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

34,472 篇 会议
5,302 篇 期刊文献
271 册 图书

馆藏范围

40,045 篇 电子文献
0 种 纸本馆藏

日期分布

学科分类号

24,642 篇 工学
- 17,640 篇 计算机科学与技术...
- 14,781 篇 软件工程
- 6,533 篇 信息与通信工程
- 3,970 篇 控制科学与工程
- 3,047 篇 电子科学与技术（可...
- 2,862 篇 电气工程
- 2,639 篇 生物工程
- 2,128 篇 生物医学工程（可授...
- 1,695 篇 光学工程
- 1,620 篇 机械工程
- 1,486 篇 仪器科学与技术
- 1,366 篇 动力工程及工程热...
- 1,107 篇 化学工程与技术
- 981 篇 安全科学与工程
- 812 篇 交通运输工程
- 742 篇 网络空间安全
12,340 篇 理学
- 6,606 篇 数学
- 3,354 篇 物理学
- 2,897 篇 生物学
- 2,193 篇 统计学（可授理学、...
- 1,535 篇 系统科学
- 1,182 篇 化学
6,432 篇 管理学
- 3,826 篇 管理科学与工程(可...
- 2,921 篇 图书情报与档案管...
- 2,006 篇 工商管理
1,862 篇 医学
- 1,595 篇 临床医学
- 1,482 篇 基础医学(可授医学...
- 954 篇 药学(可授医学、理...
- 803 篇 公共卫生与预防医...
1,206 篇 法学
- 979 篇 社会学
734 篇 经济学
569 篇 农学
496 篇 教育学
186 篇 文学
96 篇 军事学
61 篇 艺术学
1 篇 哲学

主题

1,315 篇 accuracy
1,003 篇 feature extracti...
985 篇 computational mo...
876 篇 deep learning
818 篇 training
783 篇 computer science
678 篇 real-time system...
637 篇 machine learning
624 篇 support vector m...
563 篇 predictive model...
501 篇 internet of thin...
488 篇 convolutional ne...
448 篇 data models
394 篇 reliability
353 篇 data mining
347 篇 optimization
338 篇 computer archite...
325 篇 artificial intel...
312 篇 routing
307 篇 wireless sensor ...

机构

82 篇 north-west unive...
82 篇 institut univers...
79 篇 infn sezione di ...
79 篇 national centre ...
77 篇 institute of inf...
76 篇 infn sezione di ...
66 篇 università di ca...
66 篇 tno technical sc...
59 篇 dept. of informa...
58 篇 université de st...
56 篇 dept. of compute...
53 篇 dept. of informa...
52 篇 school of automa...
49 篇 leiden universit...
48 篇 dept. of compute...
45 篇 dept. of compute...
44 篇 dept. of compute...
43 篇 in2p3 lpc campus...
42 篇 infn lnf via enr...
42 篇 nikhef national ...

作者

85 篇 ferrara g.
85 篇 ardid m.
84 篇 calvo d.
83 篇 gal t.
83 篇 bozza c.
81 篇 chen a.
80 篇 kalekin o.
76 篇 díaz a.f.
73 篇 boumaaza j.
70 篇 coleiro a.
69 篇 huang f.
67 篇 gozzini s.r.
54 篇 dallier r.
53 篇 kulikovskiy v.
51 篇 anguita m.
42 篇 benoit d.m.
42 篇 eddymaoui a.
42 篇 labalme m.
41 篇 gagliardini s.
40 篇 del burgo r.

语言

35,694 篇 英文
3,898 篇 其他
356 篇 中文
54 篇 日文
48 篇 朝鲜文
2 篇 德文
2 篇 斯洛文尼亚文
1 篇 法文
1 篇 葡萄牙文

检索条件"机构=Dept.of Computer Engineering and Computer Science"

共 40045 条记录，以下是851-860 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：

Intelligent IoT Platform for Real-Time Monitoring of Indoor Air Quality in Healthcare Facilities 12

Intelligent IoT Platform for Real-Time Monitoring of Indoor ...

引用

12th International Conference on Orange Technology, ICOT 2024

作者： Cheng, Yin-Ting Dept. Computer Science and Information Engineering SHU-TE University Kaohsiung Taiwan

ISBN: (纸本)9798331523602

In recent years, people have been confronted with unprecedented emerging infectious diseases. Medical institutions typically manage high-risk infectious diseases, which are transmitted via droplets or airborne routes, by using negative pressure isolation rooms to house patients and provide medical care. These isolation areas and rooms are specially designed to effectively prevent the spread of pathogens, with the goal of protecting healthcare personnel and preventing large-scale hospital-acquired infections. As most medical institutions have already completed the installation of hardware, wired network construction is not ideal for hospital environments, as it would require modifications to existing infrastructure, indirectly affecting the quality of the hospital environment, such as noise from construction and the layout of piping systems. Therefore, this study proposes an "Intelligent IoT Platform for Real-Time Monitoring of Indoor Air Quality in Healthcare Institutions." The system leverages smart sensors integrated with the Internet of Things (IoT), utilizing the small size and ease of deployment of the sensors as part of the overall technical framework. The platform also incorporates health and safety indicators relevant to hospital hygiene, enabling the monitoring of various environmental factors to ensure the safety of healthcare personnel. © 2024 IEEE.

关键词： Indoor air pollution

来源：评论

学校读者我要写书评

暂无评论

Career Craft AI: A Personalized Resume Analysis and Job Recommendations System 1

Career Craft AI: A Personalized Resume Analysis and Job Reco...

引用

1st International Conference on Innovative Sustainable Technologies for Energy, Mechatronics and Smart Systems, ISTEMS 2024

作者： Rajput, Akshay Dubey, Akanksha Thakur, Rishabh Singh, Deepak Singh, Upendra Pratap Graphic Era Deeemed to Be University Dept. of Computer Science and Engineering Dehradun India

ISBN: (纸本)9798350384246

In the today's era of endless career options, the challenge to get that one ideal job that aligns best with individual's skills and interests is absent due to lack of personalized recommendations and lack of guidance about resume making it becomes challenging to find best jobs and get shortlisted for the hiring process of a company. This paper introduces a novel approach to address these challenges by the development of a Career Crafter AI - A Resume analysis and Job Recommendation System. Knowing the limitations of existing recommendations systems that primarily rely on individuals provided interests, our system, implemented on the e-learning platform for skill building, Level Up, goes beyond the traditional approach of recommendation system. Using Vector Machine algorithm and the cosine similarity our system classifies the users based on their skills and profile mentioned on the platform and Natural Language Processing enables to provide the tips and recommendation to improve our resume and get the insights about the user for better recommendation. The recommendation engine utilizes these insights to provide accurate and best fit jobs to the users and as well as provide potential candidate for job roles to the recruiters This research paper aims to provide a one stop destination for learners to improve their resume for getting an edge during shortlisting and interviews and to transform and optimize the job recommendation systems by offering a more personalized and effective approach, empowering individuals to navigate their career paths with confidence and precision. © 2024 IEEE.

关键词： Support vector machines

来源：评论

学校读者我要写书评

暂无评论

A Comparative Exploration of Machine Learning and Graph Deep Learning Models for Discriminatory Speech Detection 2

A Comparative Exploration of Machine Learning and Graph Deep...

引用

2nd International Conference on Advancement in Computation and computer Technologies, InCACCT 2024

作者： Kavya, J. Pragathy Reddy, K.N. Maddipatla, Phanindra Kesanapalli, Anjali Arya, Arti PES University Dept. of Computer Science Engineering Karnataka Bengaluru560100 India

ISBN: (纸本)9798350371314

In an era marked by digital expansion, discriminatory speech remains a widespread concern, exerting significant societal implications. This study presents an overview of discriminatory speech detection techniques and explores the complexities involved in identifying discriminatory speech by utilizing a variety of datasets from various fields. The importance of preprocessing methods and feature engineering is next examined, opening the door for more in-depth study. Furthermore, the paper delves into traditional Machine Learning (ML) algorithms and state-of-the-art Deep Learning (DL) models along with a crucial component of using graph-based structures with Natural Language Processing (NLP) techniques and the use of graphs to extract contextual information. Using both graphs and NLP algorithms enhances the identification process by uncovering contextual connections within textual data. © 2024 IEEE.

关键词： Speech recognition

来源：评论

学校读者我要写书评

暂无评论

A Novel Approach for Single-Shot Target Recognition by Matching Graph of Feature Pixels 2

A Novel Approach for Single-Shot Target Recognition by Match...

引用

2nd International Conference on Machine Learning and Data engineering, ICMLDE 2023

作者： Mitra, Baldivya Deshmukh, Maroti Kumar, Abhimanyu Dept. of Computer Science & Engineering National Institute of Technology Uttarakhand 246174 India

Image feature extraction and matching constitute fundamental steps in computer vision and image analysis, enabling various applications ranging from object recognition to scene reconstruction. Object recognition is one of the major applications of artificial intelligence. Since last two decades, different techniques for object recognition were given by researchers from across the world. This paper presents a novel approach for automatic target recognition in autonomous weapons by matching connected graph of feature pixels. The Moving and Stationary Target Acquisition and Recognition (MSTAR) is taken for experimental purpose. The Proposed model has three stages for a target recognition;Image Denoising, Feature extraction & graph generation, and feature matching. Firstly, a sample image of targets taken from the MSTAR is taken as an input. Further, input sample is de-noised and features are extracted using Speeded-Up Robust Features (SURF) algorithm. Thereafter, a graph is created using feature pixels and this complete process is repeated with test image. Further, both graphs are compared using a proposed feature graph matching algorithm which results an recognition accuracy score. Proposed model is tested over the MSTAR dataset and it resulted in varying accuracy at different feature matching thresholds. © 2024 Elsevier B.V.. All rights reserved.

关键词： Synthetic aperture radar

来源：评论

学校读者我要写书评

暂无评论

Unsupervised Insider Threat Detection Using Multi-Head Self-Attention Mechanisms 4

Unsupervised Insider Threat Detection Using Multi-Head Self-...

引用

4th Intelligent Cybersecurity Conference, ICSC 2024

作者： Bertrand, Simon Germain, Pascal Tawbi, Nadia Laval University Dept. of Computer Science & Software Engineering Québec Canada

ISBN: (纸本)9798350354775

We propose an unsupervised insider threat detection system that learns normal user behaviors through audit data using neural networks equipped with multi-head self-attention mechanisms. The attention mechanisms learn precise normal user behaviors using large event windows. The key idea is to consider a sequence abnormal when it exhibits some events that are not likely to happen given the preceding events sequence. In addition, our method provides insights into detected threats through an event-based scoring system to facilitate threat understanding by security experts. Furthermore, the proposed solution does not require intensive audit logs pre-processing, such as manual domain knowledge-rich features extraction and data balancing. Thus, the proposed approach is easy to implement and use across organizations regardless of their expertise level. The proposed solution also provides the ability to detect threats in real-time. On the benchmark dataset CERT version 4.2, our solution, combined with hyperparameter search by Bayesian optimization, outperforms the previous state-of-the-art approaches with an area under the ROC curve of 97.23%, a recall of 91.51%, an accuracy of 93.13% and a false positive rate of 6.8%. © 2024 IEEE.

关键词： Deep neural networks

来源：评论

学校读者我要写书评

暂无评论

MAD: A Meta-Learning Approach to Detect Advanced Persistent Threats using Provenance Data in Industrial IoT 40

MAD: A Meta-Learning Approach to Detect Advanced Persistent ...

引用

40th Annual computer Security Applications Conference Workshops, ACSACW 2024

作者： Saha, Bikash Rani, Nanda Shukla, Sandeep Kumar Indian Institute of Technology Kanpur Dept. of Computer Science and Engineering Kanpur India

ISBN: (纸本)9798331532819

The increasing reliance on Industrial Internet of Things (IIoT) systems in critical infrastructure has made these environments prime targets for stealthy and prolonged Advanced Persistent Threats (APTs) that evade traditional security systems. This study introduces MAD (Meta-learning based APT Detection), a novel framework designed to detect APTs in IIoT environments by leveraging provenance data. This data provides a detailed view of system-level interactions, capturing subtle and persistent malicious behaviors. We evaluate MAD on the CICAPT-IIoT dataset, which simulates real-world APT scenarios with severe class imbalance due to the "low and slow"nature of APT attacks. MAD includes two variants: MAD v1, utilizing a multi-layer perceptron (MLP), and MAD v2, employing Model-Agnostic Meta-Learning (MAML) to improve detection of rare attack behaviors. MAD v1 achieves F1-score of 0.91 and outperforms the existing baselines. MAD v2 achieves F1-score of 0.95 surpassess existing baselines as well as MAD v1, which demonstrates its enhanced capability to detect rare APT activities despite the dominance of benign samples. This work combines provenance-based detection with meta-learning to address class imbalance and enhance APT detection in IIoT, demonstrating MAD's potential in tackling emerging IIoT security challenges. © 2024 IEEE.

关键词： Industrial internet of things (IIoT)

来源：评论

学校读者我要写书评

暂无评论

Smart Healthcare - IoT and Artificial Neural Network(ANN) 15

Smart Healthcare - IoT and Artificial Neural Network(ANN)

引用

15th International Conference on Computing Communication and Networking Technologies, ICCCNT 2024

作者： Sutar, Laxmikanta Chinara, Suchismita National Institute of Technology Rourkela Dept. of Computer Science and Engineering Rourkela India

ISBN: (纸本)9798350370249

With the use of the Internet of Medical Things (IoMT), the growing accessibility of wearable devices, and the continual reduction in the cost of sensor-based technologies and green computing, internet-connected sensors allow users to track, analyze, and share welfare information employing a cloud-based platform. Artificial Neural Networks (ANN) find extensive use across various applications, including healthcare systems, drawing inspiration from the biological concept of neurons. This study explores the prediction of heart attack risks using a combination of Internet of Things (IoT) sensors and artificial neural networks (ANN). Through the integration of IoT sensors such as the pulse sensor and LM35 temperature sensor, essential physiological data related to heart rate and body temperature was collected. An ANN model was developed, focusing on predictive capabilities using the sigmoid function, feedforward and backpropagation techniques, and random weight initialization. The investigation further utilized Keras with TensorFlow and optimized model parameters using Adam Optimization and Later with One Hot Encoding plus a Genetic Algorithm (GA). Additionally, the study involved training neural networks on higher-quality UCI datasets to evaluate performance. Scatterplots were generated to visualize relationships between variables. Results demonstrated promising performance improvements, with the model achieving close to 90% accuracy on the testing dataset. Encoding techniques were employed to handle categorical variables effectively, contributing to the model's robustness and generalization. Overall, this research offers valuable insights into leveraging IoT sensors and ANN for heart attack risk prediction. © 2024 IEEE.

关键词： Adam Optimisation ANN Back Propagation Dense Layers Feed Forwarding Fuzzy Genetic Algorithm HTTP IoT MQTT One Hot Encoding Protocols UCI Heart Data

来源：评论

学校读者我要写书评

暂无评论

LegalAI Across Languages: A Comprehensive Survey on Tasks, Methodologies and Challenges 1

LegalAI Across Languages: A Comprehensive Survey on Tasks, M...

引用

1st International Conference on AIML-Applications for engineering and Technology, ICAET 2025

作者： Deshpande, Anjali Deshmukh, Pratiksha COEP Technological University Dept. of Computer Science and Engineering Pune India PICT Dept. of AI & DS Pune India School of Computational Sciences COEP Technological University Dept. of Computer Science and Engineering Pune India

ISBN: (纸本)9798350355611

Natural Language Processing (NLP) is revolutionizing the legal domain, enabling tasks such as predicting legal outcomes, summarizing complex documents, identifying key entities, and assessing bail risks. This survey paper presents a comprehensive review of the existing research on NLP tasks applied to legal documents and judgments across various languages, with a special emphasis on low-resource languages. Despite the extensive work done in widely spoken languages like English, there remains a critical need to extend these advancements to languages with limited resources and data availability. This paper categorizes and analyzes the NLP tasks in the legal domain based on the languages they target. It highlights the methodologies employed, datasets utilized, and the performance of different models across diverse languages. Furthermore, it identifies the gaps in current research and proposes potential directions for future work, particularly in improving the accessibility and applicability of NLP solutions for legal texts in underrepresented languages. By providing a comprehensive overview of advancements and obstacles, this survey seeks to assist future research endeavors that bridge the disparity between high-resource and low-resource languages in legalAI applications. © 2025 IEEE.

关键词： Risk assessment

来源：评论

学校读者我要写书评

暂无评论

Enacting Rural Empowerment: Implementing Cooperative Commerce in Communities using Machine Learning 2

Enacting Rural Empowerment: Implementing Cooperative Commerc...

引用

2nd IEEE International Conference on Networking and Communications, ICNWC 2024

作者： Skandarsini, R.R. Sangavi, M.S. Harika, Ravitla Varun, C.M. RMK Engineering College Dept. of Computer Science and Business Systems Thiruvallur India

ISBN: (纸本)9798350365269

In order to revitalize rural economies through the empowerment of self-help organizations and the promotion of economic growth, this study offers a revolutionary cooperative commerce platform. The platform integrates cutting-edge features such as digital ledger and inventory management for sellers, demand forecasting, and dynamic pricing, thereby fostering optimized production and efficient marketplaces. Central to the platform's efficacy is the implementation of user segmentation, which categorizes users based on income and spending behaviors, enabling targeted marketing strategies and continuous application improvements to enhance user engagement and profitability. Leveraging machine learning algorithms, personalized user experiences are cultivated, elevating buyer satisfaction and overall engagement. Additionally, administrative tools provide valuable insights for informed decision-making. Preliminary results demonstrate improved financial management for self-help groups, heightened economic activities, and an enriched user-centric experience. Identified challenges and proposed future enhancements underscore the platform's commitment to adaptability and responsiveness to the evolving needs of rural communities, ensuring sustained relevance and impact. © 2024 IEEE.

关键词： Predictive analytics

来源：评论

学校读者我要写书评

暂无评论

Detection of Specific Language Impairment Using XGBoost Model 15

Detection of Specific Language Impairment Using XGBoost Mode...

引用

15th International Conference on Computing Communication and Networking Technologies, ICCCNT 2024

作者： Rai, Rajnish Thenkanidiyoor, Veena Dept. of Computer Science and Engineering National Institute of Technology Goa Goa India

ISBN: (纸本)9798350370249

Specific Language Impairment (SLI) in children, a neurodevelopmental disorder presenting significant hurdles in language acquisition. Motivated by the prevalence and complexity of SLI diagnosis, this article introduces an methodology using Mel-Frequency Cepstral Coefficients (MFCC) and chroma features combined with the XGBoost algorithm for classification. By analyzing a diverse dataset encompassing both SLI-diagnosed and non SLI children, the proposed model achieves efficiency of 99.3% accuracy on unseen data. Notably, the model’s strategic feature selection and utilization of XGBoost demonstrate superior performance compared to existing methods, highlighting its importance in SLI diagnosis and intervention planning. This work significantly advances machine learning-based diagnostic tools and holds promise for improving the quality of life for individuals impacted by SLI. ©2024 IEEE.

关键词： Adversarial machine learning

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 << < 82 83 84 85 86 87 88 89 90 91 > >>

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：