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

5,458 篇 会议
1,036 篇 期刊文献
98 册 图书

馆藏范围

6,592 篇 电子文献
0 种 纸本馆藏

日期分布

学科分类号

4,078 篇 工学
- 2,726 篇 计算机科学与技术...
- 2,296 篇 软件工程
- 951 篇 信息与通信工程
- 762 篇 控制科学与工程
- 585 篇 电气工程
- 552 篇 电子科学与技术（可...
- 351 篇 生物工程
- 274 篇 生物医学工程（可授...
- 273 篇 机械工程
- 249 篇 光学工程
- 238 篇 动力工程及工程热...
- 190 篇 仪器科学与技术
- 165 篇 化学工程与技术
- 144 篇 安全科学与工程
- 137 篇 交通运输工程
- 123 篇 建筑学
- 119 篇 材料科学与工程（可...
2,005 篇 理学
- 1,149 篇 数学
- 479 篇 物理学
- 384 篇 生物学
- 345 篇 统计学（可授理学、...
- 317 篇 系统科学
- 157 篇 化学
987 篇 管理学
- 634 篇 管理科学与工程(可...
- 410 篇 图书情报与档案管...
- 390 篇 工商管理
219 篇 医学
- 198 篇 临床医学
- 184 篇 基础医学(可授医学...
185 篇 法学
- 148 篇 社会学
138 篇 经济学
- 137 篇 应用经济学
111 篇 教育学
64 篇 农学
17 篇 文学
17 篇 军事学
6 篇 艺术学

主题

144 篇 accuracy
124 篇 computational mo...
114 篇 machine learning
111 篇 feature extracti...
108 篇 software
106 篇 training
96 篇 software enginee...
93 篇 optimization
87 篇 predictive model...
87 篇 artificial intel...
83 篇 deep learning
76 篇 real-time system...
73 篇 data models
68 篇 computer science
68 篇 computer archite...
62 篇 data mining
61 篇 internet of thin...
61 篇 monitoring
61 篇 mathematical mod...
58 篇 neural networks

机构

56 篇 dept. of systems...
32 篇 dept. of systems...
23 篇 optical sciences...
20 篇 dept. of electri...
19 篇 faculty of compu...
19 篇 gik institute of...
19 篇 university of eu...
19 篇 dept. of technol...
16 篇 dept. of electri...
15 篇 dept. of compute...
15 篇 dept. of softwar...
15 篇 dept. of compute...
14 篇 dept. of electri...
14 篇 dept. of electri...
13 篇 dept. of systems...
12 篇 dept. of softwar...
12 篇 networking and i...
12 篇 ieee
12 篇 bcmaterials basq...
12 篇 dept. of compute...

作者

35 篇 wainer gabriel
21 篇 ali raja hashim
20 篇 tan mengxi
20 篇 moss david j.
19 篇 xu xingyuan
18 篇 gabriel wainer
18 篇 usama arshad
18 篇 ku wei-shinn
18 篇 arshad usama
16 篇 zain ul abideen
15 篇 yangquan chen
14 篇 baldwin timothy
13 篇 shabtai asaf
13 篇 ali zeeshan ijaz
13 篇 xi zhang
12 篇 reiner lisa
12 篇 hyunseung choo
12 篇 sakamoto makoto
12 篇 min dong
12 篇 nisar ali

语言

5,982 篇 英文
533 篇 其他
59 篇 中文
9 篇 朝鲜文
8 篇 日文
1 篇 德文
1 篇 俄文

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

共 6592 条记录，以下是861-870 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：

GenAir: Generative AI for Resilient Urban Air Mobility with VTOLs in Disaster Evacuation

GenAir: Generative AI for Resilient Urban Air Mobility with ...

引用

Simulation Winter Conference

作者： Abdullah Alsaheal William Hoy Priscila Haro Asad Rehman Nurcin Celik Dept. of Industrial and Systems Engineering University of Miami Coral Gables FL USA Dept. of Mathematics and Computer Science Saint Louis University Madrid SPAIN

ISBN: (数字)9798331534202

ISBN: (纸本)9798331534219

Coastal regions face growing threats, making timely and safe evacuation paramount. Current plans rely heavily on congested ground transportation, leading to delays and heightened stress levels. The emerging field of Urban Air Mobility (UAM), utilizing Vertical Take-Off and Landing Vehicles (VTOLs), promises to alleviate these issues by providing solutions for quick evacuation strategies. Here, we aim to leverage Generative Adversarial Networks (GANs) to expand limited datasets with synthetic data specific to disaster scenarios, evacuation routes, airspace considerations, and the impact of real-time weather events, enabling robust simulation of UAM deployment in disaster evacuations. We identified two applicable scenarios: i) UAM for Extreme Weather Emergency Evacuation and ii) Hospital Evacuations using VTOLs as use cases and illustrated their impact. This research seeks to pave the way for optimized, data-driven evacuation planning with UAM and VTOLs, ultimately enhancing the safety and efficiency of evacuations in the face of extreme events.

关键词： Hospitals Disasters Land transportation Sea measurements Real-time systems Planning Faces Stress Meteorology Synthetic data

来源：评论

学校读者我要写书评

暂无评论

Rare and Common Types of Retinal Disease Recognition Using Ensemble Deep Learning

Rare and Common Types of Retinal Disease Recognition Using E...

引用

International Conference on Electrical, computer and Communication engineering (ECCE)

作者： Jesika Debnath Al Shahriar Uddin Khondakar Pranta Arafath Bin Mohiuddin Amira Hossain Anamul Sakib Md. Moniruzzaman Shanto Shamim Forhad Abdullah Al-Sakib Rezaul Haque Shafiur Rahman Dept. of Computer Science Westcliff University Irvine CA USA Dept. of Computer Science Wright State University Dayton USA Department of Collage of Engineering and Technology Westcliff University CA USA Department of Business Administration International American University CA USA Dept. of Computer Science and Engineering East West University Dhaka Bangladesh Dept. of Electrical and Electronics Engineering American International University Bangladesh Dept. of Information Technology Westcliff University CA USA Dept. of Software Engineering Daffodil International University Dhaka Bangladesh

ISBN: (数字)9798350357509

ISBN: (纸本)9798350357516

Detecting retinal diseases is crucial for preventing vision loss, but it comes with challenges, such as data imbalance and accurately classifying rare conditions. This study introduces a new ensemble transfer learning model that combines EfficientNetB7, SE-ResNet, DenseNet-169, and NASNet to improve the classification of common and rare retinal diseases. The ensemble uses a probability averaging approach to maximise each architecture’s strengths. Essential preprocessing techniques such as Global Contrast Normalization (GCN) and Total Variation Denoising (TVD) were used to enhance image quality. The model was trained and evaluated on the Retinal Fundus Multi-Disease Image Dataset (RFMiD) 2.0, achieving 98.65% accuracy and an F1-score of 0.96% for common diseases and 99.10% accuracy with an F1-score of 0.97 for rare diseases, outperforming individual models significantly. The ensemble has been integrated into a web-based application that allows clinicians to upload retinal images for instant diagnostic feedback, enabling real-time analysis and visual insights. Despite its strengths, challenges such as high computational demands and reliance on high-resolution photos remain. Future work will improve computational efficiency through model compression techniques and extend the model to other imaging modalities, such as Optical Coherence Tomography (OCT). In conclusion, this study presents a robust and scalable solution for retinal disease classification, potentially improving early detection and providing real-time support in clinical settings, particularly in resource-limited environments.

关键词： Deep learning Visualization Accuracy Computational modeling Optical coherence tomography Transfer learning Imaging Retina Real-time systems Diseases

来源：评论

学校读者我要写书评

暂无评论

Weapon detection system for surveillance and security

Weapon detection system for surveillance and security

引用

2023 International Conference on IT Innovation and Knowledge Discovery, ITIKD 2023

作者： Khalid, Shehzad Waqar, Abdullah Ain Tahir, Hoor Ul Edo, Onome Christopher Tenebe, Imokhai Theophilus Bahria University Dept. of Computer Engineering Islamabad Pakistan Auburn University at Montgomery Department of Information Systems Alabama United States Mineta Transportation Institute San Jose State University CA United States

ISBN: (纸本)9781665463720

Weapon detection is a critical and serious topic in terms of public security and safety, however, it's a difficult and time-consuming operation. Due to the increase in demand for security, safety, and personal property protection, the requirement for deploying video surveillance systems capable of recognizing and interpreting scenes and anomalous occurrences plays an important role in intelligence monitoring. In certain regions of the globe, mass shootings and gun violence are on the increase. Timely detection of the presence of a gun is critical to prevent loss of life and property. Several object detection models are available, which struggle to recognize firearms due to their unique size and form, as well as the varied colors of the background. In this study, we proposed a state-of-the-art system based on a deep learning model YOLO V5 for weapon detection that will be sufficiently resilient in terms of affine, rotation, occlusion, and size. We evaluated the performance of our system on a publicly available dataset and achieved the F1-score of 95.43%. For the detection and segmentation of firearms, we implemented Instance segmentation or Pixel level segmentation which employed Mask-RCNN. The system achieved the detection accuracy (DC) of 90.66% and 88.74% Mean intersection over union (mIoU). The purposed methodology combined different data augmentation and preprocessing methods to improve the accuracy of the proposed weapon detection system. © 2023 IEEE.

关键词： Object detection

来源：评论

学校读者我要写书评

暂无评论

Predictive Analysis of Jordan Road Accidents Severity Using Machine Learning

Predictive Analysis of Jordan Road Accidents Severity Using ...

引用

International Symposium on Networks, computers and Communications (ISNCC)

作者： Dheya Mustafa Layan Sawaged Safaa M. Khabour Dept. of Computer Engineering Faculty of Engineering The Hashemite University Zarqa Jordan Dept. of Information Systems Faculty of Information Technology and Computer Sciences Yarmouk University Irbid Jordan

Jordan has a high and growing level of traffic accidents reaching 160,600) accidents in 2021, (11,241) of them had human injuries, (589) deaths, and (320) million JOD losses. Road traffic accidents are currently the 8th leading cause of death worldwide, accounting for about 1.35 million fatalities annually. Understanding the primary causes of these accidents and the circumstances in which they occur is essential if governments throughout the world are to put policies in place to limit the number of fatalities brought on by traffic accidents. This project has two objectives: (i) to learn more about Jordan's present road accident situation by performing an exploratory study on several road accident datasets, and (ii) to investigate the effectiveness of various machine-learning techniques in predicting the severity of road accidents in Jordan. The dataset entities were collected, collated, explored, and prepared for use in the model. To assess their predictive performance, five different classification algorithms were trained and tested. The findings of the present study demonstrate that the best algorithm was Logistic Regression, which had an accuracy of 98.1%.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Selfish Users in Listen-Before-Talk Co-existence of Cellular-Wi-Fi Networks: Counteraction Methods

Selfish Users in Listen-Before-Talk Co-existence of Cellular...

引用

International Symposium on Modeling and Optimization in Mobile, Ad Hoc, and Wireless Networks (WiOpt)

作者： Saibharath S Sudeepta Mishra Gazal Arora Anamika Sharma Chittaranjan Hota Dept. of Computer Science and Information systems BITS Pilani Hyderabad Campus India Dept. of Computer Science and Engineering IIT Ropar Punjab India

5G operates in the unlicensed spectrum to expand its capacity. This spectrum provides more uplink and downlink frequency bands in 5G to satisfy ultra-dense and scalability requirements. Wi-Fi is a prominent wireless technology that operates in unlicensed bands. Due to the proximity of cellular and Wi-Fi channels, utilization of both Wi-Fi and 5G New Radio (NR) can cause interference. The co-existence of 5G NR and Wi-Fi devices lacks the means of communication for negotiation and coordination among them. Listen-Before-Talk and Duty-cycling are standard Medium Access Control (MAC) mechanisms to enable co-existence. Due to a lack of coordination, network utilization becomes unfair with the existence of selfish devices. The selfish users could maximize throughput and affect other Wi-Fi and NR users. Here, we investigate the effects of selfish nodes on this Wi-Fi Co-existence with 5G. These nodes disobey exponential backoff to boost their channel acquisition. We study the effect of misbehavior through the Order Gain metric. Through standard CSMA/CA settings with overall channel occupancy of 99.75%, we demonstrate that selfish users profoundly impact fair co-existence. We study the side effects through throughput, channel sensing, and acquisition for various backoff window access patterns. Finally, we go through counteraction methods to overcome the selfish user impact.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Characterization and Control of a Superconducting Homopolar Motor with Cryogenic GaN Inverter for Electric Aircrafts

Characterization and Control of a Superconducting Homopolar ...

引用

2024 IEEE Energy Conversion Congress and Exposition, ECCE 2024

作者： Gliese, Felix Pearce, Matthew G. S. Wadsworth, Aaron Siamaki, Mohammad Storey, James Lumsden, Grant Thrimawithana, Duleepa J. Badcock, Rod Roth-Stielow, Joerg Neuburger, Martin Esslingen University Faculty of Mobility and Technology Germany The University of Auckland Dept. of Electrical Computer and Software Engineering New Zealand OpenStar Technologies New Zealand Victoria University of Wellington Robinson Research Institute New Zealand University of Stuttgart Institute for Power Electronics and Electrical Drives Germany

ISBN: (纸本)9798350376067

In the quest for a zero-emissions future, the aviation sector is facing the challenge of reducing its carbon footprint. This paper presents a characterization of a superconducting homopolar motor designed to meet the stringent power and efficiency requirements of all-electric aircraft. The control system, which features field-oriented control and a multi-layer architecture, ensures precise operation of the motor under various load conditions. The motor uses a stationary cryogenic superconducting DC coil to generate the rotor's magnetic field. Utilizing superconducting materials helps produce the high power densities critical for aviation. The characterization of the key parameters of the motor, such as inductances, stator resistance and flux, are presented. A description of the cryogenic GaN power electronic inverter power stage immersed in liquid nitrogen is provided. This design enables future integration next to the motor, and improved power density and efficiency. This paper outlines the design, implementation, and initial testing of the superconducting homopolar motor and its power electronics, highlighting its potential for electric propulsion in aviation by providing a viable solution for long-range flights. © 2024 IEEE.

关键词： Gallium nitride

来源：评论

学校读者我要写书评

暂无评论

Neuromorphic computing by means of recurrent spectrum slicing for next generation high baud rate transmission systems

Neuromorphic computing by means of recurrent spectrum slicin...

引用

LEOS Summer Topical Meetings

作者： Adonis Bogris Kostas Sozos George Sarantoglou Stavros Deligiannidis Charis Mesaritakis Dept. Informatics and Computer Engineering University of West Attica Athens Greece Dept. of Informatics and Computer Engineering University of West Attica Athens Greece Dept. of Information and Communication Systems Engineering University of the Aegean Karlovassi Greece

In this paper we review our recent work in photonic neural networks based on recurrent optical spectrum slicing as potential accelerators for the mitigation of transmission impairments in short reach, high symbol rate...

关键词：

来源：评论

学校读者我要写书评

暂无评论

Coordinate Attention-enabled Ship Object Detection with Electro-optical Image 11

Coordinate Attention-enabled Ship Object Detection with Elec...

引用

11th International Conference on Computing and Pattern Recognition, ICCPR 2022

作者： Xu, Hongbin Jiang, Xiantao Yin, Tao Cen, Qi Zhang, Zhijian Song, Tian Yu, F. Richard Dept.Information Engineering Shanghai Maritime University Shanghai China Ningbo Special Equipment Inpection and Research Institute Ningbo China Dept. Electrical and Electronics Engineering Tokushima University Tokushima Japan Dept. Systems and Computer Engineering Carleton University Ottawa Canada

ISBN: (纸本)9781450397056

Shipping safety is one of the factors restricting the development of navigation. In particular, the route near the shore is prone to unknown risks due to the existence of multiple types of ships, the density of ships, the shielding between ships, and other reasons. This paper presents a method for detecting medium-range ships, which can improve security for ships. This method is based on the You Only Look Once Version 5 network (YOLOv5). To improve the accuracy, the coordinate attention model is integrated into the detection network. The main research content and experimental work of this paper are as follows. Firstly, the YOLOv5 network and spatial attention mechanism are analyzed. Then, detection experiments were carried out based on YOLOv5 and Singapore Maritime Data Set (SMD). Then, the coordinate attention model was used to improve the network. Finally, by adjusting training parameters and improving attention, the mAP of test results of the object detection network reaches 73%, and the feasibility of object detection of the YOLOv5 algorithm with coordinate attention is confirmed. © 2022 ACM.

关键词： Object detection

来源：评论

学校读者我要写书评

暂无评论

Deep Learning-Based Stock Price Prediction: A Comprehensive Approach Using Bi-LSTM

Deep Learning-Based Stock Price Prediction: A Comprehensive ...

引用

Ubiquitous Computing and Intelligent Information systems (ICUIS), International Conference on

作者： Md. Kalim Amzad Chy Abdul Kadar Muhammad Masum Mohammed Shamsul Alam Md. Abul Kalam Azad Md. Maruf Hassan Touhid Bhuiyan Dept. of Computer Science and Engineering International Islamic University Chittagong Bangladesh Dept. of Software Engineering Daffodil International University Dhaka Bangladesh Dept. of Computer Science and Engineering International Islamic University Chittagong Bangladesh Dept. of Business and Technology Management Islamic University of Technology Gazipur Bangladesh School of IT Washington University of Science and Technology VA USA

ISBN: (数字)9798331529635

ISBN: (纸本)9798331529642

This study delves into the prediction of stock prices in the Bangladesh stock market using advanced deep learning frameworks, with a particular focus on the Bidirectional Long Short-Term Memory (Bi-LSTM) model. Traditional statistical models often struggle to effectively capture the complex, non-linear characteristics of financial data, leading to inconsistent results. The Bi-LSTM model, however, addresses this challenge by processing data in both forward and backward sequences, making it particularly suitable for analyzing the intricate dynamics of the Bangladesh stock market. A rigorous feature engineering process is undertaken, incorporating 64 distinct features that include market trends, stock-specific indicators, technical and fundamental variables, as well as crucial macroeconomic factors like gold prices and foreign exchange reserves. The dataset spans historical stock market data from 2012 to 2022, with comprehensive preprocessing steps taken to ensure data quality and consistency. Hyperparameter tuning is executed through a grid search to optimize model performance. The evaluation of the Bi-LSTM model is carried out using metrics such as Mean Absolute Error (MAE), Mean Absolute Percentage Error (MAPE), Mean Squared Error (MSE), and the R2 score, which demonstrate its enhanced predictive power compared to traditional models. This research contributes to the growing field of deep learning in financial forecasting, offering new perspectives for stock price prediction in emerging markets, while also addressing ethical issues to minimize risks like market manipulation.

关键词： Deep learning Analytical models Data integrity Computational modeling Predictive models Data models Macroeconomics Stock markets Forecasting Long short term memory

来源：评论

学校读者我要写书评

暂无评论

Blockchain-Enhanced Framework for Secure Third-Party Vendor Risk Management and Vigilant Security Controls

Blockchain-Enhanced Framework for Secure Third-Party Vendor ...

引用

IEEE International Conference on Big Data

作者： Deepti Gupta Lavanya Elluri Avi Jain Shafika Showkat Moni Omer Aslan Dept. of Computer Information Systems Texas A&M University - Central Texas Texas USA College of Business University of Tampa Florida USA Dept. of Electrical Engineering and Computer Science Embry-Riddle Aeronautical University Florida USA Department of Software Engineering Bandırma Onyedi Eylül University Bandırma Turkey

ISBN: (数字)9798350362480

ISBN: (纸本)9798350362497

In an era of heightened digital interconnectedness, businesses increasingly rely on third-party vendors to enhance their operational capabilities. However, this growing dependency introduces significant security risks, making it crucial to develop a robust framework to mitigate potential vulnerabilities. This paper proposes a comprehensive secure framework for managing third-party vendor risk, integrating blockchain technology to ensure transparency, traceability, and immutability in vendor assessments and interactions. By leveraging blockchain, the framework enhances the integrity of vendor security audits, ensuring that vendor assessments remain up-to-date and tamperproof. This proposed framework leverages smart contracts to reduce human error while ensuring real-time monitoring of compliance and security controls. By evaluating critical security controls—such as data encryption, access control mechanisms, multi-factor authentication, and zero-trust architecture—this approach strengthens an organization’s defense against emerging cyber threats. Additionally, continuous monitoring enabled by blockchain ensures the immutability and transparency of vendor compliance processes. In this paper, a case study on iHealth’s transition to AWS Cloud demonstrates the practical implementation of the framework, showing a significant reduction in vulnerabilities and marked improvement in incident response times. Through the adoption of this blockchain-enabled approach, organizations can mitigate vendor risks, streamline compliance, and enhance their overall security posture. Our findings highlight the importance of employing blockchain to enforce security controls and maintain compliance with healthcare regulations such as HIPAA. In this paper, we present a comprehensive set of security controls and demonstrate how blockchain technology enhances their effectiveness, ensuring greater transparency, accountability, and automation in vendor assessments. By reducing human error, enabl

关键词： Multi-factor authentication Smart contracts Organizations Real-time systems Regulation Blockchains Security Time factors Risk management Resilience

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 << < 83 84 85 86 87 88 89 90 91 92 > >>

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：