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

31,159 篇 会议
4,913 篇 期刊文献
244 册 图书

馆藏范围

36,316 篇 电子文献
0 种 纸本馆藏

日期分布

学科分类号

22,638 篇 工学
- 16,120 篇 计算机科学与技术...
- 13,476 篇 软件工程
- 5,972 篇 信息与通信工程
- 3,700 篇 控制科学与工程
- 2,866 篇 电子科学与技术（可...
- 2,856 篇 电气工程
- 2,362 篇 生物工程
- 1,940 篇 生物医学工程（可授...
- 1,589 篇 光学工程
- 1,488 篇 机械工程
- 1,338 篇 动力工程及工程热...
- 1,275 篇 仪器科学与技术
- 1,157 篇 化学工程与技术
- 905 篇 安全科学与工程
- 775 篇 交通运输工程
- 678 篇 建筑学
11,662 篇 理学
- 6,265 篇 数学
- 3,255 篇 物理学
- 2,585 篇 生物学
- 2,081 篇 统计学（可授理学、...
- 1,350 篇 系统科学
- 1,218 篇 化学
5,837 篇 管理学
- 3,458 篇 管理科学与工程(可...
- 2,685 篇 图书情报与档案管...
- 1,877 篇 工商管理
1,679 篇 医学
- 1,430 篇 临床医学
- 1,330 篇 基础医学(可授医学...
- 872 篇 药学(可授医学、理...
- 721 篇 公共卫生与预防医...
1,070 篇 法学
- 862 篇 社会学
676 篇 经济学
497 篇 农学
444 篇 教育学
183 篇 文学
80 篇 军事学
43 篇 艺术学
1 篇 哲学

主题

1,129 篇 accuracy
865 篇 feature extracti...
851 篇 computational mo...
766 篇 deep learning
691 篇 training
688 篇 computer science
548 篇 real-time system...
546 篇 machine learning
524 篇 support vector m...
455 篇 predictive model...
421 篇 internet of thin...
367 篇 convolutional ne...
363 篇 data models
355 篇 computer archite...
342 篇 reliability
316 篇 optimization
292 篇 data mining
277 篇 routing
257 篇 wireless sensor ...
252 篇 artificial intel...

机构

83 篇 institut univers...
82 篇 north-west unive...
81 篇 national centre ...
79 篇 infn sezione di ...
76 篇 infn sezione di ...
76 篇 institute of inf...
76 篇 tno technical sc...
66 篇 università di ca...
65 篇 université de st...
62 篇 nikhef national ...
59 篇 dept. of compute...
59 篇 dept. of informa...
58 篇 dept. of informa...
56 篇 dept. of compute...
53 篇 school of automa...
53 篇 leiden universit...
48 篇 dept. of compute...
48 篇 dept. of compute...
45 篇 dept. of electri...
44 篇 dept. of compute...

作者

85 篇 ferrara g.
85 篇 ardid m.
85 篇 gal t.
85 篇 bozza c.
84 篇 calvo d.
81 篇 chen a.
81 篇 kalekin o.
80 篇 díaz a.f.
80 篇 boumaaza j.
79 篇 coleiro a.
78 篇 gozzini s.r.
71 篇 dallier r.
69 篇 huang f.
64 篇 anguita m.
52 篇 kulikovskiy v.
44 篇 del burgo r.
41 篇 benoit d.m.
41 篇 eddymaoui a.
40 篇 gagliardini s.
40 篇 labalme m.

语言

31,050 篇 英文
4,770 篇 其他
318 篇 中文
119 篇 日文
71 篇 朝鲜文
6 篇 斯洛文尼亚文
4 篇 德文
3 篇 法文
1 篇 葡萄牙文

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

共 36316 条记录，以下是751-760 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：

Detection and Treatment of Epilepsy Disease using EEG Signals

Detection and Treatment of Epilepsy Disease using EEG Signal...

引用

2024 International Conference on Cybernation and Computation, CYBERCOM 2024

作者： Dhondiyal, Shiv Ashish Dimri, Sushil Chandra Graphic Era Deemed to Be University Dept. of Computer Science and Engineering Dehradun India

ISBN: (纸本)9798331542344

Epilepsy Seizures is a neurological illness that causes repeated seizures and affects millions of people throughout the world. From the studies it has been detected that 70% peoples in the world suffer from epilepsy disease. The prognosis and medical care of epileptic seizure are critical for improving the quality of life of affected individual. Electroencephalography (EEG) is a valuable technique for diagnosing and managing epilepsy because it allows for real-time monitoring of brain electrical activity. Recent advancements in signal processing techniques, such as the Discrete Wavelet Transform (DWT), have shown significant promise in enhancing the diagnosis and treatment of epilepsy. This paper purposed an optimize Random Forest (RF) algorithm by using the DWT application in the analysis of EEG signals for the prognosis of epilepsy disease along with its treatment like medicines, therapies and other treatments methods to cure epilepsy disease. The suggested approach provides clinicians with a promising tool for early and precise identification of epileptic seizures, which is critical for making improvements in patient outcomes and quality of life. The simulation results show that the purposed optimize support vector machine algorithm gives better results with an accuracy of 98% along with the sensitivity, specificity and f1-score of 97%, 96% and 98% respectively. © 2024 IEEE.

关键词： Electroencephalography

来源：评论

学校读者我要写书评

暂无评论

Smart Traffic Management system for Urban Mobility Enhancement Using RF Sensors, Cameras, and Machine Learning 4

Smart Traffic Management System for Urban Mobility Enhanceme...

引用

4th International Conference on Power, Energy, Control and Transmission systems, ICPECTS 2024

作者： Vivekanandan, G. Pathmanaban, J. James, Prabahar Godwin Barani Sree, S. Priyanka, V. Samvardhini, V.M. Sri Sai Ram Institute of Technology Dept. of Computer Science and Engineering India

ISBN: (纸本)9798331508845

This paper introduces a Smart Traffic Management system (STMS)employing RF sensors, cameras, and machine learning algorithms to monitor and optimize urban traffic. The system dynamically adjusts traffic signal timings, offers real-time route recommendations based on GPS data, and incorporates adaptive control mechanisms to reduce congestion and improve overall mobility. Simulation studies and real-world testing demonstrate the effectiveness of the STMS in enhancing traffic flow, minimizing waittimes, and contributing to sustainable urbandevelopment. © 2024 IEEE.

关键词： Traffic signals

来源：评论

学校读者我要写书评

暂无评论

Plant Disease Detection using Convolutional Neural Network

Plant Disease Detection using Convolutional Neural Network

引用

2024 International Conference on Smart Devices, ICSD 2024

作者： Agarwal, Jyoti Naithani, Shivansh Singh, Utkarsh Raj, Harsh Graphic Era Deemed to be University Dept. of Computer Science and Engineering Dehradun India

ISBN: (纸本)9798350394412

Pest-infested plants and crops have a negative effect on the nation's agricultural output. To detect and identify diseases in plants, farmers or other experts must keep a careful watch on plants. However, this method is frequently expensive, time-consuming, and inaccurate. Finding a spot on the leaves of the infected plant is one method of detecting plant diseases. This research aims to develop a disease detection model based on the classification of leaf images. To detect plant illnesses the proposed model utilizes image processing with a convolution neural network (CNN). This research work focus on three different plant diseases: tomato, corn and potato. Experimental results show high accuracy rate of 98.8%. Proposed work is also compared with some existing work working o same plants diseases. © 2024 IEEE.

关键词： Support vector regression

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

Enhanced Detection of DoS/DDoS Attacks in SDN Using Ensemble and Hybrid CNN-LSTM Models

Enhanced Detection of DoS/DDoS Attacks in SDN Using Ensemble...

引用

2024 IEEE International Conference on Computing, Applications and systems, COMPAS 2024

作者： Afroj, Maharin Rifat, Khan Md Sadbin Rahman, Md. Saifur Bangladesh University of Business and Technology Dept. of Computer Science and Engineering Dhaka Bangladesh

ISBN: (纸本)9798331529765

Software-Defined Networking (SDN) faces significant challenges in mitigating Attacks known as denial of service (DoS) and distributed DDoS due to its centralized control plane architecture. This centralization makes the control plane an attractive target for attackers, highlighting the need for effective detection and mitigation strategies. In this study, we propose three innovative methodologies to enhance the accuracy of detecting DoS/DDoS attacks in SDN environments. Our first methodology employs an ensemble model with a voting classifier, which achieves a detection accuracy of 97.4%. This approach leverages multiple weak learners to enhance the robustness of detection. The second methodology utilizes an ensemble with a stacking technique, attaining a superior accuracy of 99%, demonstrating the efficacy of integrating multiple base models in a hierarchical fashion. The third approach introduces a novel hybrid model that blends LSTM networks with CNN, achieving a competitive accuracy of 98.51%. A comparative analysis of these methods reveals that, while all three significantly enhance detection rates, the stacking ensemble technique outperforms the others. This finding underscores the potential of advanced ensemble techniques in effectively addressing the dynamic and evolving cyber threats within SDN environments. Our study offers valuable insights into strengthening SDN infrastructures against DoS/DDoS attacks, contributing to the ongoing efforts to secure modern network architectures. © 2024 IEEE.

关键词： Denial-of-service attack

来源：评论

学校读者我要写书评

暂无评论

Reconnaissance Detection in Decentralised IoT system using Model-Contrastive Federated Learning 18

Reconnaissance Detection in Decentralised IoT System using M...

引用

18th IEEE International Conference on Advanced Networks and Telecommunications systems, ANTS 2024

作者： Dutta, Rajdeep Kumar Chhetry, Bishal Matam, Rakesh Barbhuiya, Ferdous Ahmed Indian Institute of Information Technology Dept. of Computer Science and Engineering Guwahati India

ISBN: (纸本)9798350391725

The detection of reconnaissance attacks is crucial for safeguarding Internet of Things (IoT) environments, which are inherently more vulnerable and resource-constrained compared to traditional computing systems. Traditional centralised detection methods face significant challenges, such as privacy concerns and limited scalability due to the need to aggregate raw data on a central server. These issues become particularly pronounced in IoT environments where devices are diverse and geographically distributed. To address these challenges, we propose ReconGuard, a novel approach leveraging Model Contrastive Federated Learning (MCFL). ReconGuard enables collaborative training across multiple IoT devices without the necessity of sharing raw data, thereby preserving user privacy and enhancing data security. The approach integrates contrastive learning techniques, which improve the model's ability to discriminate between benign and malicious activities by contrasting positive (similar) and negative (dissimilar) data pairs. Our experimental results demonstrate that the ReconGuard-based detection system provides a scalable and privacy-preserving solution for identifying reconnaissance activities. These activities are often the initial step in more severe cyber threats, such as botnet attacks, which can lead to significant disruption and damage. By effectively detecting reconnaissance activities, ReconGuard enhances the overall cybersecurity framework of IoT environments. This research presents a viable and innovative method for improving cybersecurity in IoT systems, addressing the critical need for scalable, efficient, and privacy-preserving intrusion detection solutions. The use of MCFL in ReconGuard not only mitigates the challenges of data centralisation but also leverages the distributed nature of IoT networks to enhance robustness against cyber threats. © 2024 IEEE.

关键词： Contrastive Learning

来源：评论

学校读者我要写书评

暂无评论

Cloud-Based Water Parameter Monitoring for Smart Fisheries

Cloud-Based Water Parameter Monitoring for Smart Fisheries

引用

2024 IEEE Region 10 Symposium, TENSYMP 2024

作者： Bahadur, Arshad Mohammad Sakib, Najmus Moinuddin, Kazi Md. Hussein Islam, Tanzimul Islam, A.K.M. Muzahidul United International University Dept. of Computer Science & Engineering Dhaka1212 Bangladesh

ISBN: (纸本)9798350364866

The Cloud-based Water Parameter Monitoring system leverages cloud and IoT technologies for the precise monitoring of water quality across various water bodies. In Bangladesh, fish is a vital dietary component, consumed more frequently and in larger quantities than any other animal-source food. The fisheries sector greatly contributes to GDP, employment, and it is the second-largest export product of the country. However, pollution and inadequate real-time water quality monitoring significantly impact the industry, costing thousands of crores. This research involved collecting water parameter data from different water bodies using specialized sensors connected to Arduino devices. The data was processed and stored on an edge server before being periodically sent to a cloud server. We developed a user-friendly web application and integrated an alert system to notify farm workers when parameters deviate from acceptable ranges. The goal is to enhance sustainable fish farming practices by improving operational efficiency, reducing environmental impact, and ensuring optimal fish health through IoT, Machine Learning techniques, and Cloud technologies. © 2024 IEEE.

关键词： Fish

来源：评论

学校读者我要写书评

暂无评论

Pruning Based Improved Pedestrian Detection in Video Surveillance 11

Pruning Based Improved Pedestrian Detection in Video Surveil...

引用

11th International Conference on Reliability, Infocom Technologies and Optimization, ICRITO 2024

作者： Sharma, Suchi Diwakar, Manoj Gangodkar, Durgaprasad Graphic Era Deemed to Be University Dept. of Computer Science and Engineering Dehradun India

ISBN: (纸本)9798350350357

Real-time object identification applications are using methods for image processing more and more as a result of advancements in computer technology. Results for pedestrian identification were improved by the use of deep learning techniques. To locate human beings quickly and precisely, this study suggests employing pruning to increase the Yolo models' efficiency in pedestrian recognition. This method would allow the device to function seamlessly when used for video surveillance. This method uses one stage detector, YOLOv5, to better suit the task situations and adjust to the real-time demands. To improve the possible model sparsity, 1 × 1 kernel weights are pruned using a pruning approach. The findings show that, following pruning, this model attains a 30% sparsity in this model, which indicates that 30% of the weight parameters in the nn. Conv2d layers of the algorithm are equal to 0. Inference time is nearly constant and soft-nms is applied for better ROI results. In addition, a thorough result and discussion are given to demonstrate the efficacy of this methodology regarding mAP, latency, energy consumption, and attained sparsity. © 2024 IEEE.

关键词： Energy utilization

来源：评论

学校读者我要写书评

暂无评论

Machine Learning based Anxiety Detection using Physiological Signals and Context Features 2

Machine Learning based Anxiety Detection using Physiological...

引用

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

作者： Jain, Arushi Kumar, Rajeev National Institute of Technology Hamirpur Dept. of Computer Science and Engineering Hamirpur India

ISBN: (纸本)9798350371314

Anxiety is a common mental disorder that affects millions of people worldwide. Anxiety can be detected using physiological signals such as heart rate, skin conductance, blood pressure, and respiration. Machine learning is the ability to learn from data and forecast future events. Physiological signals can be analyzed and classified into different anxiety levels using machine learning. This paper aims to present the contribution of context features in detection of anxiety using physiological signals via machine learning. It is an imbalanced multiclassification problem using ECG and EDA signals with context features collected from 15 healthy individuals. These signals of sampling rate 700 Hz collected using RespiBAN from the Wearable Stress and Affect Detection (WESAD) dataset are used here with the 6-STAI questionnaire and the context collected about the subject during the experiment. Scores for each subject are calculated from this questionnaire which categorized subjects into different levels of anxiety. Multiple features are extracted from these signals and scaling is done on the extracted features. With the help of different data balancing techniques and different machine learning algorithms, this study will classify anxiety into three classes, namely, low, moderate and high. Classification of anxiety with fusion of multimodal physiological signals gave better results as compared to single modal physiological signals with an accuracy of 89.8% with ECG signal, 85.9% with EDA signal and 96.7% with ECG and EDA both using Gradient Tree Boosting algorithm with LOOCV after random oversampling. While, the best results are achieved when multimodal physiological signals are fused with context features, it gives the accuracy of 97.3% with Gradient Tree Boosting and LOOCV algorithm. © 2024 IEEE.

关键词： Electrocardiograms

来源：评论

学校读者我要写书评

暂无评论

World Coin Currency Detection: A Comparative Study of Machine Learning and Deep Learning

World Coin Currency Detection: A Comparative Study of Machin...

引用

2024 International Conference on Smart Devices, ICSD 2024

作者： Dumka, Ankur Pandey, Arnav Mishra, Amit Kumar Bhaskarrao Bahadure, Nilesh Tripathi, Neha Pandey, Neeraj Kumar Women Institute of Technology Dept. of Computer Science & Engineering Dehradun India St. Joseph's Academy Dehradun India Graphic Era Hill University Dept. of Computer Science & Engineering Dehradun India Symbiosis Institute of Technology Nagpur Campus Pune India Dept. of Computer Science & Engineering Dehradun India

ISBN: (纸本)9798350394412

In the economy where trade and finance are closely linked it is essential to accurately identify and authenticate various currencies, especially in industries such, as banking, tourism and retail. Conventional methods, for identifying coins typically require inspections or simple automated processes, which might take up a lot of time and are susceptible, to mistakes. The advancements, in machine learning (ML) and deep learning (DL) technologies, over the years have revolutionized currency detection providing efficient solutions. This article discusses the evaluation of machine learning and deep learning approaches to identify types of coins. It explores how algorithms, like MobileNetV2, Support Vector Machines (SVM), Random Forest, Convolutional Neural Networks (CNN) and Recurrent Neural Networks (RNN) perform in distinguishing and classifying coin denominations across currencies. The results of experiments conducted on data sets show how these methods compare in terms of accuracy, effectiveness, and reliability. Furthermore, we examine the advantages and constraints of each approach while suggesting directions for advancing research, in the realm of identifying cryptocurrency. © 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

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 << < 72 73 74 75 76 77 78 79 80 81 > >>

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：