination and professional involvement, which might be time-consuming and susceptible to errors by humans. On the other hand, deep learning-powered high-performance systems can now more accurately identify pests thanks to developments in computer vision. In this work, we employed the Keras-based deep learning models VGG16 and VGG19 to construct a passive pest detection system. We greatly improved the efficacy of these models in identifying pest species by using strategies such data augmentation, model optimization, and modification of validated models. The VGG16 model produced an amazing accuracy rate of 99.8% and VGG19 model produced an accuracy of 96.8 % in our testing.

关键词： Deep learning Visualization Accuracy Computational modeling Transfer learning Crops Data augmentation Data models Agriculture Convolutional neural networks

来源：评论

学校读者我要写书评

暂无评论

Music Recommendation system Based on Lyrics Similarity and Cosine Similarity

Music Recommendation System Based on Lyrics Similarity and C...

引用

international conference on Electrical, Computer and Communication engineering (ECCE)

作者： Israt Jahan Muna Tasnim Zarin Semontee Nursadul Mamun Department of Electronics and Telecommunication Engineering Chittagong University of Engineering and Technology Bangladesh

ISBN: (数字)9798350357509

ISBN: (纸本)9798350357516

This study describes a music recommendation system that uses TF-IDF vectorization and cosine similarity to propose songs based on lyrical similarities. By converting music lyrics into numerical vectors and assessing song similarities, the system generates textual-relevant recommendations. The model includes an option to filter by artist, which improves tailored recommendations. We used data preprocessing, stemming, and TF-IDF vectorization, along with cosine similarity, to provide music recommendations. The findings show that text-based similarity is beneficial for producing music recommendations. This method could benefit streaming services by pushing personalization beyond user preferences and collaborative filtering.

关键词： Electric potential Collaborative filtering Semantics Diversity reception Data preprocessing Vectors User experience Data models Numerical models Recommender systems

来源：评论

学校读者我要写书评

暂无评论

Improving Pea Variety Sorting with a Hybrid Approach of CNN-NB Method

Improving Pea Variety Sorting with a Hybrid Approach of CNN-...

引用

Interdisciplinary Approaches in technology and Management for Social Innovation (IATMSI), ieee conference on

作者： Rishabh Sharma Manish Nagpal Centre for Research Impact & Outcome Chitkara University Institute of Engineering and Technology Chitkara University Rajpura Punjab India Chitkara Centre for Research and Development Chitkara University Himachal Pradesh India

ISBN: (数字)9798331521691

ISBN: (纸本)9798331521707

This study introduces a new way to improve the reliability of pea variety identification by using two methods together: Convolutional Neural Networks (CNN) and Naive Bayes (NB). Types of peas have small differences in appearance, making it hard to sort them using old ways. In this study, the task was to classify different types of peas into three groups: Azad P-1, Pusa Pragati, and Arkel. The suggested plan combines the good things of CNN for getting features from picture data and NB for chance sorting. The CNN part finds complex patterns and space details in pea pictures, while the NB sorter improves sorting using chance modeling. The combination of these two ways tries to use their different good points, which makes a strong and true pea-kind identification system. Testing on a big group of data shows that the mixed model - CNN and NB together is good. The proposed model gets an overall accuracy of 96.2% in the case of the testing dataset. The study helps in how to look at farm pictures. It's useful for scientists and workers who work with peas, pea growing and improving them.

关键词： Smart agriculture Technological innovation Accuracy Probabilistic logic Bayes methods Convolutional neural networks Reliability Sorting Testing Farming

来源：评论

学校读者我要写书评

暂无评论

PRESS: Defending Privacy in Retrieval-Augmented Generation via Embedding Space Shifting

PRESS: Defending Privacy in Retrieval-Augmented Generation v...

引用

international conference on Acoustics, Speech, and Signal Processing (ICASSP)

作者： Jiaming He Cheng Liu Guanyu Hou Wenbo Jiang Jiachen Li School of Computer Science and Engineering University of Electronic Science and Technology of China China College of Computer Science and Cyber Security (Oxford Brookes College) Chengdu University of Technology China School of Data Science The Chinese University of Hong Kong Shenzhen China School of Computer Science and Artificial Intelligence Wuhan University of Technology China

ISBN: (数字)9798350368741

ISBN: (纸本)9798350368758

Retrieval-augmented generation (RAG) expands the capabilities of large language models (LLMs) in various applications by integrating relevant information retrieved from external data sources. However, the RAG systems are exposed to substantial privacy risks during the information retrieval process, leading to potential data leakage of private information. In this work, we present a Privacy-preserving Retrieval-augmented generation via Embedding Space Shifting (PRESS), systematically exploring how to protect privacy in RAG systems. Specifically, we first conduct proximal policy optimization (PPO) based training on pre-trained language models to generate target training samples. Then we employ a purposive shift fine-tuning on the text embedding model with the generated samples for guiding the RAG system to map potential privacy leaking queries to safe target in embedding space. Extensive experimental results on representative models and datasets demonstrate that our protection method achieves high defense performance with high efficiency while keeping the normal functionality of the RAG system.

关键词： Training Privacy Data privacy Presses Soft sensors Retrieval augmented generation Signal processing Speech processing Protection Optimization

来源：评论

学校读者我要写书评

暂无评论

Power system Equipment Detection in Thermal Images by Deep Learning Approach

Power System Equipment Detection in Thermal Images by Deep L...

引用

Industrial Electronics: Developments & Applications (ICIDeA), ieee international conference on-

作者： Biswojyoti Khandual Rupali Balabantaraya Ashwin Kumar Sahoo Prabodh Kumar Sahoo Sibashis Panda Anushka Parashar Department of Electrical Engineering C.V.Raman Global University Bhubaneswar India Department of Mechatronics Parul Institute of Technology Parul University Gujarat India

ISBN: (数字)9798331533205

ISBN: (纸本)9798331533212

The non-contact accuracy of infrared thermography has made it indispensable for electrical equipment inspection. In order to recognize electrical equipment in thermal pictures, this study presents a revolutionary neural network-based learning model. Based on the neural network algorithm, the proposed work suggests a real-time object detection model YOLO-V8, that can predict the coordinate points, orientation angle, and type of class of certain equipment. To improve accuracy, particularly for small items, the model incorporates an orientation consistency prior. In the proposed work, an extensive thermal imaging dataset of a distribution transformer; covered a range of settings and equipment kinds. According to experimental results, the suggested model achieves a mean average precision of 93.7%, demonstrating its robustness to noise and ability to function at 20 frames per second resulting in accurate detection of different segments of a distribution transformer in a thermal image.

关键词： Deep learning Image segmentation Accuracy Neural networks Object detection Inspection Transformers Real-time systems Thermal noise Robustness

来源：评论

学校读者我要写书评

暂无评论

Autonomous Integrated Sensing and Processing for Bioradar: Advancing Non-Invasive Biomedical Monitoring and Signal Analysis

Autonomous Integrated Sensing and Processing for Bioradar: A...

引用

ieee MTT-S international Microwave Bio conference ((IMBIOC)

作者： Shafkat Hossain Omer Kurkutlu Oluwaseun Adekola Sourav Kumar Pramanik Shekh M. M. Islam Arman Roohi Dieff Vital Department of Electrical and Computer Engineering University of Illinois Chicago USA Department of Electrical and Electronic Engineering University of Dhaka Bangladesh

ISBN: (数字)9798331510473

ISBN: (纸本)9798331510480

This paper presents a novel automated system that leverages a Raspberry Pi to operate a 24 GHz single-channel continuous wave (CW) radar for through-the-wall concurrent vital sign monitoring of two subjects. The system autonomously performs independent component analysis using the joint approximation diagonalization of eigenmatrices (ICA-JADE) to separate both individuals' breathing rates (BR). It applies the maximal overlap discrete wavelet transform (MODWT) after ICA-JADE to extract heart rates (HR). By integrating the radar system and ICA-JADE into an embedded platform, the system operates without requiring manual intervention. The automation framework enables real-time processing, enhancing the system's practical deployment in real-world applications. The results demonstrate high accuracy in isolating BR and HR using ICA-JADE, as benchmarked against conventional chest belts and ECG measurements. This fully automated approach shows significant potential for applications such as search and rescue operations, security surveillance, and remote healthcare monitoring through barriers.

关键词： Heart rate Surveillance Transforms Belts Real-time systems Doppler radar Sensors Security Biomedical monitoring Signal analysis

来源：评论

学校读者我要写书评

暂无评论

Brain Cancer Detection and Classification using Transfer Learning

Brain Cancer Detection and Classification using Transfer Lea...

引用

Interdisciplinary Approaches in technology and Management for Social Innovation (IATMSI), ieee conference on

作者： Varad Gadaokar Piyush More Madhuri Wakode Geetanjali Kale Dept. of Computer Engineering Pune Institute of Computer Technology Pune India Dept. of Electronics and Telecommunication Engineering Pune Institute of Computer Technology Pune India

ISBN: (数字)9798331521691

ISBN: (纸本)9798331521707

Brain tumors are abnormal cells that grow inside the brain. If not diagnosed or treated early, such incidents can be fatal. Types of brain tumors include meningioma, glioma, and pituitary tumors. Magnetic resonance imaging (MRI) is an essential resource in diagnosis due to the clear expression of brain tissues, enabling professionals to analyze abnormal developments in the brain. The detection and classification of brain tumors using MRIs can be automated using machine learning techniques that can help to identify and diagnose brain tumors in their early stages, and subsequent treatment may result in a lower death rate. Transfer Learning allows the transfer of knowledge learned from large-scale datasets to other smaller datasets, thus avoiding wide-ranging training requirements with high accuracy and making the system converge much faster. This substantially minimizes computational resources and time in the training process. Transfer Learning also enables the effective MRI image abstraction of complex features, improved accuracy in tumor detection and classification, minimizes overfitting, especially with small amounts of medical data. In this work, we have used Transfer Learning with two pre-trained deep models, VGG16 and ResNet-50 on 3064 images available in the dataset to classify brain tumors. Fine-tuning for VGG16 and ResNet-50, we achieved validation accuracies of 98.85% and 97.72%, respectively. The results show that transfer learning can be used for the classification of brain tumors to enhance efficiency and precision for early detection and treatment.

关键词： Training Accuracy Magnetic resonance imaging Computational modeling Transfer learning Brain tumors Feature extraction Brain modeling Data models Overfitting

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 << < 477 478 479 480 481 482 483 484 485 486 > >>

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：