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

612 篇 会议
339 篇 期刊文献
10 册 图书

馆藏范围

961 篇 电子文献
0 种 纸本馆藏

日期分布

学科分类号

573 篇 工学
- 311 篇 计算机科学与技术...
- 248 篇 软件工程
- 116 篇 信息与通信工程
- 103 篇 电气工程
- 87 篇 控制科学与工程
- 83 篇 建筑学
- 80 篇 动力工程及工程热...
- 76 篇 土木工程
- 70 篇 电子科学与技术（可...
- 68 篇 材料科学与工程（可...
- 66 篇 机械工程
- 62 篇 化学工程与技术
- 59 篇 生物工程
- 48 篇 生物医学工程（可授...
- 44 篇 环境科学与工程（可...
- 29 篇 力学（可授工学、理...
299 篇 理学
- 129 篇 数学
- 87 篇 物理学
- 74 篇 生物学
- 46 篇 化学
- 42 篇 统计学（可授理学、...
- 32 篇 系统科学
146 篇 管理学
- 117 篇 管理科学与工程(可...
- 77 篇 工商管理
- 36 篇 图书情报与档案管...
50 篇 医学
- 40 篇 临床医学
- 36 篇 基础医学(可授医学...
- 27 篇 公共卫生与预防医...
41 篇 经济学
- 41 篇 应用经济学
39 篇 法学
- 31 篇 社会学
26 篇 农学
15 篇 教育学
3 篇 艺术学
2 篇 文学
1 篇 哲学
1 篇 军事学

主题

26 篇 machine learning
22 篇 accuracy
18 篇 resonators
17 篇 security
17 篇 performance eval...
16 篇 predictive model...
16 篇 resonant frequen...
15 篇 internet of thin...
15 篇 real-time system...
14 篇 simulation
14 篇 wireless communi...
14 篇 6g mobile commun...
14 篇 phased arrays
13 篇 deep learning
13 篇 slot antennas
13 篇 artificial intel...
13 篇 measurement
12 篇 covid-19
12 篇 computational mo...
11 篇 reliability

机构

72 篇 school of comput...
57 篇 school of comput...
44 篇 school of comput...
41 篇 school of comput...
35 篇 school of built ...
24 篇 school of comput...
19 篇 bts group istanb...
17 篇 department of el...
16 篇 college of engin...
16 篇 school of comput...
16 篇 faculty of engin...
15 篇 school of comput...
15 篇 edinburgh napier...
14 篇 faculty of engin...
14 篇 zarqa university...
14 篇 bts group
13 篇 glasgow caledoni...
12 篇 school of comput...
11 篇 school of comput...
10 篇 inti-iu-universi...

作者

35 篇 naser ojaroudi p...
27 篇 ahmad jawad
24 篇 parchin naser oj...
22 篇 jawad ahmad
21 篇 canberk berk
18 篇 khan muhammad sh...
16 篇 berk canberk
16 篇 chan hwang see
16 篇 haleh jahanbakhs...
15 篇 hafez mohamed
15 篇 mohamed hafez
15 篇 solyman ahmed
14 篇 mohammad alibakh...
13 篇 alibakhshikenari...
13 篇 ahmed solyman
12 篇 ahmed s.i. amar
12 篇 see chan hwang
12 篇 abd-alhameed rae...
12 篇 muhammad shahbaz...
11 篇 hani attar

语言

869 篇 英文
87 篇 其他
4 篇 中文

检索条件"机构=School of Computing Engineering and the Built Environment"

共 961 条记录，以下是31-40 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：

Advancements in predictive maintenance modelling for industrial electrical motors: Integrating machine learning and sensor technologies

Advancements in predictive maintenance modelling for industr...

引用

作者： Hanifi, Shahram Alkali, Babakalli Lindsay, Gordon Waters, Mark McGlinchey, Don School of Computing Engineering and Built Environment Glasgow Caledonian University Glasgow United Kingdom

Predictive maintenance is crucial in modern industrial settings, aiming to optimise performance, minimise downtime, and prevent costly equipment failures. The advancements in the use of machine learning techniques, sensor technologies, and data acquisition systems within Industry 4.0 has generated a lot of interest lately. In this paper, a novel predictive maintenance model is developed using machine learning approach for modelling vibration and temperature data collection for electrical motors of power press machines in Mitsubishi Electric Air Conditioning production (MACE) factory in the United Kingdom. Vibration and temperature data were collected using Bluetooth sensors installed on the motors, transmitted to a central data storage system for further analysis. To ensure the accuracy as well as the quality and reliability of the collected data sets for further analysis, pre-processing of the data was conducted, and the Isolation Forest (IF) outlier detection method was employed to filter out the anomalies. Machine learning algorithms including Auto-Regressive Integrated Moving Average (ARIMA), Random Forest (RF), and Long Short-Term Memory (LSTM) networks were employed for predicting vibration signals, with hyperparameter tuning conducted using Sequential Model-Based optimisation (SMBO) with the Tree Parzen Estimator (TPE). The results and concluding remarks presented in this paper show how the performance of the optimized ARIMA model can be used in predicting future vibration levels of the electrical motor. The residual analysis is also used to monitor discrepancies between predicted and observed vibration values, enabling proactive identification of emerging issues. © 2024

关键词： Hyperparameter optimisation Machine learning Predictive maintenance Sensor technologies Vibration analysis

来源：评论

学校读者我要写书评

暂无评论

A computational study of a solid oxide fuel cell - turbofan engine hybrid propulsion system fuelled by ammonia and hydrogen.

A computational study of a solid oxide fuel cell - turbofan ...

引用

AIAA Science and Technology Forum and Exposition, AIAA SciTech Forum 2025

作者： Wagner, Luca Tingas, Efstathios-Al. School of Computing Engineering and the Built Environment Edinburgh Napier University EdinburghEH10 5DT United Kingdom

ISBN: (数字)9781624107238

ISBN: (纸本)9781624107238

This study presents the theoretical evaluation of a hybrid aero-propulsion system that combines a Solid Oxide Fuel Cell (SOFC) with a commercial turbofan engine (JT9D), fuelled by an ammonia and hydrogen fuel blend, the latter produced by an onboard fuel reformer. As concerns over emissions from the aviation sector continue to rise along with the ongoing search for sustainable energy alternatives, this research investigates the thermodynamic performance, environmental impacts, and operational efficiencies of the proposed SOFC-turbofan hybrid system. A new hybrid model is developed on the basis of NASA’s well-established T-MATS model. Comprehensive parametric studies are carried out to evaluate the system’s performance under a range of operational parameters, such as altitude, flight conditions, equivalence ratio, and compressor pressure ratio. Emission analyses revealed that the use of the proposed fuel blend of ammonia/hydrogen resulted in low emissions, demonstrating the system’s potential for significantly reducing the environmental footprint of aviation propulsion systems. This research not only substantiates the feasibility of integrating SOFCs with existing turbofan technology but also highlights the substantial improvements in efficiency and reductions in emissions that such hybrid systems could offer. © 2025, American Institute of Aeronautics and Astronautics Inc, AIAA. All rights reserved.

关键词： NASA

来源：评论

学校读者我要写书评

暂无评论

Enhancing Transformer Ageing Prediction in NOMs Methodology: Incorporating Demand Data Analysis 59

Enhancing Transformer Ageing Prediction in NOMs Methodology:...

引用

59th International Universities Power engineering Conference, UPEC 2024

作者： Anwar, Arshad Syed Farrag, Mohamed Emad Baird, Jim Glasgow Caledonian University School of Computing Engineering and Built Environment Glasgow United Kingdom Scotland Helwan University Cairo Egypt

ISBN: (纸本)9798350379730

In response to escalating electrical demands from Electric Vehicles and Heat Pumps, the impact on transformer aging has been comprehensively investigated. By incorporating extensive demand data analysis, this study enhances the Network Output Measures methodology to predict transformer aging more accurately. The penetration of Electric Vehicles and adoption of Heat Pumps, which are expected to double the typical household electricity consumption, are quantified and simulated. This simulation uses detailed data from a lead asset database, applying comprehensive equations to predict the aging and degradation of transformers under increased load conditions. This study presents a critical advancement in the understanding and management of transformer aging under the increased stress imposed by modern energy demands. The results highlight the accelerated aging process, quantified as a rate substantially higher than under normal conditions. A revised approach to the Network Output Measures methodology is proposed, emphasizing the need for integrating real-time monitoring and advanced analytics to better manage the life cycle of electrical network assets. © 2024 IEEE.

关键词： Demand response

来源：评论

学校读者我要写书评

暂无评论

Using STEAM Principles and Experiences to Critique and Enhance a Transdisciplinary Collaboration Framework

Using STEAM Principles and Experiences to Critique and Enhan...

引用

2023 IEEE IFEES World engineering Education Forum and Global engineering Deans Council, WEEF-GEDC 2023

作者： Rodier, Chantal Carter, Claudia University of Ottawa School of Engineering Design & Teaching Innovation Faculty of Engineering Ottawa Canada Birmingham City University College of the Built Environment Faculty of Computing Engineering and Built Environment United Kingdom

ISBN: (纸本)9798350316025

STEAM interdisciplinary collaborations are essential to address complex 21st-century challenges, as they can offer new ways of learning, knowing, and collaborating with more holistic perspectives on the world. Transdisciplinary problem framing and knowledge creation can furthermore benefit deep and applied learning and guide projects. However, setting up teams across academic disciplines and practices to achieve meaningful and effective outcomes is challenging, and a coherent framework and repeatable approach could aid in their success. Today, no framework for STEAM collaborations addresses the entire collaboration cycle between project partners from diverse academic disciplines and non-academic backgrounds to systematically achieve transdisciplinary knowledge creation. This study presents a STEAM evaluation of a general framework for conducting transdisciplinary research (TDR) in three phases: TDR initiation, TDR management, and transdisciplinary knowledge exchange. This STEAM evaluation was based on the researchers' experience and network of STEAM research and recent projects. A particular focus in this paper is to share insights into the challenges faced by diverse disciplinary collaborations with engineering students and engineers in achieving transdisciplinarity and how a STEAM lens to a TDR framework may help to prepare for or overcome these challenges. The study is expected to contribute to the development of a comprehensive framework for STEAM collaborations that could be used by researchers and practitioners to achieve transdisciplinary knowledge creation, be that in their research or teaching. © 2023 IEEE.

关键词： Steam

来源：评论

学校读者我要写书评

暂无评论

Study of Energy Saving Potential of Solar Shading Devices in Various Climates 5th

Study of Energy Saving Potential of Solar Shading Devices in...

引用

5th International Conference on Building Energy and environment, COBEE 2022

作者： Turner, Lewis Yang, Siliang White, Michael School of Built Environment Engineering and Computing Leeds Beckett University West Yorkshire Leeds United Kingdom

ISBN: (纸本)9789811998218

Research studies previously performed using a singular climate had shown that certain solar shading devices have the potential for energy savings for buildings. In this paper, a commercial building was studied using the DesignBuilder programme to identify the solar performance of the building. The model represented a typical commercial building with standard properties. This study allowed for comparison for horizontal louvre, overhang and vertical shading types in various climates (Florida, Cairo, Leeds and Reykjavik) for a year presented in terms of monthly energy demand. Comparative analysis identified that the horizontal louvre type, which consisted of 5-louvre with 400 mm spacing between the adjacent louvres, performed best to reduce the annual energy usage for Florida (4191 kWh), Cairo (5194 kWh), Leeds (1882 kWh) and Reykjavik (957 kWh). In general, all environments showed increases through heating and lighting, but proportionally cooling reduction was higher annually. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Energy conservation

来源：评论

学校读者我要写书评

暂无评论

Optimal DC link voltage stabilisation technique for a grid-connected PV system

Optimal DC link voltage stabilisation technique for a grid-c...

引用

2024 Energy Conversion Congress and Expo Europe, ECCE Europe 2024

作者： Khan, Taimoor Ahmad Kahwash, Fadi Ahmed, Jubaer Goh, Keng Edinburgh Napier University School of Computing Engineering & Built Environment EdinburghEH10 5DT United Kingdom

ISBN: (纸本)9798350364446

The utilisation of renewable energy (RES) powered microgrids has seen significant growth due to environmental concerns. These RES resources are often integrated with the grid through a DC link. Maintaining the DC link voltage at a specified level is of prime importance to ensure smooth and efficient supply in the presence of fluctuating RES. Therefore, this work presents a fractional order super twisting sliding mode control technique (FOSTSMC) to stabilise the voltage, reduce response time, and overshoot at the DC link of a grid-connected microgrid. The microgrid under study is composed of a photovoltaic (PV) system with an incremental conductance and integral regulator-based maximum power point tracking (IC+IR MPPT) algorithm. Firstly, a conventional proportional-integral (PI) control-based voltage control technique is implemented, which is considered a benchmark technique for comparison and validation purposes. Secondly, the proposed control technique is implemented to control the DC link voltage to a reference voltage in constant and varying solar irradiance. Additionally, an Ant colony optimisation algorithm is used to optimally tune the coefficients of the FOSTSMC controller. The simulation results demonstrated the effectiveness of the ACO-FOSTSMC which exhibits 72% lower settling time, and no overshoot when compared with the benchmark technique. The results of the PI controller exhibit a longer settling time with a 23.6% overshoot, and 26% undershoot. The results indicated that the proposed control strategy can be effective in maintaining the DC link voltage to ensure a smooth power supply. © 2024 IEEE.

关键词： Microgrids

来源：评论

学校读者我要写书评

暂无评论

Enhancing Security and Privacy in Federated Learning for Connected Autonomous Vehicles With Lightweight Blockchain and Binius ZeroKnowledge Proofs 17

Enhancing Security and Privacy in Federated Learning for Con...

引用

17th International Conference on Security of Information and Networks, SIN 2024

作者： Andriambelo, Ny Hasina Moradpoor, Naghmeh University of Antananarivo Cognitive Sciences and Applications Madagascar School of Computing Engineering and the Built Environment Edinburgh Napier University Edinburgh United Kingdom

ISBN: (纸本)9798331509736

The rise of Autonomous Vehicles (AVs) brings with it the need for secure and privacy-preserving machine learning models. Federated Learning (FL) allows AVs to collaboratively train models while keeping raw data localized. However, traditional FL systems are vulnerable to security threats, including adversarial attacks, data breaches, and dependency on a central aggregator, which can be a single point of failure. To address these concerns, this paper introduces a peer-to-peer decentralized federated learning system that integrates lightweight blockchain technology and Binius Zero- Knowledge Proofs (ZKPs) to enhance security and privacy. In this system, Binius ZKPs ensure that model updates are cryptographically verified without exposing sensitive information, guaranteeing data confidentiality and integrity during the learning process. The lightweight blockchain framework secures the network by creating an immutable, decentralized record of all model updates, thus preventing tampering, fraud, or unauthorized modifications. This decentralized approach eliminates the need for a central aggregator, significantly enhancing system resilience to attacks and making it suitable for dynamic environments like AV networks. Additionally, the system's design includes Byzantine resilience, providing protection against adversarial nodes and ensuring that the global model aggregation process remains robust even in the presence of malicious actors. Extensive performance evaluations demonstrate that the system achieves low-latency, scalability, and efficient resource usage while maintaining strong security and privacy guarantees, making it an ideal solution for real-time federated learning in autonomous vehicle networks. The proposed framework not only ensures privacy but also fosters trust among participants in a fully decentralized environment. © 2024 IEEE.

关键词： Federated learning

来源：评论

学校读者我要写书评

暂无评论

Scalable Machine Learning Architectures for IPA-Driven Maintenance Task Allocation in Large-Scale Building Portfolios 24

Scalable Machine Learning Architectures for IPA-Driven Maint...

引用

7th International Conference on Information Science and Systems, ICISS 2024

作者： Huang, Zhimeng Liu, Xiaodong Romdhani, Imed Shih, Chi-Sheng School of Computing Engineering and Built Environment Edinburgh Napier University Edinburgh United Kingdom College of Electrical Engineering and Computer Science National Taiwan University Taipei Taiwan

ISBN: (纸本)9798400717567

This research presents a groundbreaking approach to Building Maintenance Management (BMM) by introducing an Intelligent Process Automation (IPA)-Driven Building Maintenance Management (IBMM) model. This innovative model harnesses the synergies between Artificial Intelligence (AI), Machine Learning (ML), and Internet of Things (IoT) technologies to transition from reactive to proactive and predictive building maintenance strategies. The study highlights the critical gap in current BMM practices—the absence of intelligent systems for anticipating and addressing maintenance issues before they escalate. Through an extensive literature review, the transformative potential of AI and IoT for enhancing building maintenance management within smart cities is explored, establishing a foundation for the IBMM model’s application. The core of this research lies in its novel application of scalable machine learning architectures to automate and optimize maintenance task allocation in large-scale building portfolios. The practicality of the IBMM model is demonstrated via a proof of concept (POC) in an industrial setting, evidencing its capacity to improve efficiency, reduce costs, and bolster sustainability in building maintenance operations. The model epitomizes a paradigm shift in BMM by integrating IPA, which combines AI and ML, facilitating automated, intelligent decision-making and task allocation. Among its advancements, the IBMM model introduces enhanced predictive maintenance through real-time data analysis, adaptive learning and optimization, automated decision-making, and human-machine collaboration, contributing to energy efficiency and alignment with smart city objectives. The paper delineates the methodology, design, and implementation of a machine learning model for engineer task assignments, culminating in a case study that validates the model’s efficacy. This research not only signifies a significant advancement in BMM by leveraging IPA technologies for autonomous p

关键词： Predictive maintenance

来源：评论

学校读者我要写书评

暂无评论

Quality-Diversity Optimisation on a Physical Robot Throu Dynamics-Aware and Reset-Free Learning

Quality-Diversity Optimisation on a Physical Robot Throu Dyn...

引用

2023 Genetic and Evolutionary Computation Conference Companion, GECCO 2023 Companion

作者： Smith, Simón C. Lim, Bryan Janmohamed, Hannah Cully, Antoine School of Computing Engineering and The Built Environment Edinburgh Napier University United Kingdom Department of Computing Imperial College London United Kingdom

ISBN: (纸本)9798400701207

Learning algorithms, like Quality-Diversity (QD), can be used to acquire repertoires of diverse robotics skills. This learning is commonly done via computer simulation due to the large number of evaluations required. However, training in a virtual environment generates a gap between simulation and reality. Here, we build upon the Reset-Free QD (RF-QD) algorithm to learn controllers directly on a physical robot. This method uses a dynamics model, learned from interactions between the robot and the environment, to predict the robot’s behaviour and improve sample efficiency. A behaviour selection policy filters out uninteresting or unsafe policies predicted by the model. RF-QD also includes a recovery policy that returns the robot to a safe zone when it has walked outside of it, allowing continuous learning. We demonstrate that our method enables a physical quadruped robot to learn a repertoire of behaviours in two hours without human supervision. We successfully test the solution repertoire using a maze navigation task. Finally, we compare our approach to the MAP-Elites algorithm. We show that dynamics awareness and a recovery policy are required for training on a physical robot for optimal archive generation. Video available at https://***/BgGNvIsRh7Q © 2023 Copyright held by the owner/author(s).

关键词： Robots

来源：评论

学校读者我要写书评

暂无评论

Green Wave Control Strategy for Optimal Energy Consumption by Model Predictive Control in Electric Vehicles 6

Green Wave Control Strategy for Optimal Energy Consumption b...

引用

6th International Congress on Human-Computer Interaction, Optimization and Robotic Applications, HORA 2024

作者： Ozkan, Furkan Arslan, M. Selcuk Mercan, Hatice Dept. of Mechatronics Engineering Yildiz Technical University Istanbul Turkey School of Computing Engineering and the Built Environment Glasgow Caledonian University Glasgow United Kingdom

ISBN: (纸本)9798350394634

Electric vehicles are becoming increasingly popular as a sustainable alternative to traditional combustion engine vehicles. However, to fully realize the potential of EVs in reducing environmental impact and energy consumption, efficient control strategies are essential. This study explores the application of green wave control using model predictive control for electric vehicles, coupled with energy consumption modeling using neural networks. The strategy consists of three components: a fuel consumption model, a powertrain model, and an optimization algorithm. These components work together to generate an optimal vehicle control plan that minimizes energy usage while maintaining desired performance levels. The green wave control strategy utilizes anticipated roadway information to vary the vehicle's speed within a preset speed window, ensuring an energy-saving operation. The results show that the green wave control strategy can lead to significant fuel savings, making electric vehicles even more sustainable and cost-effective. © 2024 IEEE.

关键词： Energy efficiency

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97页 << < 1 2 3 4 5 6 7 8 9 10 > >>

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：