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

6,378 篇 会议
161 册 图书
46 篇 期刊文献

馆藏范围

6,585 篇 电子文献
0 种 纸本馆藏

日期分布

学科分类号

4,749 篇 工学
- 4,176 篇 计算机科学与技术...
- 3,369 篇 软件工程
- 1,157 篇 信息与通信工程
- 762 篇 生物工程
- 563 篇 生物医学工程（可授...
- 497 篇 控制科学与工程
- 420 篇 电气工程
- 326 篇 动力工程及工程热...
- 267 篇 机械工程
- 254 篇 光学工程
- 251 篇 电子科学与技术（可...
- 240 篇 安全科学与工程
- 219 篇 化学工程与技术
- 214 篇 环境科学与工程（可...
2,076 篇 理学
- 942 篇 数学
- 830 篇 生物学
- 413 篇 物理学
- 399 篇 统计学（可授理学、...
- 278 篇 系统科学
- 222 篇 化学
1,415 篇 管理学
- 784 篇 管理科学与工程(可...
- 774 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
208 篇 农学
- 199 篇 作物学
197 篇 经济学
- 196 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...
262 篇 machine learning
253 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

6,395 篇 英文
184 篇 其他
15 篇 中文

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

共 6585 条记录，以下是131-140 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：

Ensuring data Integrity in Multi-Tenant Cloud Environments Through Advanced Testing

Ensuring Data Integrity in Multi-Tenant Cloud Environments T...

引用

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

作者： Vinay Kumar Gali Sansar Singh Chauhan Gopal Kumar Gupta Padmini Rajendra Bulani Vardhansinh Yogendrasinnh Ravalji Kumaresan Durvas Jayaraman Nagarjuna University Guntur Andhra Pradesh India Department of Computer Science and Engineering G.L. Bajaj Institute of Technology and Management Greater Noida India Symbiosis Institute of Technology Nagpur Campus Symbiosis International (Deemed University) Pune India Institute of Chartered Accountants of India Northeastern University Boston MA USA Bharathidasan University Tiruchirappalli Tamil Nadu India

ISBN: (数字)9798331518578

ISBN: (纸本)9798331518585

fortunately, multi-tenant cloud environments offer a more cost-effective provisioning model that consumes infrastructure to store and access data. As the volume of sensitive data processed and stored in the cloud continues to grow, ensuring data integrity has become a top concern for organizations. data integrity is the information that is correct, consistent, and reliable is stored in the cloud. To address this issue, we also present a solution that allows us to maintain integrity in a multi-tenant cloud environment using advanced testing. The standard approach to testing (functional and performance testing) does not identify and will enable us to prevent data integrity problems. That's because these approaches describe the system's functionality and performance rather than the accuracy of the system's data. They proposed a solution that used techniques like anomaly detection, data profiling, and data quality checks to discover possible integrity issues in the dataset. The new techniques work within the testing process, while all data is assessed for integrity before being stored in the cloud.

关键词： Access control Cloud computing data integrity Disasters Standards organizations Authentication Organizations Cryptography Reliability Testing

来源：评论

学校读者我要写书评

暂无评论

Fed-MoE: Efficient Federated Learning for Mixture-of-Experts Models via Empirical Pruning 25th

Fed-MoE: Efficient Federated Learning for Mixture-of-Expert...

引用

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

作者： Zou, Yifei Qi, Senmao Yuan, Yuan Wang, Dawei Shen, Shikun Wu, Libing Guo, Shaoyong Yu, Dongxiao School of Computer Science and Technology Shandong University Qingdao China School of Cyber Science and Engineering Wuhan University Wuhan China State Key Laboratory of Networking and Switching Technology Beijing University of Posts and Telecommunications Beijing China

ISBN: (纸本)9789819642069

In recent years, the combination of Federated Learning (FL) framework and Mixture of Experts (MoE) architecture has shown promise for large-scale model pre-training while preserving data privacy. However, the significant computational and communication requirement of MoE-based models presents substantial challenges for FL systems. To address this, we propose Fed-MoE, an efficient federated learning framework designed for MoE models through empirical pruning. Fed-MoE reduces computational overhead by pruning multiple experts at the client side while retaining general components, thus converting the model into dense sub-models. These sub-models are locally trained and later aggregated by the parameter server into a sparse MoE model. Our method optimizes the use of sparse activation in MoE models and reduces resource consumption without compromising performance. Extensive experimental results demonstrate that Fed-MoE significantly improves the efficiency of FL without compromising model performance, offering an effective solution for deploying large-scale MoE models in federated learning environments. © 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

Prediction of Covid and Covid-19 and Omicron data with ESPRINT, ERF, CSDLM and HMC-19HRP Models

Prediction of Covid and Covid-19 and Omicron data with ESPRI...

引用

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

作者： V. Ramya K.S. Thirunavakkarasu Department of Computer Science Vel's Institute of Science Technology and Advanced Studies Chennai Tamil Nadu India

ISBN: (数字)9798350356236

ISBN: (纸本)9798350356243

SARS-CoV-2, also known as the Covid-19 Corona Virus, has caused widespread damage globally, and the situation is only becoming worse. Officials from all across the world are using a number of COVID-19 outbreak prediction models to help them make choices and implement pertinent control measures. Simple epidemiological and statistical models are well-liked by the media and have garnered more attention from authorities among the conventional models for COVID-19 global pandemic prediction. It's a pandemic illness that spreads daily from person to person. As a result, it's critical to monitor the total patient population impacted. The way that the computerised data is now provided by the system makes it extremely difficult to analyse and forecast the spread of disease both locally and globally. An enhanced Sprint algorithm, Enhanced Random forest algorithm, Customized sequential Deep learning Model (CSDLM), and HMC-19HRP model is proposed in this study and analysed each with two dataset that is Covid dataset and OMICRON dataset. Finally results obtained from all the method are compared. On overall comparison HMC-19HRP outperforms other methods on both the dataset with precision of 94.92 and 98.26, Recall of 99.03 and 95.86, F1-score of 96.93 and 97.04, Specificity of 78.71 and 97.06 and Accuracy of 94.98 and 96.30 on covid data and Omicron dataset respectively.

关键词： COVID-19 Measurement Deep learning Accuracy Pandemics Computational modeling Predictive models Prediction algorithms data models Random forests

来源：评论

学校读者我要写书评

暂无评论

Long-Term and Periodicity-Aware Spatio-Temporal Model for Traffic Flow Prediction 25th

Long-Term and Periodicity-Aware Spatio-Temporal Model for Tr...

引用

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

作者： Hua, Qiang Lv, DongLiang Dong, Chun-Ru Zhang, Feng College of Mathematics and Information Science Hebei University Baoding071002 China

ISBN: (纸本)9789819642069

With the continuous expansion of comprehensive road transport networks in major cities, accurate traffic flow prediction—an essential component of intelligent urban transport systems has become increasingly challenging. Spatio-Temporal Graph Neural Networks (STGNNs), which combine time-series models like the Transformer with spatial relationship learning models such as Graph Neural Networks (GNNs), have shown significant promise in addressing this challenge. However, they still face issues like insufficient exploitation of long-term dependencies, high structural and computational complexity, and underutilization of periodic patterns in traffic data. To address these limitations, we propose LL-MLP, a spatio-temporal model based on an encoder-decoder architecture. Our approach extends the look-back window to better capture long-term dependencies, introduces learnable parameter matrices to enhance spatial information extraction, and incorporates periodic information as a dynamic covariate to further leverage temporal patterns. Extensive experiments on four real-world traffic datasets demonstrate that LL-MLP achieves performance on par with or exceeding that of existing model architectures. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Graph neural networks

来源：评论

学校读者我要写书评

暂无评论

Decentralized Federated Learning with Knowledge Distillation for Image Classification and Demand Forecasting in Industrial Chains 25th

Decentralized Federated Learning with Knowledge Distillatio...

引用

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

作者： Lin, Guanyu Ma, Ruikang Dong, De Liu, Dongning Song, Junteng Di, Kai Shenzhen Institute of Advanced Technology Chinese Academy of Sciences Guangdong Shenzhen China University of Chinese Academy of Sciences Beijing China Southern University of Science and Technology Guangdong Shenzhen China Guangdong University of Technology Guangdong Guangzhou China Southeast University Jiangsu Nanjing China

ISBN: (纸本)9789819642069

This study proposes a novel decentralized federated learning algorithm, DKFL, which combines knowledge distillation technology and has been successfully applied in the fields of image classification and demand forecasting in the industrial chain. This algorithm effectively improves the performance of the model through knowledge distillation, while retaining the privacy protection advantages of decentralized federated learning. In image classification tasks, our algorithm not only performs well on the CIFAR10 dataset, but also demonstrates significant improvement in classification accuracy on the automotive parts dataset in the automotive industry chain. In demand forecasting tasks, this algorithm was applied to the supply chain dataset of the industrial chain, achieving more accurate forecasting results. The experimental results show that the proposed method can effectively improve the generalization ability and prediction accuracy of the model while ensuring data privacy, providing new ideas and technical support for the promotion of federated learning in the application of the industry chain. © 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

Parallel Acceleration of Transportation Problem Solving Using SpMV in the Industrial Chain Context 25th

Parallel Acceleration of Transportation Problem Solving Usi...

引用

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

作者： Dong, De Lin, Guanyu Xu, Yicheng Ma, Ruikang Xia, Chenliang Fan, Jianping Li, Fuchong Southern University of Science and Technology Guangdong Shenzhen China Shenzhen Institute of Advanced Technology Chinese Academy of Sciences Guangdong Shenzhen China University of Chinese Academy of Sciences Beijing China Jinan Industrial Development Park Technology Development Co. Ltd. Shandong Jinan China

ISBN: (纸本)9789819642069

As modern industrial chains grow increasingly complex and time-sensitive, traditional transportation planning methods face efficiency bottlenecks. To address this, we propose a parallelization method based on Sparse Matrix-Vector Multiplication (SpMV) to accelerate the Transportation Simplex Algorithm (TSA) for large-scale transportation problems. Existing approaches primarily leverage data parallelism but underutilize GPU computational potential. This study transforms sequential algorithms into matrix-based representations, combining SpMV and parallel graph algorithms to enhance TSA performance. Key contributions include mapping performance bottlenecks—potential vector calculation and closed-loop search—onto SpMV operations, and converting branch logic into matrix operations to reduce divergence. Experiments on a 10000×10000 dataset demonstrate a 20.8x speedup for the parallelized MODI algorithm and a 28x overall speedup for solving the Transportation Problem, significantly improving efficiency. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Graph algorithms

来源：评论

学校读者我要写书评

暂无评论

A CNN_LSTM_KAN Based Genetic Algorithm for Photovoltaic Power Generation Revenue Prediction 25th

A CNN_LSTM_KAN Based Genetic Algorithm for Photovoltaic Pow...

引用

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

作者： Ma, Ruikang Lin, Guanyu Dong, De Zhou, Rong Fan, Jianping Duan, Keliang Zhang, Jun Shenzhen Institute of Advanced Technology Chinese Academy of Sciences Guangdong Shenzhen China University of Chinese Academy of Sciences Beijing China Southern University of Science and Technology Guangdong Shenzhen China National Supercomputing Center in Shenzhen Guangdong Shenzhen China Beijing JH Eco-Energy Technology Co. Ltd. Beijing100160 China Xinjiang Technical Institute of Physics and Chemistry Chinese Academy of Sciences Ürümqi China

ISBN: (纸本)9789819642069

In order to improve the economic benefits of photovoltaic power generation systems, accurate prediction of photovoltaic power generation revenue has become particularly important. However, traditional prediction algorithms such as CNN and LSTM suffer from overfitting issues, while the latest emerging KAN neural network also has problems with parameter tuning difficulties and sensitivity to data quality. Based on these issues, this paper proposes a CNN_LSTM_KAN photovoltaic power generation revenue prediction algorithm based on genetic algorithm. The experimental results show that the algorithm outperforms traditional methods in both prediction accuracy and robustness, providing an effective solution for predicting the revenue of photovoltaic power generation systems. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： genetic algorithm photovoltaics predictive algorithm

来源：评论

学校读者我要写书评

暂无评论

Perception-Centric Explainable AI: Bridging Cognitive Theories and HCI Design for Enhanced User Experience 16

Perception-Centric Explainable AI: Bridging Cognitive Theori...

引用

16th international conference on Ambient Systems, Networks and technologies Networks, ANT 2025 / 8th international conference on Emerging data and Industry 4.0, EDI40 2025

作者： Alhasan, Sara Alnanih, Reem Computer Science Department Faculty of Computing and Information Technology King Abdulaziz University Jeddah21589 Saudi Arabia

Artificial Intelligence (AI) systems increasingly influence high-stakes decision-making, necessitating explainability tailored to non-technical users. This research investigates integrating cognitive theories, Human-Computer Interaction (HCI) principles, and Explainable AI (XAI) techniques to enhance user perception, a core cognitive function. A perception-focused framework was developed and tested using a medical symptom checker tool. The study involved 20 participants divided into control and experimental groups. The experimental group used an enhanced tool with features like visual hierarchy and consistency, while the control group used a basic version with minimal explainability. Participants completed pre-test, testing, and post-test phases, including surveys and objective tasks measuring recognition and recall. Results showed that 90% of the experimental group achieved "Good Performance" in recognition tasks compared to 20% in the control group. Subjective feedback indicated significantly higher un-derstandability, with an average rating of 4.8 out of 5 for the enhanced tool versus 3.1 for the control. These findings underscore the effectiveness of combining HCI principles and cognitive theories, such as Gestalt and Feature Integration, in reducing cognitive load and improving clarity. This multidisciplinary approach advances the design of intuitive, user-centered AI systems, fostering trust and accessibility. © 2025 Elsevier B.V.. All rights reserved.

关键词： User centered design

来源：评论

学校读者我要写书评

暂无评论

Effectual Side Channel Attack Detection Using Convolutional Neural Network Optimized CMP-COA

Effectual Side Channel Attack Detection Using Convolutional ...

引用

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

作者： Prasath Vijayan Sudalaimuthu T Department of CSE Hindustan Institute of Technology and Science (Deemed to be University) Chennai India

ISBN: (数字)9798350356236

ISBN: (纸本)9798350356243

Smart phones are more vulnerable to malicious assaults because of technological advancements. An attack known as a side channel attack (SCA) in which attacker exploits the physical implementation of a cryptosystem to obtain confidential information. There are several existing works focused on side channel attack but lacks an accuracy and timely detection through important features. To resolve this issue, this paper proposes the novel technique intends to detect the side channel attack that includes phases of pre-processing, feature extraction and classification. Initially, the input data is pre-processed under data normalization and the statistical and higher order statistical features are extracted and are subjected to SCA classification using Optimal Convolutional Neural Network (OCNN). To make the prediction more precise and accurate, the weight of Optimal Convolutional Neural Network are optimized with hybrid Coronavirus Mask Protection and Coati Optimization Algorithm to improve the accuracy in detection of SCA. The proposed technique is implemented in python and the performance metrics such as accuracy, error rate, and execution time are evaluated. The proposed model shows that it has accuracy of 96% and the lowest execution time and error rate of 2.5 sec and 0.04 % which is far better when compared to the existing methods.

关键词： COVID-19 Accuracy Error analysis Side-channel attacks Feature extraction Prediction algorithms Convolutional neural networks Protection Optimization Smart phones

来源：评论

学校读者我要写书评

暂无评论

Cricket Shot Classification from Video Using Body Pose Landmarks

Cricket Shot Classification from Video Using Body Pose Landm...

引用

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

作者： Chava Govardhana Rao N Sai Harshith Varma Kashish K C Priyangshu Mazumder Prema Ramasamy Dept of Computer Science PES University Bengaluru India

ISBN: (数字)9798350356236

ISBN: (纸本)9798350356243

The primary focus of this study is to use deep learning techniques to classify cricket shots. data acquisition begins by gathering video clips of different cricket shots and manually annotating them. To address imbalance in class, generated synthetic examples are used to ensure each shot type has equal representation. Advanced techniques for handling missing data points using combined object detection and 3D landmark extraction to track the batsman's move-ments are employed for efficiency. To enhance accuracy of the analysis, complex methods are used to deal with missing data. By integrating object detection methods with 3D land-mark extraction, effective tracking of batsman movements is captured. Tests with multiple machine learning models such as simple neural networks and more complicated models which could capture movement sequence over time are tested on the data. The most successful results were achieved with systems that could process video frames in both forward and reverse directions, leading to a more precise identification of cricket shots. This research illustrates the potential of machine learning techniques and how advanced models can be used to analyze and classify sports activities in video data. We contribute to the growing community and knowledge base of automated sports analytics, paving the way for future innovations in real-time action recognition and commentary generation.

关键词： Deep learning Analytical models Technological innovation Solid modeling Three-dimensional displays Tracking Object detection Streaming media data models Sports

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 << < 10 11 12 13 14 15 16 17 18 19 > >>

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：