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

3,172 篇 会议
42 册 图书
25 篇 期刊文献

馆藏范围

3,239 篇 电子文献
0 种 纸本馆藏

日期分布

学科分类号

2,212 篇 工学
- 2,032 篇 计算机科学与技术...
- 1,327 篇 软件工程
- 418 篇 信息与通信工程
- 339 篇 电气工程
- 302 篇 控制科学与工程
- 153 篇 机械工程
- 128 篇 生物工程
- 124 篇 交通运输工程
- 116 篇 动力工程及工程热...
- 110 篇 生物医学工程（可授...
- 102 篇 安全科学与工程
- 81 篇 环境科学与工程（可...
- 72 篇 仪器科学与技术
- 70 篇 建筑学
- 67 篇 电子科学与技术（可...
675 篇 管理学
- 513 篇 管理科学与工程(可...
- 312 篇 工商管理
- 250 篇 图书情报与档案管...
498 篇 理学
- 244 篇 数学
- 138 篇 生物学
- 96 篇 统计学（可授理学、...
- 73 篇 系统科学
- 64 篇 物理学
152 篇 医学
- 142 篇 临床医学
- 132 篇 基础医学(可授医学...
- 76 篇 药学(可授医学、理...
- 75 篇 公共卫生与预防医...
138 篇 法学
- 105 篇 社会学
114 篇 经济学
- 113 篇 应用经济学
67 篇 教育学
- 67 篇 教育学
63 篇 农学
2 篇 文学
2 篇 军事学

主题

376 篇 big data
257 篇 internet of thin...
227 篇 cloud computing
133 篇 machine learning
129 篇 edge computing
123 篇 real-time system...
103 篇 data analytics
97 篇 artificial intel...
95 篇 smart cities
93 篇 intelligent sens...
84 篇 monitoring
81 篇 data models
79 篇 smart city
78 篇 data mining
74 篇 blockchain
71 篇 predictive analy...
64 篇 sensors
63 篇 deep learning
59 篇 iot
58 篇 security

机构

14 篇 jilin engineerin...
9 篇 hubei province k...
8 篇 school of comput...
8 篇 fujian provincia...
7 篇 institute for in...
7 篇 chitkara univers...
7 篇 liaoning jianzhu...
7 篇 school of econom...
6 篇 college of compu...
6 篇 fuzhou universit...
6 篇 symbiosis instit...
5 篇 china electric p...
5 篇 school of big da...
5 篇 luoyang normal u...
5 篇 smart agricultur...
5 篇 comsats univ isl...
5 篇 college of mecha...
5 篇 guangzhou colleg...
5 篇 electrical and i...
5 篇 university of ma...

作者

18 篇 javaid nadeem
9 篇 xu hongsheng
8 篇 leung carson k.
7 篇 zeng zeng
7 篇 xu xiaolong
7 篇 chang kuo-chi
7 篇 ramakrishnan ram...
6 篇 tang you
6 篇 doukovska lyubka
6 篇 wang wei
6 篇 cuzzocrea alfred...
5 篇 liu yang
5 篇 silva jesús
5 篇 vikrant bhateja
5 篇 fan ganglong
5 篇 vale zita
5 篇 qiu meikang
5 篇 cristea valentin
5 篇 stoyanov stanimi...
5 篇 wang yong

语言

3,182 篇 英文
46 篇 其他
20 篇 中文

检索条件"任意字段=International Conference on Intelligent and Smart Computing in Data Analytics, ISCDA 2020"

共 3239 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：

data analytics Using Machine Learning for Cyber Security Safeguards Individual Privacy

Data Analytics Using Machine Learning for Cyber Security Saf...

引用

2023 international conference on Innovative computing, intelligent Communication and smart Electrical Systems, ICSES 2023

作者： Sruthy, S. Ravindran, Zina Akhilkk Gouri, M.S. Waheeduddin Hussain, Mohammed Jothikumar, R. Kerala Palai India Baselios Mathews II College of Engineering Department of Computer Science and Artificial Intelligence Engineering Sasthamcotta690520 India Vimal Jyothi Engineering College Department of Computer Science and Design Chemperi India Baselios Mathews II College of Engineering Lake View Department of Computer Science and Engineering Kerala India Shadan College of Engineering and Technology Department of Information Technology Peerancheru Hyderabad India Shadan College of Engineering and Technology Department of Computer Science and Engineering Peerancheru Hyderabad India

ISBN: (纸本)9798350319200

The merging of data analytics and machine learning offers tremendous potential for boosting cyber security and protecting individual privacy in an age when personal data and cyber dangers are abundant. The purpose of this study was to create, test, and publish a model that takes into account this junction. Accuracy, precision, recall, F1-Score, and area under the receiver operating characteristic curve (AUC-ROC) are only a few of the indicators that show how well the framework can identify cyber threats. Further, the use of privacy-preserving methods like differential privacy highlights the moral need to guard sensitive information. Readers are given a concrete knowledge of the framework's real-world effect via vivid depictions of its practical use based on hypothetical data sets. This study serves as a helpful resource for a varied audience, from consumers worried about data privacy to organisations looking to better their cyber security defenses and legislators aiming to safeguard citizens' data. It also provides a springboard for further study in areas such as privacy enhancement, more sophisticated machine learning models, and sector-specific framework development. The digital ecosystem is always changing, but this study provides a guide for overcoming obstacles and capitalizing on possibilities at the intersection of cyber security and personal privacy. © 2023 IEEE.

关键词： Cyber Security Cyber Threat Detection data analytics Differential Privacy Digital Privacy Framework Development Individual Privacy Performance Metrics Privacy-Preserving Techniques User-Centric Security

来源：评论

学校读者我要写书评

暂无评论

The Intensive Model Design using FL for smart HC System Design 4

The Intensive Model Design using FL for Smart HC System Desi...

引用

4th IEEE international conference on Advance computing and Innovative Technologies in Engineering, ICACITE 2024

作者： Raman, Ramakrishnan Verma, Apurv Kumar, Vikram Rastogi, Shailesh Pillai, Biju G. Meenakshi, R. India Parul Institute of Technology Parul University Computer Science and Engineering Faculty of Engineering and Technology India Srv Media Pvt. Limited India India Sri Balaji University Faculty of Management It & Business Analytics Pune India Chennai Institute of Technology Computer Science and Engineering India

ISBN: (纸本)9798350360165

Using cutting-edge technology like wearables, internet access of Things, and smartphones, smart healthcare has become a crucial component of health policy services. This revolutionary method enables seamless connection and ongoing information access between patients, medical equipment, the facilities, allowing for intelligent responses to a variety of demands within the medical ecosystem. No matter when or where they are, patients may get urgent assistance, diagnostic services, and monitoring via the digital platform of the smart Health care Management Systems (SHMS). This research emphasizes innovation with direct healthcare services and suggests the use of the smart the management of healthcare Examination using Fuzzy Decision-Taking (SHME-FDM) technique to measure the effectiveness of technology integration. Furthermore, the Fuzzy Asymmetric Hierarchy Process-Technique for Orders of Preference by The sameness to Ideal Solution (Fuzzy AHP-TOPSIS) is used to evaluate the privacy protection and healthcare data inside the SHMS. In order to make predictions about healthcare, the research uses a fuzzy-based neural network. Through experimental analysis, reliability, accuracy, and error rates are evaluated. Notably, a security risk analysis highlights the proposed fuzzy model's potential for protecting healthcare data by demonstrating its improved risk assessment performance when compared to current methods. © 2024 IEEE.

关键词： Risk assessment

来源：评论

学校读者我要写书评

暂无评论

Analysis of Digital Twins Implementation in smart City using Big data and Deep Learning 7

Analysis of Digital Twins Implementation in Smart City using...

引用

7th international conference on intelligent computing and Control Systems, ICICCS 2023

作者： Nayak, Chinmaya Kumar Karunakaran, S. Yamunaa, P. Kayalvili, S. Tiwari, Mohit Unni, Manu Vasudevan Sri Sri University Faculty of Emerging Technologies Sri Sri Vihar Ward No - 3 Godi Sahi Odisha Barang754006 India Computer Technology Kongu Engineering College Erode Tamilnadu Perundurai India Peri Institue of Technology Department of EEE India Computer Science & Engineering Velalar College of Engineering and Technology Erode Tamil Nadu Thindal638012 India Computer Science and Engineering Bharati Vidy Ap Eeth's College of Engineering A-4 Rohtak Road Paschim Vihar Delhi110063 India St. Claret College P. O. Box 1355 MES Ring Rd Sharadhamba Nagar Jalahalli Karnataka Bengaluru560013 India

ISBN: (纸本)9798350397253

Digital twins are becoming more relevant for business and academic users due to advances in IoT, AI, and Big data. Due to global urbanization, pollution, public safety, traffic congestion, and other challenges have arisen. New technologies make cities smarter to keep up with growth. In the Internet of Things (IoT) age, many sensing devices acquire and/or produce a broad range of sensory data over long periods of time for a variety of businesses and applications. The use case determines the device's data stream volume and speed. The efficacy of the analytics process used to analyze these streams of data to learn, predict, and act determines IoT's worth as a business paradigm changer and quality-of-life technology. This study introduces Deep Learning (DL), a family of advanced machine learning techniques, to enhance IoT analytics and teaching. Introducing new results, challenges, and research opportunities. This study may assist academics and newbies comprehend how to use DL to smart cities. Analyzing and summarizing major IoT DL research initiatives. Check out smart IoT devices with DL embedded into their AI. Ultimately, the study will identify issues and suggest additional research. Each chapter concludes with experimental findings and the newest literature review. © 2023 IEEE.

关键词： smart city

来源：评论

学校读者我要写书评

暂无评论

A Demo of a Software Platform for Ubiquitous Big data Engineering, Visualization, and analytics, via Reconfigurable Micro-Services, in smart Factories 8

A Demo of a Software Platform for Ubiquitous Big Data Engine...

引用

8th IEEE international conference on smart computing (smartCOMP)

作者： Soderi, Mirco Kamath, Vignesh Breslin, John G. Natl Univ Ireland Data Sci Inst Galway Ireland

ISBN: (纸本)9781665481526

intelligent, smart, Cloud, reconfigurable manufacturing, and remote monitoring, all intersect in modern industry and mark the path toward more efficient, effective, and sustainable factories. Many obstacles are found along the path, including legacy machineries and technologies, security issues, and software that is often hard, slow, and expensive to adapt to face unforeseen challenges and needs in this fast-changing ecosystem. Lightweight, portable, loosely coupled, easily monitored, variegated software components, supporting Edge, Fog and Cloud computing, that can be (re)created, (re)configured and operated from remote through Web requests in a matter of milliseconds, and that rely on libraries of ready-to-use tasks also extendable from remote through sub-second Web requests, constitute a fertile technological ground on top of which fourth-generation industries can be built. In this demo it will be shown how starting from a completely virgin Docker Engine, it is possible to build, configure, destroy, rebuild, operate, exclusively from remote, exclusively via API calls, computation networks that are capable to (i) raise alerts based on configured thresholds or trained ML models, (ii) transform Big data streams, (iii) produce and persist Big datasets on the Cloud, (iv) train and persist ML models on the Cloud, (v) use trained models for one-shot or stream predictions, (vi) produce tabular visualizations, line plots, pie charts, histograms, at real-time, from Big data streams. Also, it will be shown how easily such computation networks can be upgraded with new functionalities at real-time, from remote, via API calls.

关键词： Software Platform Micro-service API Edge Fog Cloud Big data data Engineering data Visualization data analytics intelligent Manufacturing smart Manufacturing Reconfigurable Manufacturing Remote Monitoring

来源：评论

学校读者我要写书评

暂无评论

Greensense: IoT-Enabled smart Monitoring And Early Detection System For Optimal Plant Health In Greenhouse

Greensense: IoT-Enabled Smart Monitoring And Early Detection...

引用

2024 international conference on Advances in data Engineering and intelligent computing Systems, ADICS 2024

作者： Venkatesh, R. Aadhira, K.R. Kathiravan, M. Hindustan Institute Of Technology And Science Department Of Computer Science & Engineering Chennai India

ISBN: (纸本)9798350364828

The emergence of Agriculture 4.0 signifies a transformative shift in traditional farming practices, integrating cutting-edge technologies like IoT, machine learning, and robotics to support productivity and sustainability. This era leverages real-time data and automation for precision farming, predictive analytics, and resource optimization, crucial for addressing global food security challenges while minimizing environmental impact. GreenSense represents progress within Agriculture 4.0. It seeks to revolutionize greenhouse management by integrating IoT and advanced machine learning algorithms. Through sensors, actuators, and a Raspberry Pi 4 board, this system offers a comprehensive solution for monitoring and optimizing plant health in controlled environments. The motivation behind this system stems from the imperative to enhance agricultural practices sustainably in the face of population growth. By enabling real-time monitoring and swift anomaly detection through application, this paper empowers proactive intervention to mitigate risks and optimize growing conditions. Integration of the YOLOv5 algorithm with 97% accuracy enhances precision in leaf disease and pest detection using OpenCV, reducing crop losses effectively. Beyond greenhouse management, this paper contributes to advancing sustainable agriculture. Its scalable and adaptable nature promotes resource-efficient practices and environmental care. Finally, a user-friendly interface is tailored to facilitate efficient data collection from sensors, enabling comprehensive monitoring of crop conditions, including pest and disease detection. © 2024 IEEE.

关键词： Learning algorithms

来源：评论

学校读者我要写书评

暂无评论

Transitioning to smart Sustainable Cities Based on Cutting-Edge Technological Improvements

Transitioning to Smart Sustainable Cities Based on Cutting-E...

引用

29th international conference on Parallel and Distributed computing (Euro-Par)

作者： Andreou, Andreas Mavromoustakis, Constandinos X. Univ Nicosia Dept Comp Sci Nicosia Cyprus Univ Nicosia Res Fdn Nicosia Cyprus

ISBN: (纸本)9783031488023;9783031488030

A smart city is a concept that has been gaining momentum in recent years as cities worldwide seek to improve their efficiency, sustainability, and quality of life for their residents. smart cities are constructed atop smart data. Therefore, this research work focuses on the optimization of data acquisition, data sharing and data analysis. Aiming towards this evolution, the research elaborates on the advancement of smart healthcare, a novel approach for energy consumption, preparedness for a potential pandemic, innovative data encryption techniques, and vehicle-to-everything (V2X) connectivity to enable smart mobility. However, developing an intelligent ecosystem is paramount to providing citywide, reliable, high multi-Gbps peak data speeds with ultra-lowlatency. Hence, we finally focused our research on Unmanned Aerial Vehicles (UAV) assisted network optimization.

关键词： smart Cities UAV Healthcare Consumption V2X

来源：评论

学校读者我要写书评

暂无评论

SecSCS: A User-Centric Secure smart Camera System Based on Blockchain 44

SecSCS: A User-Centric Secure Smart Camera System Based on B...

引用

44th IEEE international conference on Distributed computing Systems (ICDCS)

作者： Qian, Xinyuan Li, Hongwei Wang, Haoyong Xu, Guowen Xu, Shengmin Ren, Ju Univ Elect Sci & Technol China Sch Comp Sci & Engn Chengdu Peoples R China Chongqing Key Lab Automated Reasoning & Cognit Chongqing Peoples R China City Univ Hong Kong Dept Comp Sci Hong Kong Peoples R China Fujian Normal Univ Coll Comp & Cyber Secur Fuzhou Peoples R China Tsinghua Univ Dept Comp Sci & Technol Beijing Peoples R China

ISBN: (纸本)9798350386066;9798350386059

smart cameras have gained immense popularity in commercial markets for their safety and security capabilities. Yet, the prevalent design of these intelligent camera systems often compels users to cede control of their data to potentially untrusted service providers, such as cloud services. This relinquishment can lead to unauthorized data access by these intermediaries, posing significant security and privacy risks. The conventional solutions have been to employ privacy-enhancing technologies to bypass these intermediaries, but at the cost of increased overhead for video streaming and sharing. In our study, we introduce SecSCS, a user-centric, blockchain-based secure camera system that incorporates essential features like video streaming, sharing, deletion, and permission restoration. SecSCS integrates a blockchain-enabled user login protocol with a secure device pairing mechanism that combines visual authorization with blockchain to flexibly manage the device ownership. We utilize blockchain to provide integrity protection for the video clips stored remotely, ensuring the video data remains tamper-proof. Furthermore, we present a video frame compression and a fast video encryption method aimed at boosting the efficiency of smart camera systems. Our evaluations show that, in comparison to the leading decentralized scheme, CaCTUs, SecSCS improves the computational and communication overhead for live streaming by a factor of 12.58 and 11.29, respectively, at a frame rate of 24 fps and a resolution of 720p.

关键词： smart camera system Privacy-preserving Video Encryption Access Control

来源：评论

学校读者我要写书评

暂无评论

smart Sensory Approach for Soil Health Tracking based Precision Farming 3

Smart Sensory Approach for Soil Health Tracking based Precis...

引用

3rd international conference on Innovative Mechanisms for Industry Applications, ICIMIA 2023

作者： Bhattacharyya, Avilasha Saini, Tanisha Sharma, Vandana Mishra, Sushruta Deemed to Be University Kalinga Institute of Industrial Technology India Department of Computational Sciences Delhi NCR India

ISBN: (纸本)9798350343632

Internet of Things (IoT) technology will have an impact on every area in the future as it will make everything intelligent, which will affect everyone's daily lives. It is a network composed of many devices that can configure themselves. The use of IoT in smart farming is transforming traditional agricultural practices by reducing crop loss, improving them, and making them more cost-effective for farmers. The study's goal is to propose a technological model for soil health monitoring that uses smart sensors and intelligent methods to communicate with farmers through a variety of channels. Farmers will benefit from the real-time farm data (temperature, humidity, soil moisture, UV index, and IR) that allows them to practice smart farming while increasing crop yields and conserving resources. © 2023 IEEE.

关键词： humidity Internet of Things Precision farming predictive analytics remote sensing Sensory computing

来源：评论

学校读者我要写书评

暂无评论

Real-Time Traffic Flow Optimization using Adaptive IoT and data analytics: A Novel DeepStreamNet Model 4

Real-Time Traffic Flow Optimization using Adaptive IoT and D...

引用

4th international conference on Sustainable Expert Systems, ICSES 2024

作者： Saranya, V.S. Subbarao, Garimidi Balakotaiah, Dega Bhavsingh, Maloth Babu, K. Suresh Dhanikonda, Srinivasa Rao School of Computing Srm Institute of Science and Technology Department of Computing Technologies Chennai603 203 India India Department of Computer Science and Engineering India Ashok: Womens Engineering College Department of Computer Science and Engineering Andhra Pradesh Kurnool India Department of Computer Science and Engineering A.P Narasaraopet India Department of Artificial Intelligence and Data Science Telangana Hyderabad India

ISBN: (纸本)9798331540364

Thisstudy introduces the DeepStreamNet model, an advanced framework for enhancing real-time traffic management in urban environments using adaptive IoT and sophisticated big data analytics. Central to our approach is the integration of convolutional neural networks (CNNs), recurrent neural networks (RNNs), and long short-term memory (LSTM) units, which synergize with IoT devices to facilitate dynamic adaptation to fluctuating traffic conditions. The model excels in operational performance, achieving a notable accuracy of 94.7% in congestion prediction with an exceptionally low latency of only 45 ms per decision cycle and the capability to process up to 50,000 data points per second. These technical achievements have marked significant improvements over traditional traffic management systems, enhancing traffic flow efficiency and reducing congestion effectively. The results underscore the transformative potential of the DeepStreamNet model in urban traffic management and public safety, offering actionable insights for intelligent transportation systems and setting the stage for more informed urban planning. Looking forward, we suggest extending the application of our model to areas such as logistics and broader smart city initiatives, highlighting its adaptability and broad utility in various urban contexts © 2024 IEEE.

关键词： Convolutional neural networks

来源：评论

学校读者我要写书评

暂无评论

IoT Based Soil Nutrient Monitoring and Analysis System 5

IoT Based Soil Nutrient Monitoring and Analysis System

引用

5th international conference on IoT Based Control Networks and intelligent Systems, ICICNIS 2024

作者： Sushma, Yarra Lakshmi, Ch Jaya Rajesh, Karra Hemanth, Vanamala Sowmyarao, Ventrapragada VR Siddhartha Engineering College Deemed to Be University Department of EIE A.P Vijayawada India

ISBN: (纸本)9798331518097

Traditional soil nutrient monitoring methods are time-consuming and inefficient, relying on manual sampling and delayed laboratory testing, which hinders timely interventions and leads to resource wastage in agricultural practices. This paper presents an IoT-based soil nutrient monitoring and analysis system designed to address these inefficiencies by enabling real-time data collection and analysis. The proposed system utilizes a network of advanced soil sensors that measure key parameters such as nitrogen, phosphorus, potassium (NPK), moisture, and pH levels. The data is wirelessly transmitted to a cloud platform for continuous processing and analysis, providing real-time insights into soil health. The innovation of this system lies in the integration of IoT sensors, cloud computing, and data analytics, which enables precise and timely decision-making for optimal soil management. Compared to recent soil monitoring systems that either lack real-time capabilities or require costly infrastructure, this IoT-based solution offers a more affordable, scalable, and efficient approach. By offering actionable insights, this system significantly improves crop management, reduces overuse of fertilizers, and enhances resource efficiency, ultimately leading to higher yields and more sustainable agricultural practices. © 2024 IEEE.

关键词： smart agriculture

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324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：