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

6,842 篇 会议
70 篇 期刊文献
44 册 图书

馆藏范围

6,956 篇 电子文献
0 种 纸本馆藏

日期分布

学科分类号

3,947 篇 工学
- 3,648 篇 计算机科学与技术...
- 2,754 篇 软件工程
- 1,193 篇 信息与通信工程
- 701 篇 控制科学与工程
- 510 篇 电气工程
- 474 篇 生物工程
- 331 篇 网络空间安全
- 313 篇 生物医学工程（可授...
- 274 篇 电子科学与技术（可...
- 259 篇 动力工程及工程热...
- 215 篇 交通运输工程
- 215 篇 安全科学与工程
- 213 篇 机械工程
- 208 篇 仪器科学与技术
- 179 篇 光学工程
- 165 篇 化学工程与技术
- 165 篇 石油与天然气工程
1,718 篇 理学
- 1,022 篇 数学
- 494 篇 生物学
- 372 篇 统计学（可授理学、...
- 305 篇 物理学
- 252 篇 化学
- 195 篇 系统科学
1,362 篇 管理学
- 778 篇 图书情报与档案管...
- 744 篇 管理科学与工程(可...
- 352 篇 工商管理
338 篇 医学
- 269 篇 临床医学
- 260 篇 基础医学(可授医学...
- 168 篇 公共卫生与预防医...
- 164 篇 药学(可授医学、理...
195 篇 法学
129 篇 经济学
87 篇 农学
71 篇 教育学
19 篇 文学
8 篇 军事学
2 篇 艺术学

主题

311 篇 big data
294 篇 machine learning
211 篇 deep learning
210 篇 data mining
202 篇 data models
157 篇 cloud computing
138 篇 machine learning...
123 篇 training
119 篇 computational mo...
116 篇 feature extracti...
108 篇 signal processin...
102 篇 predictive model...
97 篇 internet of thin...
96 篇 signal processin...
94 篇 prediction algor...
89 篇 support vector m...
83 篇 data privacy
80 篇 artificial intel...
74 篇 sentiment analys...
72 篇 edge computing

机构

88 篇 maharishi school...
67 篇 centre of interd...
31 篇 department of ar...
28 篇 tianjin universi...
28 篇 college of compu...
27 篇 vishwakarma inst...
26 篇 department of co...
26 篇 department of el...
25 篇 chitkara univers...
25 篇 department of co...
22 篇 department of in...
18 篇 university of ch...
17 篇 chitkara univers...
17 篇 lovely professio...
17 篇 department of sc...
17 篇 vishwakarma inst...
17 篇 vivekananda glob...
16 篇 department of el...
15 篇 vishwakarma inst...
14 篇 key laboratory o...

作者

11 篇 dipannita mondal
11 篇 ramakrishnan ram...
10 篇 wang jing
10 篇 nitin n. sakhare
10 篇 rajeswari d.
9 篇 mondal dipannita
8 篇 kumar ritesh
8 篇 akhilendra prata...
8 篇 li zuoyong
8 篇 kodipalli ashwin...
8 篇 jambi ratna raja...
7 篇 chen chen
7 篇 liu ying
7 篇 xu xiaolong
7 篇 vaishali singh
7 篇 zhang jing
6 篇 zheng-guang wu
6 篇 bin wang
6 篇 ye jun
6 篇 yang yang

语言

4,159 篇 英文
2,790 篇 其他
112 篇 中文

检索条件"任意字段=2023 International Conference on Algorithms, Computing and Data Processing, ACDP 2023"

共 6956 条记录，以下是4561-4570 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：

Robust Graph Embedding Recommendation Against data Poisoning Attack

Robust Graph Embedding Recommendation Against Data Poisoning...

引用

international conference on Big data Intelligence and computing, dataCom 2022

作者： Zhong, Junyan Liu, Chang Wang, Huibin Tian, Lele Zhu, Han Lam, Chan-Tong HSBC Software Development Guangdong Ltd. Guangzhou China Faculty of Humanities and Social Science Macao Polytechnic University China ABB Global Open Innovation Center Shenzhen China Gree Electric Appliances Inc. of Zhuhai Zhuhai China Faculty of Applied Sciences Macao Polytechnic Uniuversity China

ISBN: (纸本)9789819922321

With the development of recommendation system technology, more and more Internet services are applied to recommendation systems. In recommendation systems, matrix factoring is the most widely used technique. However, matrix factoring algorithms are very susceptible to shilling attacks (trust or espionage). The former defends methods against data poisoning attacks focused on detecting individual attack behaviors. But there are few detection methods for group data poisoning attacks. Therefore, we propose a detection method based on Graph Neural Network (GNN) and adversarial learning. We train user-item nodes and edges through a semi-supervised learning approach, improving the robustness of the GNN recommendation system. Our work can be divided into the following parts: Firstly, we review the former recommendation systems and the graph representation learning recommendation systems. Secondly, we analyze the main vulnerabilities of the graph representation learning recommendation systems. Furthermore, the detection methods of data poisoning attacks are analyzed, and the difference between individual data poisoning attacks and group data poisoning attacks are discussed. Finally, we propose a per-process Robust-GNN semi-supervised detection model to conduct group detection on different types of attacks. In addition, we also analyze the sensitivity of the proposed methods. From the experiments results, it can be concluded that we should apply the attention mechanism to the proposed methods which makes it more generalized. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Graph neural networks

来源：评论

学校读者我要写书评

暂无评论

Genetic Algorithm and Its Application in Software Test data Generation

Genetic Algorithm and Its Application in Software Test Data ...

引用

Applied Intelligence and Sustainable computing (ICAISC), international conference on

作者： Luo Gang Qiannan Normal University for Nationalities China

Genetic algorithm is a computational technique that simulates the process of natural selection to solve complex problems. It has been widely applied in various fields, including software engineering. One of its applications in software engineering is test data generation. Test data generation is an important component of software testing, aimed at ensuring the quality and reliability of software systems. However, generating effective test data can be challenging and time-consuming, especially for complex systems with large input domains. Genetic algorithm provides a solution to this problem by using population based search methods to generate test data that meets specific criteria. This algorithm starts from the initial population of random test cases and iteratively evolves them through selection, crossover, and mutation operations until a satisfactory solution is found. The effectiveness of genetic algorithms in generating test data has been proven in various studies. It has been proven to generate various effective test cases, covering different parts of the input domain, and revealing hidden faults in the system. In short, genetic algorithms are a powerful tool for software engineers to generate effective test data for complex systems. Its application can significantly improve the quality and reliability of software systems by identifying hidden faults that may not have been discovered. In this study, we analyzed genetic algorithms in current software testing, controlled them based on model data and generation structure in software testing, and obtained effective calculation methods based on various genetic algorithms. By using traditional genetic algorithms and various swarm genetic algorithms to analyze the distribution and optimal value interval of two curves, it is shown that various swarm genetic methods have strong optimization ability, high accuracy, and can quickly jump out of local optima to obtain the final solution. They are a very effective optimizat

关键词：

来源：评论

学校读者我要写书评

暂无评论

19th IFIP WG 12.5 international conference on Artificial Intelligence Applications and Innovations, AIAI 2023

19th IFIP WG 12.5 International Conference on Artificial Int...

引用

19th IFIP WG 12.5 international conference on Artificial Intelligence Applications and Innovations, AIAI 2023

ISBN: (纸本)9783031341700

The proceedings contain 129 papers. The special focus in this conference is on Artificial Intelligence Applications and Innovations. The topics include: Generating Synthetic Vehicle Speed Records Using LSTM;Measuring the State-Observation-Gap in POMDPs: An Exploration of Observation Confidence and Weighting algorithms;predicting Colour Reflectance with Gradient Boosting and Deep Learning;the Importance of the Current Input in Sequence Modeling;towards Historical Map Analysis Using Deep Learning Techniques;analysis of the Lingering Effects of Covid-19 on Distance Education;exploring the Power of Failed Experiences in Case-Based Reasoning for Improved Decision Making;improving Customer Experience in Call Centers with Intelligent Customer-Agent Pairing;a Sharpe Ratio Based Reward Scheme in Deep Reinforcement Learning for Financial Trading;mind the Gap: Addressing Incompleteness Challenge in Case-Based Reasoning Applications;Sentiment Analysis of Tweets on Online Education during COVID-19;image Classification Using Class-Agnostic Object Detection;Ince-PD Model for Parkinson’s Disease Prediction Using MDS-UPDRS I & II and PDQ-8 Score;medical Knowledge Extraction from Graph-Based Modeling of Electronic Health Records;Predicting ALzheimer's Disease with AI and Brain Imaging data;Pre-trained Model Robustness Against GAN-Based Poisoning Attack in Medical Imaging Analysis;semi-supervised Brain Tumor Segmentation Using Diffusion Models;A Methodology for Emergency Calls Severity Prediction: From Pre-processing to BERT-Based Classifiers;a Temporal Metric-Based Efficient Approach to Predict Citation Counts of Scientists;algorithmic Forex Trading Using Q-learning;Comparing Vectorization Techniques, Supervised and Unsupervised Classification Methods for Scientific Publication Categorization in the UNESCO Taxonomy;decoding Customer Behaviour: Relevance of Web and Purchasing Behaviour in Predictive Response Modeling;exploring Pairwise Spatial Relationships for Actions Recognition and

关键词：

来源：评论

学校读者我要写书评

暂无评论

Implementation of Ensemble Algorithm with data Pruning on Qualcomm Snapdragon 820c

Implementation of Ensemble Algorithm with Data Pruning on Qu...

引用

international conference on computing and Networking Technology (ICCNT)

作者： Purab Nandi K. R. Anupama Himanish Agarwal Arav Jain Siddharth Paliwal Rohan Jakhar Department of EEE K.K. Birla Goa Campus BITS Pilani Goa India

Falls, especially those left unattended for an extended period are serious health issues for the geriatric population. Several efforts have been made in the use of IoT and ML algorithms in fall detection. These systems have issues in terms of sensor placements and connectivity since most of the data analysis is done on the cloud. Sensors are usually placed on the thigh or the torso this may prove to be very uncomfortable for the elderly. Also, constant disconnects from the network and high latencies may delay a Fall alert. Therefore, we have built a wrist-worn end device that uses the concept of Dew computing, where the computing is done on the end device itself. In order to have good prediction accuracies, we have also developed three ensemble algorithms; the first one is based on stacking, we call this Stack (A), the other two are based on voting, and we term them as Variable Weight Ensemble (B) and (C). This ensemble algorithm runs on the end device which is equipped with IMU and heart rate sensors. Qualcomm Snapdragon 820c is the SoC around which the end device is built. To execute the algorithms on the end device we use feature extraction as well as feature selection to prune the data. We obtained an accuracy between 97.5% to 98.1% for various algorithms and a sensitivity of almost 100%. In this paper we present a complete analysis of the Fall detection system (with and without pruning), we have analysed the accuracies and the latencies on 820c while using ensemble algorithms specifically. We have compared the performance of our algorithms with XGBoost, AdaBoost and RF ensemble techniques.

关键词：

来源：评论

学校读者我要写书评

暂无评论

19th IFIP WG 12.5 international conference on Artificial Intelligence Applications and Innovations, AIAI 2023

19th IFIP WG 12.5 International Conference on Artificial Int...

引用

19th IFIP WG 12.5 international conference on Artificial Intelligence Applications and Innovations, AIAI 2023

ISBN: (纸本)9783031341069

关键词：

来源：评论

学校读者我要写书评

暂无评论

Research into Developing a data Mining-Based Quantitative Trading System for Use with Software and High Performance Computers

Research into Developing a Data Mining-Based Quantitative Tr...

引用

Industrial IoT, Big data and Supply Chain (IIoTBDSC), international conference on

作者： Paulo Zhang Hong Kong Red Lion Capital Limited Hong Kong China

ISBN: (数字)9798350341690

ISBN: (纸本)9798350341706

This research is dedicated to the design and study of quantitative trading systems based on data mining methods in software and high-performance computing environments. With the continuous accumulation of financial market data and the improvement of computing power, quantitative trading, as a method of trading decision making using mathematical models and algorithms, has received more and more attention from traders and investors. In this study, the basic concepts, methods and techniques of quantitative trading are firstly reviewed to introduce the important role of data mining in quantitative trading. Subsequently, a design framework for a quantitative trading system based on data mining methods is proposed, which combines the key steps of data collection, feature engineering, model construction, and trade execution to improve the real-time performance and efficiency of the trading system.

关键词： High performance computing Computational modeling Supply chains Software algorithms Software Real-time systems data models

来源：评论

学校读者我要写书评

暂无评论

MS-SAM: Multi-scale SAM Based on Dynamic Weighted Agent Attention 31st

MS-SAM: Multi-scale SAM Based on Dynamic Weighted Agent Att...

引用

31st international conference on Multimedia Modeling, MMM 2025

作者： Yang, Enhui Zhang, Zhibin Engineering Research Center of Ecological Big Data Ministry of Education Key Laboratory of Wireless Networks and Mobile Computing Inner Mongolia University Hohhot010021 China

ISBN: (纸本)9789819620630

The Segment Anything Model (SAM), introduced in 2023, has made significant advancements in the field of computer vision. However, SAM faces two major challenges: limitations related to single-scale processing and high computational demands for large-scale data handling, which restrict its widespread adoption in practical applications. Therefore, we propose MS-SAM to achieve better segmentation performance at a lower cost. We introduce a multi-scale image encoder to handle images of varying scales and complexities. Additionally, we propose a dynamic weighted agent attention, which can flexibly and efficiently adjust attention distribution while reducing computational costs. We train MS-SAM on a 1/20 subset of the SA-1B dataset for instance segmentation using points or boxes as prompts. The results show that we maintain the accuracy with the SAM method while reducing the parameters by about 6 times. We give sufficient experimental results to demonstrate its effectiveness. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Image segmentation

来源：评论

学校读者我要写书评

暂无评论

Computer data Security and Encryption Algorithm Based on Mobile Edge computing

Computer Data Security and Encryption Algorithm Based on Mob...

引用

Networking, Informatics and computing (ICNETIC), international conference on

作者： Nannan Jiang Jianing Wang Xiaoting Yu Wenting Ma Lurong Sun Harbin HuaDe University Harbin China

With the rapid development of science and technology, data is increasing exponentially. data security has become a problem that people pay close attention to. How to ensure data security has aroused people's thinking. In order to ensure the communication security of network data, this paper points out the security threats in computer network communication, clarifies the significance of data encryption technology, and analyzes the commonly used data encryption methods in computer network communication. In this paper, a computer data security application model based on edge computing is constructed. In this model, data redundancy elimination method and differential privacy protection algorithm are adopted successively. After removing duplicate data and obtaining good quality data, the computer data is privacy protected, and the data security processing based on edge computing is realized. After testing, the privacy protection budget value of the built model is 0.23, and the computer data information leakage ratio based on edge computing is the smallest. Under this condition, the maximum data information leakage ratio based on edge computing is reduced from 0.678 to 0.234, and the data security is significantly improved.

关键词：

来源：评论

学校读者我要写书评

暂无评论

A Fine-Grained data Encryption Scheme Based on Shortest Vector Problem in the Cloud computing Environment

A Fine-Grained Data Encryption Scheme Based on Shortest Vect...

引用

IEEE international conference on Signal and Image processing (ICSIP)

作者： Qinlu Yang Rui Jiang School of Cyber Science and Engineering Southeast University Nanjing China

Lattice-based encryption is a promising public key cryptography to resist quantum computing attacks. Simultaneously, due to the need for fine-grained access control in cloud environments, it is crucial to do the research on attribute-based encryption (ABE). However, researches on ABE algorithm have some problems such as not having mechanisms secure enough to defend against quantum computing attacks with high decryption accuracy, having vulnerabilities to collusion attacks and lacking of attribute revocation mechanism. In order to solve the above problems, we propose a new data encryption scheme with fine-grained access control based on the shortest vector problem in the cloud computing environment (DES-SVP). We formally prove that our DES-SVP scheme can resist quantum computing attacks and can resist collusion attacks between users. We reduce our DES-SVP scheme to the problem of finding a short vector in a lattice so that our scheme can withstand quantum computing attacks. Finally, the performance analysis shows that our DES-SVP scheme can achieve efficient results comparing with other related works.

关键词：

来源：评论

学校读者我要写书评

暂无评论

NLP Tools for Epileptic Seizure Prediction Using EEG data: A Comparative Study of Three ML Models 6th

NLP Tools for Epileptic Seizure Prediction Using EEG Data: A...

引用

6th international conference on Nanotechnologies and Biomedical Engineering, ICNBME 2023

作者： Iapascurta, Victor Fiodorov, Ion Department of Software Engineering and Automation Technical University of Moldova Chisinău Moldova Department of Anesthesia and Intensive Care N. Testemitanu State University of Medicine and Pharmacy Chisinău Moldova

ISBN: (纸本)9783031427817

Natural Language processing (NLP) is an ever-evolving field of computer science that involves the development of algorithms that can process, analyze and understand human language. One of the most exciting areas of NLP is the creation of NLP language models with applications across almost every industry. However, most people only associate NLP with its traditional use in language translation, sentiment analysis, and chatbots. In reality, there are many less-common uses for NLP models that have the potential to transform businesses, improve customer experiences, and even save lives. In the healthcare industry, NLP models can be used to analyze unstructured medical data and help diagnose and treat patients more efficiently. For example, NLP can be used to analyze clinical notes, lab results, and other data combing through vast amounts of data to identify patterns and create targeted treatment plans. NLP-based medical diagnosis is still in its infancy, but it has the potential to revolutionize the healthcare industry in the coming years. This article explores a less common use of machine-learning language models built on transformed EEG data for epilepsy prediction using the Kolmogorov-Chaitin algorithmic complexity as the first step in generating text-like data, which are finally used for building machine learning models. © 2024, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Diagnosis

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 << < 453 454 455 456 457 458 459 460 461 462 > >>

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：