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

521 篇 会议
1 篇 期刊文献

馆藏范围

522 篇 电子文献
0 种 纸本馆藏

日期分布

学科分类号

110 篇 工学
- 72 篇 计算机科学与技术...
- 51 篇 软件工程
- 34 篇 建筑学
- 33 篇 土木工程
- 33 篇 测绘科学与技术
- 11 篇 电气工程
- 11 篇 控制科学与工程
- 9 篇 光学工程
- 8 篇 电子科学与技术（可...
- 8 篇 石油与天然气工程
- 7 篇 机械工程
- 7 篇 仪器科学与技术
- 7 篇 安全科学与工程
- 6 篇 信息与通信工程
- 5 篇 材料科学与工程（可...
- 4 篇 化学工程与技术
- 3 篇 动力工程及工程热...
44 篇 管理学
- 31 篇 管理科学与工程(可...
- 26 篇 工商管理
- 15 篇 图书情报与档案管...
29 篇 理学
- 13 篇 数学
- 11 篇 物理学
- 5 篇 化学
- 4 篇 统计学（可授理学、...
10 篇 经济学
- 10 篇 应用经济学
9 篇 法学
- 7 篇 社会学
8 篇 医学
- 8 篇 基础医学(可授医学...
- 8 篇 临床医学
- 8 篇 公共卫生与预防医...
3 篇 教育学
- 3 篇 教育学
2 篇 农学
1 篇 文学

主题

195 篇 visualization
155 篇 visual analytics
125 篇 accuracy
111 篇 data models
90 篇 real-time system...
69 篇 feature extracti...
65 篇 training
63 篇 data visualizati...
57 篇 deep learning
56 篇 speech processin...
47 篇 signal processin...
45 篇 computational mo...
45 篇 convolutional ne...
44 篇 predictive model...
38 篇 adaptation model...
37 篇 analytical model...
35 篇 transformers
32 篇 semantics
31 篇 robustness
30 篇 scalability

机构

5 篇 department of el...
4 篇 symbiosis instit...
4 篇 department of bi...
3 篇 department of co...
3 篇 hindustan instit...
3 篇 rajalakshmi engi...
3 篇 school of comput...
3 篇 department of el...
3 篇 department of it...
3 篇 saveetha school ...
3 篇 department of el...
3 篇 saveetha school ...
2 篇 department of co...
2 篇 faculty of compu...
2 篇 shanghai jiao to...
2 篇 department of co...
2 篇 department of co...
2 篇 nagpur campus pu...
2 篇 department of in...
2 篇 department of co...

作者

7 篇 n. mohankumar
5 篇 r. sathya
5 篇 m. rajmohan
4 篇 asha sundaram
4 篇 p kumar
3 篇 l.n. jayanthi
3 篇 senthil pandi s.
3 篇 k. karthikeyan
3 篇 arpana prasad
3 篇 v asha
3 篇 rajmohan m.
3 篇 mohankumar n.
3 篇 t. r. ganeshbabu
2 篇 s. muthumarilaks...
2 篇 chuan-xian ren
2 篇 jose anand a.
2 篇 b. lavaraju
2 篇 jing zhang
2 篇 vamsilala purush...
2 篇 kumar p.

语言

429 篇 英文
93 篇 其他
10 篇 中文

检索条件"任意字段=2025 International Conference on Visual Analytics and Data Visualization, ICVADV 2025"

共 522 条记录，以下是141-150 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：

GPS and IoT-Based Zone-Specific Vehicle Speed Control System

GPS and IoT-Based Zone-Specific Vehicle Speed Control System

引用

visual analytics and data visualization (icvadv), international conference on

作者： Prakash N B Vinslet Mercy J Gopika G Meruthula M K P.Samuel Pakianathan Bindhu A Department of EEE National Engineering College Kovilpatti Tamilnadu

ISBN: (数字)9798331521394

ISBN: (纸本)9798331521400

Two of the biggest issues of contemporary transportation systems are road safety and noise pollution. Pedestrians and the environment are seriously endangered by speeding cars and excessive honking in sensitive places, such as school zones, hospitals, and accident-prone areas. This project presents a Zone-Based Vehicle Speed Control and Horn Control System Using Arduino and IoT to address these issues. This system tracks vehicle movement and enforces predetermined traffic laws by integrating a GPS module, Arduino microcontroller, motor driver, buzzer, and LCD. The device eliminates the need for driver compliance by automatically lowering speed and turning off the horn in no-horn zones when a car reaches a restricted area. Additionally, there is a toggle switch for manual override in an emergency. Traffic laws are enforced dynamically thanks to real-time monitoring and changes made possible by IoT technology. This technology improves traffic discipline, prevents noise pollution, and lowers accidents by automating speed and horn regulation. This project lays the groundwork for the next developments in intelligent traffic management systems and smart transportation because of its scalable and reasonably priced architecture.

关键词： Pollution Microcontrollers visual analytics Velocity control Noise Turning Liquid crystal displays Automobiles Vehicles Global Positioning System

来源：评论

学校读者我要写书评

暂无评论

Contextual Aligned Tamil Sign Language Retrieval System with Semantic Masked Transformer

Contextual Aligned Tamil Sign Language Retrieval System with...

引用

visual analytics and data visualization (icvadv), international conference on

作者： S Thillai Sivakavi R I Minu Department of Computer Science and Engineering SRM Institute of Science and Technology Kattankulathur India

ISBN: (数字)9798331521394

ISBN: (纸本)9798331521400

The sign language retrieval system, while similar to conventional video retrieval systems, faces distinct challenges that require a thorough understanding of the meanings conveyed through human actions depicted in the videos. Typically, meaningful information is extracted using RGB feature extraction techniques. However, this method can lead to redundancy, as it often fails to capture the global contextual information inherent in each video frame. Additionally, the reliance on RGB features can present significant memory challenges due to the large data requirements associated with processing and storing this information. Consequently, a more efficient approach is necessary to enhance both the accuracy and effectiveness of sign language retrieval. To address these issues, we have implemented a semantic masked transformer architecture specifically tailored for the sign language retrieval task. This innovative system not only incorporates RGB features but also integrates pose features, which are derived from the movements and positions of the signer. By fusing these two types of features based on their similarity, the system can provide a more refined and pertinent retrieval of textual information related to the video frames. Our extensive experiments conducted on a custom dataset designed for Tamil Sign Language demonstrate that this framework significantly outperforms current state-of-the-art methods. These results underscore the effectiveness of combining semantic understanding with advanced feature extraction techniques, ultimately leading to improved accuracy and efficiency in sign language retrieval.

关键词： Training Sign language Accuracy visual analytics Semantics Redundancy Assistive technologies Feature extraction Transformers Faces

来源：评论

学校读者我要写书评

暂无评论

Real Time Adaptive Routing for Efficient Urban Mobility

Real Time Adaptive Routing for Efficient Urban Mobility

引用

visual analytics and data visualization (icvadv), international conference on

作者： I. Karthika D. Pushpalatha Infant Hilda D Dheenadhayalan S Mukilan K Hariprasaath S Department of Computer Science and Engineering M Kumarasamy college of engineering Karur India Department of Electronics and Communications Engineering M Kumarasamy college of engineering Karur India

ISBN: (数字)9798331521394

ISBN: (纸本)9798331521400

Urban mobility faces growing challenges due to the inefficiencies of traditional public transportation systems, which rely on fixed schedules and routes. These systems struggle to meet dynamic passenger demands, resulting in overcrowding during peak times and underutilization during off-peak periods. Variable passenger demand frequently results in inefficiencies in public transportation networks, which create crowding during rush hours and underutilization during off-peak hours. The proposed system offers a Smart Ticket Scheduling System that uses real-time crowd data to dynamically schedule and distribute tickets in order to overcome these difficulties. Using sensors, cameras, and mobile network data, the system tracks the number of passengers at different locations by utilizing technologies like IoT, AI, and advanced analytics. By controlling ticket availability and managing passenger flow, this data ensures that commuters are distributed among buses and other public transportation options as efficiently as possible. Additionally, the technology modifies bus routes and schedules in real-time to meet changes in demand, which eases traffic and enhances the entire travel experience.

关键词： Schedules data integration Pricing Dynamic scheduling Real-time systems Complexity theory Resource management Internet of Things Artificial intelligence Public transportation

来源：评论

学校读者我要写书评

暂无评论

Optimizing Air Pollution Prediction in Urban Environments using a Hybrid RNN-PBO Model with IoT data

Optimizing Air Pollution Prediction in Urban Environments us...

引用

visual analytics and data visualization (icvadv), international conference on

作者： Prajul Mohandas Subramanian P Surendran R Department of Computer Science and Engineering Saveetha School of Engineering Saveetha Institute of Medical and Technical Sciences Chennai India Department of Computer Science and Engineering Saveetha School of Engineering Saveetha Institute of Medical and Technical Sciences Chennai Tamil Nadu India

ISBN: (数字)9798331521394

ISBN: (纸本)9798331521400

This research study proposes a novel hybrid model based on Recurrent Neural Network (RNN) combinatorial with Polar Bear Optimization (PBO) to improve air pollution prediction and control measures over cities. The model aims at learning the temporal relationships and interdependence among air-quality data. To implement the model styled with real-time Internet of Things (IoT) sensor data, tracking pollutants and other environmental factors in the urban region of study, the sequential nature of the RNNs allows it to build model patterns yet has a slow convergence and local minima when learning. To address this challenge, the PBO algorithm is introduced to optimize the parameter weight of the RNN, thus enhancing learning capacity and prediction accuracy. The exploration and exploitation of the PBO allows an effective mechanism of saving time with fast convergence and better process of complex data. The hybrid method was validated on an actual urban data set, giving improved prediction accuracy and stability over traditional RNNsand other optimization schemes. The proposed model aspires to deliver an efficient and trustworthy methodology for real-time air quality forecasting smart city management and a healthier city.

关键词： Recurrent neural networks Accuracy Atmospheric modeling Predictive models Air pollution Prediction algorithms data models Real-time systems Optimization Convergence

来源：评论

学校读者我要写书评

暂无评论

database Theory in Action: database visualization 28

Database Theory in Action: Database Visualization

引用

28th international conference on database Theory, ICDT 2025

作者： Wu, Eugene Columbia University New YorkNY United States

We draw a connection between data modeling and visualization, namely that a visualization specification defines a mapping from database constraints to visual representations of those constraints. We show data modeling... 详细信息

ISBN: (纸本)9783959773645

关键词： data visualization

来源：评论

学校读者我要写书评

暂无评论

Personalized Content-based Movie Recommendation System: A Comparative Analysis

Personalized Content-based Movie Recommendation System: A Co...

引用

visual analytics and data visualization (icvadv), international conference on

作者： B Nithya Asha V Sreeja S P Abhay Aditya Sinha Akash P Akshay Bharadwaj S Department of Master of Computer Applications New Horizon College of Engineering Bengaluru India

ISBN: (数字)9798331521394

ISBN: (纸本)9798331521400

A recommendation system is an analytical tool designed to provide personalized suggestions to users for specific resources such as literature, films, or music, derived from a comprehensive dataset. Movie recommendation systems aim to predict movies a user might enjoy based on attributes of previously liked movies. These systems are particularly advantageous for organizations that manage data from extensive customer bases and seek to deliver optimal suggestions. Factors such as genre, cast, and filmmakers significantly influence recommendations, which may be based on a single attribute or a combination of features. This paper focuses on a genre-based recommendation system employing content-based filtering to cater to user preferences. Using Python, the design tools algorithms like Cosine Similarity, Jaccard Similarity, and Pearson Correlation on a large dataset to identify patterns and preferences eIectively. Through a detailed evaluation of these approaches, the system provides robust and applicable movie suggestions. By smoothing user-friendly navigation and aligning recommendations with user interests, the system enhances user engagement and satisfaction. Also, this study examines the strengths and limitations of the applied algorithms, emphasizing the implicit for combining multiple similarity measures to enhance accuracy. The findings emphasize the significance of substantiated content delivery in optimizing user experience.

关键词： Technological innovation Correlation Smoothing methods Sensitivity Filtering visual analytics Motion pictures Vectors User experience Recommender systems

来源：评论

学校读者我要写书评

暂无评论

Explainable AI-Driven Heart Disease Prediction

Explainable AI-Driven Heart Disease Prediction

引用

visual analytics and data visualization (icvadv), international conference on

作者： R Bhuvaneswari P Kumar S Kaviya Department of Computer Science and Engineering Rajalakshmi Engineering College Chennai India

ISBN: (数字)9798331521394

ISBN: (纸本)9798331521400

The earliest detection is crucial both to prevention and treatment of heart disease, which ranks highly in the list of worldwide health concerns. data gathering and processing are performed as the initial phase through several health indicators such as blood pressure, cholesterol, and lifestyle factors. All the inputs are processed and computed with the chances of suffering heart disease using a state-of-art model in machine learning. From, this the best performed machine learning model are integrated in the proposed methodology which results in the better accuracy with 83.9%. For the second step, with the help of explainable AI approaches, relevant elements for each prediction of the model are highlighted. Since the performance of the model is assessed in terms of the interpretation and accuracy of its predictions, the third phase comes as the final one, to deliver medical practitioners with an accurate tool that can be put to use for an early diagnosis and helpful insight. The main objective of our approach is to make EAI models in the health care sector more transparent and user-friendly. LIME (Local Interpretable Model-agnostic Explanations) is a popular method in Explainable Artificial Intelligence (EAI) that has been utilized in the proposed work since it interprets complex machine learning models by highlighting the most significant features contributing to a prediction. In the proposed method, LIME provides insights into the features influencing the model's output, such as whether a patient is likely to have heart disease along with the features which contribute to that prediction.

关键词： Heart Accuracy Explainable AI Computational modeling visual analytics Medical services Predictive models Medical diagnostic imaging Tuning Diseases

来源：评论

学校读者我要写书评

暂无评论

Decoding Cyber Identity Theft Through the Innovative ShieldCyNet Framework

Decoding Cyber Identity Theft Through the Innovative ShieldC...

引用

visual analytics and data visualization (icvadv), international conference on

作者： A. Sivanandam B. Lavaraju Asha Sundaram Saveetha School of Law Saveetha Institute of Medical and Technical Sciences (SIMATS) Chennai Saveetha School of Law Saveetha Institute of Medical and Technical Sciences (SIMATS) Chennai Tamil Nadu India

ISBN: (数字)9798331521394

ISBN: (纸本)9798331521400

Cyber identity theft is a pressing concern, particularly in regions like Tamil Nadu, where increasing digital adoption has heightened vulnerabilities. This study introduces the ShieldCyNet framework, a modular and scalable solution for detecting, mitigating, and responding to identity theft incidents. Leveraging machine learning models, including Neural Networks, Random Forests, and XGBoost, the framework achieved remarkable accuracy in threat detection and classification. Neural Networks outperformed other models with an accuracy of 96.5%, precision of 95.8%, recall of 96.0%, and an F1-score of 95.9%. The framework's performance was further validated through metrics like false positives (2.1%) and false negatives (1.8%) for Neural Networks. Additionally, the system's localized design incorporated multilingual support and culturally relevant features, receiving a user satisfaction score of 92% and ease-of-use rating of 9/10. The ShieldCyNet framework demonstrated robust capabilities in identifying patterns such as phishing (45% of attacks) and credential stuffing (25%), which are prevalent in Tamil Nadu. The study concludes that ShieldCyNet is not only effective in addressing existing threats but also scalable for broader applications. Future improvements will focus on integrating blockchain for enhanced security and expanding awareness programs for rural areas.

关键词： Measurement Accuracy Identity theft Phishing visual analytics Neural networks Pressing Threat assessment Multilingual Random forests

来源：评论

学校读者我要写书评

暂无评论

Machine Learning-Based Cardiovascular Disease Prediction: A Comparative Analysis of Classification Algorithms for Enhanced Diagnostic Accuracy

Machine Learning-Based Cardiovascular Disease Prediction: A ...

引用

visual analytics and data visualization (icvadv), international conference on

作者： Harsheeta Singh Vanshaj Satija Priyadharshini K Department of Computing Technologies SRM Institute of Science and Technology Kattankulathar Chennai

ISBN: (数字)9798331521394

ISBN: (纸本)9798331521400

Cardiovascular diseases (CVDs) were one of the major causes of death in all the continent, to such an extent that early detection and accurate diagnosis of CVDs is crucial to the early intervention. The aim of this research is to predict the likely hood of a heart related condition based on ML techniques in order to increase diagnostic precision. To develop predictive models, a dataset of 383 patient records along with 13 key attributes such as age, cholesterol levels, blood pressure, heart rate was used. The implementation of various ML algorithms like Support Vector Machine (SVM), K-Nearest Neighbors (KNN), Decision Tree, Random Forest, Naïve Bayes, and Logistic Regression in Python was done with the help of Jupyter Notebook environment. And the study focuses on data preprocessing, feature selection, and algorithm performance evaluation by means of accuracy, precision, recall, and F1-score. SVM was found to be the model with the highest accuracy of 86% on the tested models, which shows its ability to cope with the complexity of clinical data. In consequence, it also emphasizes the promise of ML driven predictive systems for timely, data driven decision support in the clinical setting, and in so doing, improves patient outcomes.

关键词： Support vector machines Logistic regression Accuracy Nearest neighbor methods Prediction algorithms data models Bayes methods Decision trees Cardiovascular diseases Random forests

来源：评论

学校读者我要写书评

暂无评论

Distributed Intrusion Detection System using Kafka and Spark Streaming

Distributed Intrusion Detection System using Kafka and Spark...

引用

visual analytics and data visualization (icvadv), international conference on

作者： Kotyada Mohan Kiran Kumar M. Vivek Srikar Reddy Karthik Ullas Supriya M. Dept. of Computer Science and Engineering Amrita School of Computing Bengaluru India

ISBN: (数字)9798331521394

ISBN: (纸本)9798331521400

Intrusion Detection Systems (IDS) are critical for identifying and mitigating potential security threats within network traffic. However, traditional IDS solutions often struggle with scalability and real-time threat detection, particularly in high-volume, high-velocity environments. The proposed work introduces a scalable and efficient IDS that leverages Apache Kafka and Apache Spark to address these challenges. Kafka's robust streaming platform ensures reliable, low-latency data flow, while Apache Spark's parallelized machine learning algorithms (MLlib) enable rapid and accurate classification of network traffic. By combining Kafka's data handling capabilities with Spark's processing efficiency, the proposed system provides fast, adaptive threat detection in real- time. This approach not only enhances IDS performance but also sets the stage for future developments in scalable, distributed IDS solutions. The work demonstrates the potential of big data technologies to improve network security in complex and dynamic network environments.

关键词： Computational modeling Intrusion detection Cluster computing Telecommunication traffic Big data Network security Threat assessment Real-time systems data models Low latency communication

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53页 << < 11 12 13 14 15 16 17 18 19 20 > >>

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：