检索结果-内蒙古大学图书馆

您好，读者！请登录

内蒙古大学图书馆

首页
概况
党建
资源
服务
科研支持
- 论文收录引用证明
- 科技查新
知识产权
档案馆
帮助

咨询与建议

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

您的常用邮箱：*

您的手机号码：*

问题描述：

当前已输入0个字，您还可以输入200个字

全部搜索
期刊论文
图书
学位论文
标准
纸本馆藏
外文资源发现
数据库导航
超星发现

高级检索

时间限定

出版年份：

文献类型

图书期刊文献学位论文多媒体

馆藏选择

电子馆藏纸本馆藏

核心期刊

全部期刊 SCI 收录期刊 SSCI 收录期刊 EI 收录期刊 CSCD 收录期刊 CSSCI 收录期刊

语言

中文英文

文献类型

期刊文献图书学位论文标准纸本馆藏

帮助

文字说明：

T=题名（书名、题名），A=作者（责任者），K=主题词，P=出版物名称，PU=出版社名称，O=机构（作者单位、学位授予单位、专利申请人），L=中图分类号，C=学科分类号，U=全部字段，Y=年（出版发行年、学位年度、标准发布年）

检索规则说明：

AND代表“并且”；OR代表“或者”；NOT代表“不包含”；(注意必须大写,运算符两边需空一格)

检索范例：

范例一：(K=图书馆学 OR K=情报学) AND A=范并思 AND Y=1982-2016
范例二：P=计算机应用与软件 AND (U=C++ OR U=Basic) NOT K=Visual AND Y=2011-2016

分类表

所选分类

>> <<

限定检索结果

文献类型

6,382 篇 会议
161 册 图书
46 篇 期刊文献

馆藏范围

6,589 篇 电子文献
0 种 纸本馆藏

日期分布

学科分类号

4,753 篇 工学
- 4,180 篇 计算机科学与技术...
- 3,371 篇 软件工程
- 1,160 篇 信息与通信工程
- 762 篇 生物工程
- 562 篇 生物医学工程（可授...
- 498 篇 控制科学与工程
- 422 篇 电气工程
- 326 篇 动力工程及工程热...
- 268 篇 机械工程
- 254 篇 光学工程
- 251 篇 电子科学与技术（可...
- 241 篇 安全科学与工程
- 220 篇 化学工程与技术
- 214 篇 环境科学与工程（可...
2,079 篇 理学
- 944 篇 数学
- 830 篇 生物学
- 413 篇 物理学
- 400 篇 统计学（可授理学、...
- 278 篇 系统科学
- 223 篇 化学
1,416 篇 管理学
- 786 篇 管理科学与工程(可...
- 775 篇 图书情报与档案管...
- 514 篇 工商管理
615 篇 医学
- 580 篇 临床医学
- 555 篇 基础医学(可授医学...
- 331 篇 药学(可授医学、理...
- 302 篇 公共卫生与预防医...
359 篇 法学
- 266 篇 社会学
209 篇 农学
- 200 篇 作物学
198 篇 经济学
- 197 篇 应用经济学
132 篇 教育学
23 篇 军事学
13 篇 文学

主题

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

机构

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

作者

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

语言

6,396 篇 英文
187 篇 其他
17 篇 中文

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

共 6589 条记录，以下是101-110 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：

A Hybrid Approach Using Cryptography and K-Least Significant Bit Steganography Algorithm in Cloud computing

A Hybrid Approach Using Cryptography and K-Least Significant...

引用

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

作者： Anshika Goyal Bhumika Gupta Dept. of Computer Science & Engineering VMSB Uttarakhand Technical University Dehradun India Dept. of Computer Science & Engineering G.B. Pant Institute of Engineering & Technology Pauri India

ISBN: (数字)9798331518578

ISBN: (纸本)9798331518585

The exponential growth of communication technologies has broadened the cloud computing ecosystem horizon to meet main communication needs. However, in-parallel upsurge in online attacks has alarmed industries to ensure optimal data security. The combination of steganography and cryptosystems has been recognized as an enhanced security model for data transfer among the main security systems now in use. In this paper, a hybrid approach using cryptography and K- Least Significant Bit Steganography algorithm in Cloud computing (HYBC-KLSBS-CC) are proposed. Initially, input text data is retrieved from cloud storage and compressed using Huffman Compression Coding (HCC) to reduce data size. The compressed data is then encrypted with a Hybrid Cryptography Algorithm (Hyb-MRFC-ALC), combining Modified Random Fibonacci Cryptography and Asymmetric Lightweight Cryptography to ensure robust encryption. Finally, encrypted data is embedded within an image using the K-Least Significant Bit (KLSB) steganography technique, providing additional layer of security. The proposed method enhances data confidentiality, integrity, and storage efficiency in cloud environments. The proposed HYBC-KLSBS-CC approach attains 26.89%, 29.49% and 18.64% lower PSNR and 26.89%, 29.49% and 18.64% lower MSE when analyzed through existing techniques like data security dependent on cryptography steganography related with OTP procedure and Huffman coding in the cloud environment (CS-OTP-CE), a novel hybrid cryptographic framework for secure data storage in cloud computing: Integrating AES-OTP and RSA with adaptive key management and Time-Limited access control (AES-OTP-RSA-CC) and Crypto-Stegno dependent model for securing medical information on IOMT platform (CS-SMI-IOMT).

关键词： Cloud computing Steganography Image coding Computational modeling data models Encoding Communications technology Encryption Cryptography Huffman coding

来源：评论

学校读者我要写书评

暂无评论

A Privacy Preserving Decision Tree Classification Algorithm for Prediction of Health Care Monitoring System 3rd

A Privacy Preserving Decision Tree Classification Algorithm ...

引用

3rd international conference on Intelligent Systems and Sustainable computing, ICISSC 2023

作者： Raj, Thaluka Mohan Maheswari, K. Raju, K. Srujan Shweta, N. Dharmireddi, Srinivasarao Reddy, Avala Raji Department of Computer Science and Engineering CMR Technical Campus Hyderabad India

ISBN: (纸本)9789819783540

In recent years, health monitoring systems have become popular due to increasing medical costs and advances in wireless technology. Organisations use information systems to develop and distribute information as well as gather, filter, and process data. Patients are responsible for sharing information with particular types of healthcare providers in order to make an accurate diagnosis and decide on the most appropriate model of treatment. In health monitoring systems, hospitals outsource clinical decision-making models to cloud service providers, who then use the models to make clinical decisions based on the biomedical information they receive from remote clients. Biomedical data as well as clinical decision-making models must be protected since privacy issues are extremely serious. An effective categorization technique for health monitoring systems using a privacy-preserving decision tree (PPDT) is given in this analysis. Decision tree classification with privacy preservation is carried out by using the encrypted token to search the encrypted index. According to a performance analysis, PPDT is extremely effective in terms of accuracy, time, storage, and communication. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Electronic health record

来源：评论

学校读者我要写书评

暂无评论

Swin-VasMamba: A Topologically Constrained Model For 3D Vascular Segmentation

Swin-VasMamba: A Topologically Constrained Model For 3D Vasc...

引用

2025 IEEE international conference on Acoustics, Speech, and Signal Processing, ICASSP 2025

作者： Liu, Ziyu Li, Jiaxuan He, Xiangjian Xu, Qing Chen, Xin Zhou, Shoujun School of Computer Science University of Nottingham Ningbo China Shenzhen Institute of Advanced Technology Chinese Academy of Sciences China School of Computer Science University of Nottingham United Kingdom

ISBN: (纸本)9798350368741

Accurate 3D vascular segmentation is essential for diagnosing and treating vascular diseases. This task remains challenging due to the complexity of the 3D data and the morphological diversity of blood vessels. In recent years, state space models (SSMs) have received a great attention for its good performance while preserving global receptive field and consuming less computing resources and time. Inspired by this, we propose a model called Swin-VasMamba for 3D vascular segmentation. It consists of a network called CMU-Net and a topologically constrained loss function called dsh loss. We compare our model with several other advanced segmentation models based on CNN, Transformer and Mamba. The results show that Swin-VasMamba achieves a state-of-the-art performance, with the highest Dice coefficient of 0.880, the lowest 95th-percentile of Hausdorff Distance (HD95) of 0.673, and the lowest Average Surface Distance (ASD) of 0.159 on a benchmark dataset. © 2025 IEEE.

关键词： 3D Vascular segmentation CNN Mamba topological constraint

来源：评论

学校读者我要写书评

暂无评论

Enhancing Federated Learning Robustness in Non-IID data Environments via MMD-Based Distribution Alignment 25th

Enhancing Federated Learning Robustness in Non-IID Data Env...

引用

25th international conference on Parallel and Distributed computing, Applications and technologies, PDCAT 2024

作者： Ma, Xiao Shen, Hong Lyu, Wenqi Ke, Wei Faculty of Applied Sciences Macao Polytechnic University China School of Engineering and Technology Central Queensland University Rockhampton Australia

ISBN: (纸本)9789819642069

Federated learning(FL), due to its distributed nature, is highly susceptible to malicious attacks. Although various Byzantine-robust FL methods exist, they often fail to maintain robustness in practical scenarios due to the non-independent and identically distributed (Non-IID) nature of client data. Moreover, existing FL methods often suffer from weight divergence caused by heterogeneous data distributions across clients. To address these issues, we propose a novel federated learning framework that aligns local data distributions across different clients to enhance robustness for Non-IID data in adversarial environments. It contains a feature transformation layer that incorporates Maximum Mean Discrepancy (MMD) as a regularization term to avoid weight divergence through aligning local and global data distributions without sharing raw data. Our approach dynamically updates the statistical information of both local and global data, including the mean and variance, ensuring that local models are closely aligned with the global model throughout training. Experimental results on MNIST and CIFAR-10 datasets demonstrate that our proposed framework significantly improves robustness both in the absence of attacks and against untargeted attacks such as sign-flipping and additive noise. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Federated learning

来源：评论

学校读者我要写书评

暂无评论

Privacy Preservation of Cluster Integrity on Web-Scraped Hospital data

Privacy Preservation of Cluster Integrity on Web-Scraped Hos...

引用

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

作者： Hrishik Sai Bojnal Dharmisht SVK J Krishna Kaarthik Dhyaan Kotian Shashidhar Virupaksha Department of Computer Science and Engineering RV Institute of Technology and Management Bengaluru Karnataka India Visvesvaraya Technological University Belagavi Karnataka India

ISBN: (数字)9798350356236

ISBN: (纸本)9798350356243

This paper proposes a method for anonymizing geospatial healthcare data that preserves the natural clustering of locations. A dataset is built with each healthcare facility's location, ratings, and review count by scraping it off an online maps platform. This enables the calculation of each facility's regional influence. The approach retains spatial clusters by restricting the displacements on each facility's geospatial coordinates to at most the minimum radius of the cluster while also factoring for the prominence of the facility in the region. This ensures that the shape and magnitude distribution of clusters is maintained, thereby preserving dataset quality. Impactful insights can be drawn from this anonymized dataset without having to identify any individual facility.

关键词： data privacy Hospitals Reviews Shape Layout Spatial databases Information filtering Geospatial analysis Protection Information integrity

来源：评论

学校读者我要写书评

暂无评论

Integrating Instruction-based Learning with Bidirectional LSTM for Autonomous Vehicle Pedestrian Detection

Integrating Instruction-based Learning with Bidirectional LS...

引用

2025 international conference on Multi-Agent Systems for Collaborative Intelligence, ICMSCI 2025

作者： Shoba, B. Raghunathan, T. Peter, S.Sam Karthick, K. Akshya, J. Sundarrajan, M. Choudhry, Mani Deepak Psn College of Engineering and Technology Department of Electronics and Communication Engineering Tirunelveli India Dr.NG.p.Institute of Technology Department of Artificial Intelligence and Data Science Coimbatore India Sri Krishna College of Technology Department of Computer Science and Engineering Coimbatore India Sona College of Technology Department of Information Technology Salem India Srm Institute of Science and Technology Department of Computational Intelligence Chennai India Srm Institute of Science and Technology Department of Networking and Communications Chennai India Srm Institute of Science and Technology Department of Computing Technologies Chennai India

ISBN: (纸本)9798331509828

Pedestrian detection is a crucial aspect of autonomous vehicle (A V) safety, as it enables accurate identification and tracking of individuals in an A V environment. Effective pedestrian detection supports essential A V functions like braking, steering, and speed control to prevent accidents in urban settings. Traditional computer vision methods, such as Support Vector Machines and Random Forests, rely on pre-designed features like the Histogram of Oriented Gradients. While the existing techniques offer some performance, it face significant challenges in dynamic environments, especially under varying lighting conditions, occlusions, and diverse pedestrian poses. Traditional models also require extensive manual feature engineering and tuning, which limits scalability and adaptability. Recent advances in deep learning, particularly with Convolutional Neural Networks (CNNs), have allowed for automatic feature learning, yielding practical improvements over classical methods. However, CNNs can struggle in low light and when facing adversarial attacks, as they mainly capture spatial features. To address these limitations, this research proposes a new methodology combining CNNs for spatial feature extraction with Bidirectional Long Short-Term Memory (BiLSTM) networks to capture temporal dependencies. This hybrid approach enhances detection capabilities by learning both static and dynamic patterns. Our proposed CNN-BiLSTM model achieves a 92 % detection accuracy and an F1 score of 88.5% across diverse conditions, outperforming existing models by up to 15%. By integrating temporal features, the model reduces missed detections and false positives by up to 20%, providing a more reliable and adaptable solution for pedestrian detection in autonomous vehicles. © 2025 IEEE.

关键词： Convolutional neural networks

来源：评论

学校读者我要写书评

暂无评论

Analysis for Predicting English Premier League Matches Using Clifford-Steerable Convolutional Networks

Analysis for Predicting English Premier League Matches Using...

引用

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

作者： Mohideen AbdulKader M S. Advay Vaithieswaran Tanuj Rao Department of Computing Technologies School of Computing SRM Institute of Science and Technology Chengalpattu Tamilnadu India

ISBN: (数字)9798350356236

ISBN: (纸本)9798350356243

The most widely watched football league globally is the Barclays English Premier League (EPL), the future performance of which attracts attention from both scholars and practitioners in terms of outcome prediction. It is still challenging to provide accurate predictions per match result because of the many attempts tried in the past due to complicated interference of many factors that entice game dynamics. In order to predict the EPL matches, this paper proposed a Cubature Kalman Filter Haar Wavelet Transform Clifford-Steerable Convolutional Neural Network with Mud Ring Algorithm (CKFHWTCSCNNet-MRA). The data was downloaded from Kaggle and the OCRCKF was used for data pre-processing. For feature selection the Q-DHWT was used, which stands for Quantized Discrete Haar Wavelet Transform. CS-CNNs were then applied to predict match results while The Mud Ring Algorithm (MRA) was applied to the analysis of hyperparameters. The rationale and validation of the proposed model is established based on the performance measures employed in predicting wins/loses of the match which yielded an outstanding accuracy, specificity, sensitivity and recall of 99%, F1-Score of 99% and error of 0.25%.

关键词： Accuracy Games Predictive models Prediction algorithms Feature extraction Discrete wavelet transforms Kalman filters Convolutional neural networks Multiresolution analysis Sports

来源：评论

学校读者我要写书评

暂无评论

Color Image Encryption Using Novel 5D Piecewise Map

Color Image Encryption Using Novel 5D Piecewise Map

引用

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

作者： Bharti Salunke Sharad Salunke Department of Computer Science & Engineering Parul University Vadodara India

ISBN: (数字)9798350356236

ISBN: (纸本)9798350356243

This paper presents a novel color image encryption technique using a 5D piecewise chaotic map. In recent years, image encryption has become crucial for securing multimedia data in various applications, especially in communication over the internet. The proposed 5D piecewise map introduces complex chaotic behavior, ensuring higher security for color images. We extensively evaluate the performance of the encryption scheme using metrics such as correlation coefficient, information entropy, and keyspace. The results indicate that the proposed method achieves excellent security properties, and provides a substantial keyspace to prevent unauthorized access. Additionally, the comparison with recent methods demonstrates the superiority of our proposed encryption approach in terms of encryption speed, randomness, and robustness.

关键词： Measurement Correlation coefficient Chaotic communication Color Robustness Encryption Security Multimedia communication Information entropy

来源：评论

学校读者我要写书评

暂无评论

HybridFL: Hybrid Approach Toward Privacy-Preserving Federated Learning 6th

HybridFL: Hybrid Approach Toward Privacy-Preserving Federate...

引用

6th international conference on Security and Privacy in New computing Environments, SPNCE 2023

作者： Ali, Sheraz Mamoon, Saqib Usman, Areeba Abidin, Zain ul Zhao, Chuan School of Information Science and Engineering University of Jinan Jinan250022 China School of Computer Science and Engineering Nanjing University of Science and Technology Nanjing210094 China University of Sargodha Sargodha Pakistan Shandong Provincial Key Laboratory of Network-Based Intelligent Computing University of Jinan Jinan250022 China Shandong Provincial Key Laboratory of Software Engineering University of Jinan Jinan250022 China

ISBN: (纸本)9783031736988

In this study, we introduce a novel Hybrid Federated Learning (HybridFL) approach aimed at enhancing privacy and accuracy in collaborative machine learning scenarios. Our methodology integrates Differential Privacy (DP) and secret sharing techniques to address inference risks during training and protect against information leakage in the output model. Drawing inspiration from recent advances, we present a HybridFL framework that combines the strengths of Homomorphic Encryption (HE) and Multi-Party Computation (MPC) to achieve secure computation without the computational overhead of pure HE methods. Our contributions include a privacy-preserving design for Federated Learning (FL) that ensures local data privacy through secret sharing while leveraging DP mechanisms for noise addition. The system offers resilience against unreliable participants and is evaluated using various machine learning models, including Convolutional Neural Networks (CNN), Multi-Layer Perceptrons (MLP), and linear regression. Furthermore, we address potential external threats by deploying predictive model outputs as robust services against inference attacks. Experimental results demonstrate improved accuracy and convergence speed, establishing the viability of HybridFL as an effective solution for collaborative machine learning with enhanced privacy guarantees. © ICST Institute for Computer sciences, Social Informatics and Telecommunications Engineering 2025.

关键词： Federated learning

来源：评论

学校读者我要写书评

暂无评论

Energy-Efficient Autism Spectrum Disorder data Collection Mechanism using Wireless Sensor Networks and Internet-of-Things

Energy-Efficient Autism Spectrum Disorder Data Collection Me...

引用

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

作者： Vijaya Shetty S Srujana S.N P. Ramesh Naidu Jyoti Neeli Sarojadevi H Ramya Prakash Department of Computer Science and Engineering Nitte Meenakshi Institute of Technology Bengaluru Karnataka India

ISBN: (数字)9798350356236

ISBN: (纸本)9798350356243

A patient's cognitive health may be better assessed using smart monitoring and assisted living technologies. Social skills, repetitive habits, verbal and nonverbal communication, and adjusting to new environments are among the challenges children on the autism spectrum face. Because of their reduced cognitive capacities, children with autism spectrum disorder (ASD) present a significant public health challenge because it is difficult to comprehend their feelings. The main purpose of this research is to assist autistic newborns in adapting to their environment via Internet-of-things (IoT) technologies and wireless sensor networks. The study indicates an Internet of Things (IoT)-WSNs system for data collection, using an energy-efficient cluster-based routing optimization (EECRO) method that sends data to an IoT gateway server as quickly as possible, allowing the guardian to access the data in real-time. The simulation outcome indicates the EECRO can significantly reduce energy consumption to deliver messages from autistic children to their guardians.

关键词： Wireless sensor networks Autism Pediatrics Energy consumption Computational modeling Routing Energy efficiency Real-time systems Internet of Things Optimization

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 << < 7 8 9 10 11 12 13 14 15 16 > >>

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：