检索结果-内蒙古大学图书馆

Random hyperbolic graphs in d+1 dimensions

Physical Review E 2024年第5期109卷 054131-054131页

作者： Gabriel Budel Maksim Kitsak Rodrigo Aldecoa Konstantin Zuev Dmitri Krioukov Faculty of Electrical Engineering Mathematics and Computer Science Department of Physics Network Science Institute Department of Computing and Mathematical Sciences Department of Physics Department of Mathematics Department of Electrical & Computer Engineering

We consider random hyperbolic graphs in hyperbolic spaces of any dimension d+1≥2. We present a rescaling of model parameters that casts the random hyperbolic graph model of any dimension to a unified mathematical framework, leaving the degree distribution invariant with respect to the dimension. Unlike the degree distribution, clustering does depend on the dimension, decreasing to 0 at d→∞. We analyze all of the other limiting regimes of the model, and we release a software package that generates random hyperbolic graphs and their limits in hyperbolic spaces of any dimension.

关键词： Network formation & growth Network structure

来源：评论

学校读者我要写书评

暂无评论

Design and Development of a Small-Scale Green Hydrogen Vehicle:Hydrogen Consumption Analysis under Varying Loads for Zero-Emission Transport

引用

Energy engineering 2025年第5期122卷 1788-1803页

作者： Perry Yang Tchie Hunn Hadi Nabipour Afrouzi Research Centre for Sustainable Technologies Faculty of EngineeringComputing and ScienceSwinburne University of TechnologyJalan Simpang TigaKuching93350SarawakMalaysia College of Engineering Faculty of ComputingEngineering and the Built EnvironmentBirmingham City UniversityBirminghamB47XGUK

With growing interest in its potential applications across both stationary and transportation sectors,hydrogen has emerged as a promising alternative for environmentally responsible power *** replacing traditional fuels,hydrogen can significantly reduce greenhouse gas emissions in the transportation *** study focuses on the design and downsizing of a green hydrogen fuel cell car,aiming to scale the concept for larger *** components,including fuel cells,electrolysers,and solar panels,were evaluated through extensive laboratory *** reveal that variations in sunlight impact the solar panel’shydrogenproductionrate,withdifferences of approximately 4.9%attributed to changes in time and *** of consumption rates showed that a 17.4%increase in current consumption leads to a significant reduction in operational *** testing under varying loads demonstrated that higher current demands,such as those from a DC motor,accelerate hydrogen depletion,whereas lower currents extend operational *** results underscore the importance of maximizing solar energy efficiency,reducing reliance on conventional energy sources,and regulating consumption rates to optimize fuel cell *** hydrogen is produced using renewable energy,fuel cell technology is virtually ***,the study highlights the viability of powering vehicles with renewable energy,emphasizing the potential of green hydrogen fuel cell technology as a sustainable transportation solution.

关键词： Environmentally sustainable small scale solar hydrogen fuel cell car

来源：评论

学校读者我要写书评

暂无评论

Non-GPS-based ETA Models Constructed from Historical GPS Data and Traffic Contexts 8

Non-GPS-based ETA Models Constructed from Historical GPS Dat...

引用

8th International Conference on Business and Industrial Research, ICBIR 2023

作者： Phon-Amnuaisuk, Somnuk Tan, Soon-Jiann Khor, Kok-Chin Tham, Mau-Luen Chong, Yung-Wey Omar, Saiful Ibrahim, Noor Farizah Binti Yusoff, Mohd Najwadi Mashud, Idham School of Computing and Informatics Universiti Teknologi Brunei Brunei Universiti Teknologi Brunei Faculty of Engineering Brunei Universiti Tunku Abdul Rahman Lkc Faculty of Engineering and Science Malaysia Universiti Sains Malaysia School of Computer Sciences Malaysia

ISBN: (纸本)9798350399646

Without GPS data, ETA can be estimated with good precision from historical GPS data and the context of the traffic environment. In this paper, the estimated travel duration between bus stops was computed based on historical GPS data with time stamps. Three approaches were employed to compute the duration between bus stops: (i) statistical central tendencies, (ii) nonlinear regression techniques i.e., decision tree regressor, random forest regressor and k-nearest neighbors regressor, and (iii) an ANN predictive model. These three approaches capture different characteristics of the traffic environment. Statistical central tendencies give the overall view of the ETA information while nonlinear regressors can capture context from the time stamps (e.g., weekdays vs holidays). Finally, predicting the duration required to reach the next bus stop based on previous timespans on the same route implicitly captures temporal dynamics of the traffic environment from previous time steps and the ANN predictive model exploits this temporal information. The feasibility of ETA estimation using these three approaches was explained, evaluated and discussed. © 2023 IEEE.

关键词： Decision trees

来源：评论

学校读者我要写书评

暂无评论

Advanced Pedestrian Detection in Low Visibility Scenarios Using UltraLytics YOLOv8 and Kalman Filtering

Advanced Pedestrian Detection in Low Visibility Scenarios Us...

引用

Sustainable Communication Networks and Application (ICSCNA), International Conference on

作者： Sanjay Kumar Reddy Pattem Manjula Rajagopal Nandan Nirujogi Computing Technologies SRM Institute of Science and Technology Chennai Computing Technologies Faculty of Engineering and Technology SRM Institute of Science and Technology Chennai

ISBN: (数字)9798331530013

ISBN: (纸本)9798331530020

Nighttime detection of pedestrians brings important problems such as low light conditions, limitations of sensors, and environmental noise. To tackle this problem, in this study, we propose a novel visual-radar data fusion to enhance a pedestrian detection system using the UltraLytics YOLOv8 deep learning model together with Kalman Filtering technique. The system is based on a Low-Light Vision Infrared Paired (LLVIP) dataset that includes infrared vision data to attenuate the performance decrement of a pedestrian detector in the dark. The combination of infrared cameras and millimeter-wave radar achieves a detection rate of 97.6 % , in which UltraLytics YOLOv8 exhibits excellent object recognition performance by generating accurate spatial & category information from the infrared image; complementary distance and velocity data are obtained by millimeter-wave radar. It brings Kalman Filtering to track the radar-detected pedestrian targets, making the system more robust by predicting target and noise reduction. It was capable of fusing infrared and radar data at decision-level to make the system provide very precise position accurately in even nighttime situations. The experimental results show that the proposed model has improved capability of detection accuracy, robustness, and response time in comparison with the single-sensor system, which is suitable for practical autonomous driving scenarios.

关键词： Pedestrians Accuracy Filtering Working environment noise Data integration Millimeter wave radar Robustness Data models Kalman filters Autonomous vehicles

来源：评论

学校读者我要写书评

暂无评论

Recent Advances in Edge computing for 6G

Recent Advances in Edge Computing for 6G

引用

2022 International Conference on Intelligent Technology, System and Service for Internet of Everything, ITSS-IoE 2022

作者： Alawadhi, Abdulwadood Almogahed, Abdullah University of Science and Technology Faculty of Engineering and Computing Department of Computers and Information Technology Yemen Taiz University Faculty of Engineering and Information Technology Department of Software Engineering Taiz Yemen

ISBN: (数字)9781665459983

ISBN: (纸本)9781665459983

Edge computing is a new technology that enables 6G development by bringing cloud capabilities closer to end users to overcome traditional cloud flaws such as high latency and a lack of security. Few studies identify recent advances, challenges, and opportunities in 6G edge computing. As a result, this paper presents a review to identify recent advances in edge computing in 6G. It also discusses the challenges and opportunities of such new trends in the computing landscape. The paper identifies challenges (security and privacy, offloading and task division, bandwidth, service management, advanced communication, general-purpose computing on edge nodes, quantum computing and edge computing, and IoT heterogeneous platforms) as well as opportunities (academic-industry collaborations, algorithms and libraries that are lightweight and virtualization and micro-operating systems). Finally, some conclusions have been drawn after identifying current research directions. © 2022 IEEE.

关键词： Internet of things

来源：评论

学校读者我要写书评

暂无评论

AI-enhanced cognitive behavioral therapy with novel ontological and pattern-based thought segmentation

引用

International Journal of Information Technology (Singapore) 2025年 1-8页

作者： Vidanage, Kaneeka Maduranga, M.W.P. Department of Computer Science Faculty of Computing General Sir John Kotelawala Defense University Kandawala Road 10390 Dehiwala-Mount Lavinia Sri Lanka Department of Electrical and Electronic Engineering University of Sri Jayewardenepura Nugegoda 10500 Sri Lanka

Use of Artificial Intelligence (AI) has contributed to improving the quality standards of the healthcare solutions provided for the patients. Therefore, healthcare informatics has been recognized as a very demanding discipline which is on constant evolution. Thus, the utilization of AI advancements to uplift the treatment strategies are mainly confined to provide solutions linked with treating physical ailments. Application of AI to improve psychotherapeutic treatments are very naïve. However, psychological well-being is also a vital requirement ensuring the physical well-being of an individual. Cognitive Behavioral Therapy (CBT) is recognized as the world's most acceptable psychotherapeutic treatment tool. Consequently, with the involvement of the psychological consultants and referring the CBT manuals, specialized ontological structure has been orchestrated to assess the human “thoughts” as per the CBT guidelines. The designed ontological structure has been accompanied with a specialized knowledge elicitation algorithm designed to reason the knowledge constructs embedded in the ontology against the stakeholder`s input. Operational effectiveness of this entire pipeline has been assessed via both quantitative and qualitative measurements under the observation of the consultants. The entire prototype designed yielded an overall accuracy of 82%. This entire pipeline compiled can be considered as a novel contribution enriching the expansion of the application of AI into the psychotherapeutic domain as well. © Bharati Vidyapeeth's Institute of Computer Applications and Management 2025.

关键词： AI CBT Ontology Psychotherapy RegEX

来源：评论

学校读者我要写书评

暂无评论

Maize EfficientNet Fusion: Advancing Maize Disease Detection with MF-NET 25

Maize EfficientNet Fusion: Advancing Maize Disease Detection...

引用

25th International Conference on Digital Image computing: Techniques and Applications, DICTA 2024

作者： Khalid, Fatima Hanif, Muhammad Ul Ain, Qurat Ghulam Ishaq Khan Institute of Engineering Sciences and Engineering Faculty of Computer Science and Engineering KPK Topi Pakistan Ghulam Ishaq Khan Institute of Engineering Sciences and Engineering Aerial Robotics and Vision Lab KPK Topi Pakistan Shifa Tameer-E-Millat University Department of Computing Islamabad Pakistan

ISBN: (纸本)9798350379037

Maize is a vital global crop, essential for food security but highly susceptible to diseases that threaten yield and quality. Traditional methods for detecting these diseases are computationally intensive and rely on high-quality images, limiting their practical use in diverse field conditions. This research addresses these challenges by proposing MF-Net, a novel model that leverages two EfficientNet-b0 architectures with ReLU and Swish activation functions. Our approach involves partially training Model R with frozen early layers using ReLU, and fully training Model S with Swish activation for enhanced optimization and robustness. We employ model concatenation and feature fusion techniques to create a lightweight yet powerful model, complemented by additional layers for improved feature extraction and regularization. Experimental results on the Corn Disease and Severity (CD&S) dataset are compelling: MF-Net achieves a remarkable 95.7% accuracy and 96% precision in disease classification, and 88.3% accuracy and 88.46% precision in severity level detection. These results highlight the model's effectiveness under challenging conditions such as cluttered backgrounds and variable lighting, significantly reducing computation time without compromising accuracy. Hence, MF-Net presents an innovative and efficient solution for maize disease detection and severity assessment, offering significant advancements for agricultural practices and crop management. © 2024 IEEE.

关键词： CD&S Dataset EffiecientNet-b0 Fused Truncated EfficientNet Maize Disease Maize Severity Level

来源：评论

学校读者我要写书评

暂无评论

SIMPLIFIED FATIGUE LOAD CASES ASSESSMENT IN TENSION LEG PLATFORM FLOATING OFFSHORE WIND STRUCTURAL ANALYSIS 43

SIMPLIFIED FATIGUE LOAD CASES ASSESSMENT IN TENSION LEG PLAT...

引用

ASME 2024 43rd International Conference on Ocean, Offshore and Arctic engineering, OMAE 2024

作者： Meng, Xun Wang, Zhaoyue Lu, Qing Rawlinson-Smith, Robert Greaves, Deborah Wang, Wenping Fu, Qiang Ocean University of China Qingdao China School of Engineering Computing and Mathematics Faculty of Science and Engineering University of Plymouth Plymouth United Kingdom Shenzhen Intelligent Ocean Engineering Innovation Center Limited Shenzhen China Yantai CIMC Ocean Engineering Co. Ltd Yantai China

ISBN: (纸本)9780791887851

Floating offshore wind turbines (FOWTs) are considered a promising solution for wind energy harvesting in deep water, and optimized designs will bring the costs of FOWTs down and increase profitability. However, verifying the fatigue lifetime for the FOWT optimization model requires a large number of loading situations with computationally expensive response analyses. Fatigue damage calculated for six sets of simplified fatigue load cases (FLCs), with different combinations of turbine loads and wave loads, were compared using time-domain simulations in combination with Miner's Rule, which allows for the identification of optimal parameters in a lifetime perspective, and fair comparisons between the different contribution from loading of the wind turbine and environmental waves. The chosen FLC for fatigue damage verification of the floater scantling model in the present work is applicable for the preliminary design of Tension Leg Platform (TLP) FOWTs, where they can provide a starting design for the detailed design phases. The methodologies can be further extended to account for different FOWT concepts, additional design parameters, and other load combination cases. Copyright © 2024 by ASME.

关键词： Fatigue damage

来源：评论

学校读者我要写书评

暂无评论

Sinhala Named Entity Recognition Model: Domain-Specific Classes in Sports 4

Sinhala Named Entity Recognition Model: Domain-Specific Clas...

引用

4th International Conference on Advancements in computing, ICAC 2022

作者： Wijesinghe, W.M.S.K. Tissera, Muditha Department of Statistics and Computer Science Faculty of Science University of Kelaniya Sri Lanka Department of Software Engineering Faculty of Computing & Technology University of Kelaniya Sri Lanka

ISBN: (纸本)9798350398090

Named Entity Recognition (NER) is one of the crucial and vital subtasks that must be solved in most Natural Language Processing (NLP) tasks. However, constructing a NER system for the Sinhala Language is challenging. Because it comes under the category of low-resource languages. Therefore, the proposed approach attempted designing a mechanism to identify specific named entities in the sports domain. Firstly, a domain-specific corpus was built using Sinhala sport e-News articles. Then a semi-automated, rule-based component named as "Class_Label_Suggester" was built to annotate pre-defined named entities. After auto annotation, the outcome was further validated manually with a little effort. Finally, it was trained using the annotated data. Linear Perceptron, Stochastic Gradient Descent (SGD), Multinomial Naive Bayes (MNB), and Passive Aggressive classifiers were used to train the NER model. Though, the above Machine Learning (ML) algorithms showed approximately 98% accuracy, the MNB model demonstrated highest accuracy for the identified class labels of which, 99.76% for 'Ground', 99.53% for 'School', 98.55% for 'Tournament', and 97.87% for 'Other' classes. Additionally, high precision values of the above classes were 81%, 72%, 62%, and 98% respectively. An accurately annotated Sinhala dataset and the trained Sinhala NER model are main contributions of the study. © 2022 IEEE.

关键词： Sports

来源：评论

学校读者我要写书评

暂无评论

Intelligent Digital Twin Communication Framework for Addressing Accuracy and Timeliness Tradeoff in Resource-Constrained Networks

引用

IEEE Transactions on Cognitive Communications and Networking 2024年第3期11卷 1954-1965页

作者： Cakir, Lal Verda Thomson, Craig J. Ozdem, Mehmet Canberk, Berk Nguyen, Van-Linh Duong, Trung Q. Edinburgh Napier University School of Computing Engineering and Built Environment EdinburghEH10 5DT United Kingdom BTS Group Istanbul Turkey Turk Telekom Turkey Department of Computer Science and Information Engineering Taiwan Memorial University of Newfoundland Faculty of Engineering and Applied Science St. John'sNLA1C 5S7 Canada Queen's University Belfast School of Electronics Electrical Engineering and Computer Science BelfastBT7 1NN United Kingdom

The accuracy and timeliness tradeoff prevents Digital Twins (DTs) from realizing their full potential. High accuracy is crucial for decision-making, and timeliness is equally essential for responsiveness. Therefore, this tradeoff in DT communication must be addressed to achieve DT synchronization. Previous studies identified the issue but considered the problem as maximizing data transfer, which is infeasible due to resource constraints. To facilitate this, we quantify accuracy and timeliness as E and φ and define the problem as joint minimisation. We then introduce the Intelligent DT Communication (IDTC) Framework to solve the problem, which includes machine learning-based Predictive Synchronization (PS) and DT synchronization management (DTSYNC) protocol. Here, PS uses imputation and forecasting to generate future values, which are utilized to update DT at the projected time points. This mechanism of PS enables lowering E and φ of the communication. Subsequently, we utilize the DTSYNC to control synchronization and optimise the twining frequency ft. We evaluate the proposed framework using a public dataset and compare its performance with several state-of-the-art studies in a real-world scenario. Evaluation results indicate that IDTC outperforms the existing methods by 80% for E and 84% for φ while enabling ft adjustment, resulting in 3.8 times goodput improvement. © 2015 IEEE.

关键词： Adversarial machine learning

来源：评论

学校读者我要写书评

暂无评论

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：

请选择收藏分类：

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

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：