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
71 篇 期刊文献
44 册 图书

馆藏范围

6,957 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
1,720 篇 理学
- 1,022 篇 数学
- 494 篇 生物学
- 372 篇 统计学（可授理学、...
- 306 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
158 篇 cloud computing
139 篇 machine learning...
124 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...
20 篇 vivekananda glob...
18 篇 university of ch...
18 篇 vishwakarma inst...
17 篇 chitkara univers...
17 篇 lovely professio...
17 篇 department of sc...
16 篇 department of el...
15 篇 vishwakarma inst...
14 篇 key laboratory o...

作者

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

语言

4,160 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 6957 条记录，以下是4461-4470 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 for Enhancing data Aggregation Security in the Internet of Medical Things

A Hybrid Approach for Enhancing Data Aggregation Security in...

引用

international conference on computing and Networking Technology (ICCNT)

作者： Abhishek Bajpai Akash Maurya Anita Yadav Rajkiya Engineering College Kannauj India Harcourt Butler Technical University Kanpur India

In this study, we focus on addressing the security and privacy challenges associated with the Internet of Medical Things (IoMT) and associated data. IoMT involves the transmission of large volumes of real-time medical data from various small devices. To tackle these challenges, we propose a novel approach that combines the Lightweight Encryption Algorithm (LEA) with the Paillier encryption approach. This combination is aimed at improving energy consumption, encryption time, and memory usage. By employing LEA encryption, our approach ensures both confidentiality and data integrity during the transmission of medical data. Additionally, the Paillier encryption technique is leveraged to preserve privacy and facilitate secure data aggregation. Through extensive security analysis and experimental evaluations, we have found that our proposed method achieves average encryption and decryption speeds that are 30% faster and 8% less energy consumption compared to the ECC-AES and ElGamal algorithms.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Learning from Patterns via Pre-trained Masked Language Model for Semi-supervised Automated Essay Scoring 19th

Learning from Patterns via Pre-trained Masked Language Model...

引用

19th international conference on Advanced Intelligent computing Technology and Applications (ICIC)

作者： Sun, Jingbo Peng, Weiming Song, Tianbao Song, Jihua Beijing Normal Univ Sch Artificial Intelligence Beijing 100875 Peoples R China Beijing Normal Univ Chinese Character Res & Applicat Lab Beijing 100875 Peoples R China Univ Penn Linguist Data Consortium Philadelphia PA 19104 USA Beijing Technol & Business Univ Sch Comp Sci & Engn Beijing 100048 Peoples R China

ISBN: (纸本)9789819947515;9789819947522

Automated essay scoring is one of the key applications of natural language processing technology in the field of education. Currently, pre-trained language models for automated essay scoring systems have no significant advantage over classical models, and pre-trained language models are underutilized for this task. Moreover, in real-world scenarios, supervised models that lack annotated data often perform poorly. To address the issue that the pre-trained language models are not fully applied, we propose a novel prompt tuning model PTAES in this paper, andwe convert the essay scoring procedure into a cloze-style question, after which we design pairs of natural language pattern-verbalizer. Further, we propose a joint model that combines the prompt tuning based model and the pre-trained fine-tuning based model, attempting to address the issue of inadequately supervised models in low-resource situations. Experimental findings indicate that, in supervised, semi-supervised, and zero-shot scenarios, our model can achieve state-of-the-art results, and our method further increases the value of the pre-trained language model in automated essay scoring.

关键词： Automated essay scoring Semi-supervised learning Prompt learning Pre-trained masked language model

来源：评论

学校读者我要写书评

暂无评论

Deep Learning-Based Brain Tumor Classification Prototype Using Transfer Learning

Deep Learning-Based Brain Tumor Classification Prototype Usi...

引用

Advances in Intelligent computing and Applications (AICAPS), international conference on

作者： Binju Saju Laiby Thomas Fredy Varghese Arpana Prasad Neethu Tressa New Horizon College of Engineering Bengaluru India Naipunnya Institute of Managerment and Information Technology Kerala India

Accumulation of cells with unimpeded growth is the hallmark for the development of life challenging brain tumor disease. In pre-existing research Machine Learning analytical models are trained on domain specific dataset to achieve goals of an Artificial Intelligence based application in Computer Science for the said disease identification. An ongoing research in the field is presented in this paper where an experimental set of 7038 domain specific images are used to train a model. On experiments conducted on the dataset using six different Machine Learning algorithms the researchers are able to identify Glioma tumor, Meningioma tumors and Pituitary tumor with an accuracy of 96% using RESTNET 5.0 with Transfer Learning Model.

关键词： Analytical models Machine learning algorithms Computational modeling Transfer learning Brain modeling data models Tumors

来源：评论

学校读者我要写书评

暂无评论

Efficient Online Convolutional Dictionary Learning Using Approximate Sparse Components

Efficient Online Convolutional Dictionary Learning Using App...

引用

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

作者： Farshad G. Veshki Sergiy A. Vorobyov Department of Signal Processing and Acoustics Aalto University Espoo Finland

Most available convolutional dictionary learning (CDL) methods use a batch-learning strategy, which consists of alternating optimization of the dictionary and the sparse representations using a training dataset. The computational efficiency of CDL can be improved using an online-learning approach, where the dictionary is optimized incrementally following a sparse approximation of each training sample. However, the existing online CDL (OCDL) methods are still computationally costly when learning large dictionaries. In this paper, we propose an OCDL approach that incorporates decomposed sparse approximations instead of the training samples and substantially improves the computational costs of the existing CDL methods. The resulting optimization problem is addressed using the alternating direction method of multipliers (ADMM).

关键词： Training Dictionaries Convolution Signal processing algorithms Training data Machine learning Approximation algorithms

来源：评论

学校读者我要写书评

暂无评论

Detecting Flood in Real-Time Weather data Using Anomaly Detection Algorithm

Detecting Flood in Real-Time Weather Data Using Anomaly Dete...

引用

international conference on Artificial Intelligence and data Sciences (AiDAS)

作者： Muhammad Yunus Iqbal Basheer Azliza Mohd Ali Nurzeatul Hamimah Abdul Hamid Rozianawaty Osman Sharifalillah Nordin Muhammad Azizi Mohd Ariffin College of Computing Informatics and Mathematics Universiti Teknologi MARA Shah Alam Selangor Malaysia

This paper presents flood detection using anomaly detection algorithms in real-time weather data. Nine different attributes are used to detect suspicious weather that can cause floods. The weather dataset was acquired from Kelantan, Malaysia. In this paper, the collected dataset will be sent from the chosen Internet of Things (IoT) pipeline to three different anomaly detection algorithms. These algorithms are multi-threaded autonomous anomaly detection (MAAD), robust random cut forest (RRCF), and outlier detection in feature-evolving data streams (xStream). Our evaluation demonstrates that the MAAD algorithm has a 68.5% precision score and a 0.01 false alarm rate, which is better than the RRCF and xStream for detecting floods.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Research on Federated Sharing Methods for Massive data in Blockchain 7th

Research on Federated Sharing Methods for Massive Data in Bl...

引用

7th EAI international conference on Smart Grid and Internet of Things, SGIoT 2023

作者： Wu, Bing Kang, Haiyan School of Information Management Beijing Information Science and Technology University Beijing100192 China

ISBN: (纸本)9783031559754

data storage with the help of blockchain can ensure the transparency, non-tampering and autonomy of data information holders. However, the on-chain storage of massive data will seriously affect the performance of blockchain, and some private sensitive data and so on are not suitable for public storage in blockchain. To address the above problems, a trusted federated learning method based on local differential privacy mechanism, Loosely Coupled Local Differential Privacy Blockchain Federated Learning (LL-BCFL) is proposed for blockchain that realizes secure and efficient processing of massive user data. Firstly, a client selection mechanism is proposed and designed with the help of blockchain, which mainly includes two operations, namely, verification update and reputation calculation, to ensure the correctness and effectiveness of global model aggregation as well as the honesty and motivation of clients participating in training. Secondly, federated learning is used to realize the joint training of massive data distributed stored in each terminal device, so as to alleviate the phenomenon of "data silos" caused by privacy and security issues. In addition, a local differential privacy mechanism is designed in this method to solve the inference attack problem in the training process of federated learning. Finally, experiments are conducted on the MNIST dataset for both balanced and unbalanced datasets to verify the effectiveness of the proposed method LL-BCFL. © ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering 2024.

关键词： Blockchain

来源：评论

学校读者我要写书评

暂无评论

Improving Rice Yield Prediction Accuracy Using Regression Models with Climate data 9th

Improving Rice Yield Prediction Accuracy Using Regression Mo...

引用

9th international conference on computing and Informatics, ICOCI 2023

作者： Mohamad Mohsin, Mohamad Farhan Umana, Muhammad Khalifa Hassan, Mohamad Ghozali Sharif, Kamal Imran Mohd Ismail, Mohd Azril Salleh, Khazainani Zahari, Suhaili Mohd Sarmani, Mimi Adilla Gordon, Neil School of Computing Universiti Utara Malaysia Kedah Sintok06010 Malaysia School of Technology Management and Logistics Universiti Utara Malaysia Kedah Sintok06010 Malaysia National Climate Center Malaysian Meteorological Department Selangor Darul Ehsan Petaling Jaya46667 Malaysia Computer Science University of Hull Hull United Kingdom

ISBN: (纸本)9789819995912

Rice production is critical to food security, and accurate yield predictions are required for planning and decision-making. However, precisely predicting rice yields using machine learning models can be difficult due to the complicated interactions of various factors, such as how climate affects rice production. This study sought to solve this rice production is critical to food security, and accurate yield predictions are required for planning and decision-making. However, accurately predicting rice yields using machine learning models can be difficult due to the complicated interactions of various factors, such as how climate affects rice production. This study aims to address this issue by investigating how climate data affect Malaysian rice yield prediction models. The study used a linear regression model trained on rice production data and compared its performance with models incorporating climate data. Both datasets covered the period from 2010 to 2021 in Malaysia. The study found that including climate data significantly improved the prediction accuracy, with an approximately 77% improvement in MAE and 69% in RMSE. The results suggest that incorporating climate data into yield prediction models is essential for accurate and reliable predictions. These findings have important implications for stakeholders in the agricultural industry who can use accurate yield predictions to make informed decisions. However, the study’s limitations include using a single predictive model and data from a single country, suggesting the need for future studies to explore other machine learning algorithms and expand the scope of the research to other regions. Overall, this study contributes to the growing body of literature on the impact of climate data on yield prediction models and highlights the importance of considering climate data in agricultural decision-making. © 2024, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Decision making

来源：评论

学校读者我要写书评

暂无评论

An Improved Differential Evolution Algorithm for Parameter Extraction of Photovoltaic Models

An Improved Differential Evolution Algorithm for Parameter E...

引用

Evolutionary algorithms and Soft computing Techniques (EASCT), international conference on

作者： Jai Keerthy Chowlur Revanna Dilli. Mahitha Kalakonda Jyothsna A. Mahendar Manjula B. M Information Systems Engineering and Management Harrisburg University of Science and Technology Harrisburg USA Malla Reddy Engineering College for Women Autonomous Coimbatore India Department of Electronics and Communication Engineering Vaageshwari College of Engineering Karimnagar India Department of Comuter Science and Engineering (Data Science) CMR Technical Campus Hyderabad India Department of Electronics and Communication Engineering Nitte Meenakshi Institute of Technology Bengaluru India

In photovoltaic systems, extracting parameters from generated current-voltage data is critical for simulating, controlling, and optimizing their performance. While there are several strategies for accomplishing this task, but they all have limitations. This work provides an improved adaptive differential evolution approach for solar system parameter extraction. A crossover rate sorting mechanism is developed in this system that allocates different crossover rates to individuals based on their fitness, allowing better-performing individuals to have a greater impact on the following generation. A Pelican optimization strategy used to speed up convergence and balance exploration and exploitation. The performance of the proposed method is validated by extracting characteristics from several solar models, including single diode, double diode, and photovoltaic modules. As a result, the proposed method is a viable and efficient option for parameter extraction in photovoltaic models.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Human Activity Recognition from Sensor data using Machine Learning

Human Activity Recognition from Sensor Data using Machine Le...

引用

Advanced computing & Communication Technologies (ICACCTech), international conference on

作者： Aditya Deepakshi Puri Vasu Prabhneet Singh Chandigarh University Chandigarh India

Human activity detection from sensor data has developed as a critical study subject with far-reaching implications in healthcare, sports, security, and beyond. This study proposes a unique way to reliably detect and categorise human actions using sensor data, leveraging sophisticated machine learning algorithms implemented with Python and the NumPy library. The combination of the Python programming language with the NumPy library provides rapid data manipulation and mathematical calculations, therefore permitting simplified implementation of the suggested technique. The source is made accessible to the scientific community, enabling openness, reproducibility, and continued development. Experimental findings using benchmark datasets indicate the usefulness of the proposed strategy, exhibiting great accuracy and resilience across varied human activities. The attained performance not only beats previous approaches but also illustrates the potential of the offered strategy in real-world applications.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Semantic Interoperability Toolkit for data Marketplaces

Semantic Interoperability Toolkit for Data Marketplaces

引用

international conference on Distributed computing in Sensor Systems (DCOSS)

作者： Márcio Mateus Bruno Almeida Gonçalo Rolo Gonçalo Rodrigues António Gonçalves Tiago Teixeira Pedro Maló UNPARALLEL Innovation Almada Portugal

Due to the countless number of data sources, an integration issue emerges, as the same data often have several representations. Therefore, this paper suggests a Natural Language processing (NLP) based approach for the so-called Semantic Interoperability Toolkit. It comprises two components - the Semantic Matchmaking solution and the Semantic Engine - allowing users to identify similarities between concepts and manage queries against them respectively, regardless of their original representations. The solution is at use on the AI4PublicPolicy's data Marketplace for supporting the exploitation of a wide range of data sets.

关键词：

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 << < 443 444 445 446 447 448 449 450 451 452 > >>

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：