检索结果-内蒙古大学图书馆

17th International Conference on Multi-disciplinary Trends in Artificial Intelligence, MIWAI 2024

作者： Klaykul, Pattarapon Lee, Wilaiporn Prayote, Akara Department of Computer and Information Science King Mongkut’s University of Technology North Bangkok Bangkok10800 Thailand Department of Electrical and Computer Engineering King Mongkut’s University of Technology North Bangkok Bangkok10800 Thailand

ISBN: (纸本)9789819606917

At toll plazas, congestion frequently occurs during peak hours due to inadequate lane management and misalignment of toll payment lanes with traffic volume and payment patterns. This study proposes a model to determine the optimal number of Manual Toll Collection (MTC) lanes to open or close and to optimize the proportion of Electronic Toll Collection (ETC) lanes. The objective is to minimize average queue lengths while striving to meet secondary-level service requirements. The current system often exceeds these standards, and this study aims to simulate the effects of increasing ETC usage and ETC lanes to improve queue management. The analysis shows that ETC lanes are more efficient and can handle a higher traffic volume than MTC lanes, leading to shorter average queue lengths based on queueing theory. It was observed that lane adjustments are only feasible during off-peak periods, optimizing queue lengths to meet standards. During peak hours, simulations show significant reductions in average queue lengths for various ETC usage scenarios, with reductions of up to 91.96% depending on lane configuration. Additionally, converting one MTC lane to ETC reduces hourly operating costs per lane from 73.17 Baht to 5.42 Baht, a cost reduction of approximately 92.59%. These results emphasize the importance of strategic planning and scheduling for dynamic lane adjustments and advocate for increased ETC adoption through targeted policies and incentives to enhance overall toll plaza efficiency. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Queueing theory

来源：评论

学校读者我要写书评

暂无评论

Live Audio Recognition and Text Conversion system 2

Live Audio Recognition and Text Conversion System

引用

2nd International Conference on Computational Intelligence, Communication technology and Networking, CICTN 2025

作者： Sharma, Pratyaksha Gupta, Sumita Bhavya, Boddu Asmitha Sharma, Khushi Dhir, Saru Gambhir, Sapna Department of Computer Science & Engineering Amity School of Engineering & Technology Amity University UP India Department of Information Technology Amity School of Engineering & Technology Amity University UP India Dept. of Computer Science College of Engineering and Computing George Mason University United States

ISBN: (纸本)9798331530389

With the advancement of technologies, different methods are currently being used for converting spoken language into text. These systems offer a hands-free alternative to traditional input methods, especially for individuals with physical disabilities or those requiring efficient documentation of spoken content. The goal of this study is to review recent advancements in this field and highlight gaps in current research, with a focus on accuracy, language adaptability, ease of use, and the integration of various technologies. We also suggest future directions for enhancing and developing this technology further. © 2025 IEEE.

关键词： Hidden Markov models

来源：评论

学校读者我要写书评

暂无评论

Fingerprint Matching for Noisy and Distorted Patterns using a Siamese Network with ResNet50 and Multihead Attention

引用

IEEE Access 2025年 13卷 88047-88064页

作者： Sawhney, Tinny Sharma, Ashu Abrol, Pawanesh Lehana, Parveen Kumar Chaahat Yadav, Vaishali Scherer, Rafal Kulakov, Oleksii AlZubi, Ahmad Ali University of Jammu DSP Lab Department of Electronics India University of Jammu Department of Computer Science and IT India Chitkara University Institute of Engineering and Technology Chitkara University Department of Computer Science and Engineering Punjab India Manipal University Jaipur Jaipur India Czestochowa University of Technology Department of Artificial Intelligence Częstochowa Poland National Technical University of Ukraine "Igor Sikorsky Kyiv Polytechnic Institute" Faculty of Informatics and Software Engineering Kyiv Ukraine King Saud University Community College Department of Computer Science Riyadh Saudi Arabia

Dermatoglyphics, the study of unique ridge patterns on fingertips, plays a crucial role in fingerprint-based identification. However, skin conditions such as psoriasis, eczema, and verruca vulgaris can distort these patterns. This distortion creates challenges for fingerprint matching systems in forensic science and biometric authentication. This paper proposes a Siamese network with a modified ResNet50 architecture and multihead attention mechanisms to improve fingerprint matching under such distortions. The Siamese network enables the system to compare fingerprint pairs effectively, even under distortions. The modified ResNet50 architecture captures intricate ridge patterns, while the multihead attention mechanisms focus on critical fingerprint regions. Overall, the proposed approach enhances the system’s ability to learn discriminative features. As a result, it can effectively differentiate between matched and unmatched fingerprint pairs, even in the presence of moderate to extreme noise. The proposed system was trained on the Sokoto coventry fingerprint dataset (SOCOFing) and a custom dataset. Experimental results demonstrate high accuracy, with the system achieving 99.47% accuracy under low noise conditions and 90% under moderate noise. However, performance declined to 55.56% under extreme distortions. A comparative analysis highlighted the superiority of the proposed system over widely used minutiae-based methods. The latter exhibited a significant drop in matching scores, falling below 15% for highly distorted fingerprints. These findings underscore the limitations of traditional fingerprint recognition techniques and highlight the effectiveness of proposed approach in handling dermatoglyphic distortions. © 2013 IEEE.

关键词： Feature Selection

来源：评论

学校读者我要写书评

暂无评论

Mapping the Scientific Landscape of Integrated Scheduling Towards Industry 5.0 with A Bibliometric Analysis 6

Mapping the Scientific Landscape of Integrated Scheduling To...

引用

6th International Conference on Industry 4.0 and Smart Manufacturing, ISM 2024

作者： Putri Ardyanti, Anak Agung Ayu Xie, Zhiqiang Karnyoto, Andrea Stevens Pardamean, Bens Estiyanti, Ni Made School of Computer Science and Technology Harbin University of Science and Technology Harbin150000 China Faculty of Information Technology and Design Primakara University Bali 80226 Indonesia Bioinformatics and Data Science Research Center Bina Nusantara University Jakarta11480 Indonesia Computer Science Department BINUS Graduate Program Master of Computer Science Bina Nusantara University Jakarta 11480 Indonesia School of Management and Business University of Debrecen Debrecen Hungary

The industry is rapidly transitioning from the 4.0 era to the 5.0 era, prompting renewed interest among scholars in scheduling problems. They allow operations to process and assemble various components simultaneously. This bibliometric analysis provides a comprehensive understanding of the diverse research perspectives on the potential challenges of integrated scheduling within the framework. We identified 357 Scopus articles and analysed co-occurrence keyword (CNK) by VOSViewer tools and Global Citation Score (GCS) by Scopus tools. The research data obtained from 1993 to 2023 mainly in the subject areas of Engineering, computer science, Maths, and others. CNK identified six cluster keywords, and nine most cited articles based on normalised GCS. These results contribute to our understanding of the development of scheduling algorithms, shifting from an emphasis on manufacturing transfers to contemporary demand-centric research directions. Furthermore, this research provides a valuable perspective for policymakers, plant personnel, and manufacturing managers to make informed decisions. © 2025 The Authors. Published by Elsevier B.V.

关键词： Job shop scheduling

来源：评论

学校读者我要写书评

暂无评论

Optimal Stopping Theory Based Online Node Selection in IoT Networks for Multi-Parameter Federated Learning

IEEE Transactions on Machine Learning in Communications and ...

引用

IEEE Transactions on Machine Learning in Communications and Networking 2025年 3卷 659-676页

作者： Dogan-Tusha, Seda Bouanani, Faissal El Qaraqe, Marwa Hamad Bin Khalifa University Qatar Foundation Division of Information and Computing Technology College of Science and Engineering Doha Qatar Mohammed V University Department of Computer Science Rabat10000 Morocco

Federated Learning (FL) has attracted the interest of researchers since it hinders inefficient resource utilization by developing a global learning model based on local model parameters (LMP). This study introduces a novel optimal stopping theory (OST) based online node selection scheme for low complex and multi-parameter FL procedure in IoT networks. Global model accuracy (GMA) in FL depends on the accuracy of the LMP received by the central entity (CE). It is therefore essential to choose trusty nodes to guarantee a certain level of global model accuracy without inducing additional system complexity. For this reason, the proposed technique in this study utilizes the secretary problem (SP) approach as an OST to perform node selection considering both received signal strength (RSS) and local model accuracy (LMA) of available nodes. By leveraging the SP, the proposed technique employs a stopping rule that maximizes the probability of selecting the node with the best quality, and thereby avoids testing all candidate nodes. To this end, this work provides a mathematical framework for maximizing the selection probability of the best node amongst candidate nodes. Specifically, the developed framework has been used to calculate the weighting coefficients of the RSS and LMA to define the node quality. Comprehensive analysis and simulation results illustrate that the OST based proposed technique outperforms state-of-the-art methods including the random node selection and the offline node selection (exhaustive search methods) in terms of GMA and computational complexity, respectively. © 2023 CCBY.

关键词： Federated learning

来源：评论

学校读者我要写书评

暂无评论

Optimal Selection of Frequency Band and Wavelet Scattering for Feature Extraction in Multi-class EEG Classification

引用

SN computer science 2025年第2期6卷 1-17页

作者： Shirodkar, Vaishali Edla, Damodar Reddy Kumari, Annu Department of Computer Science and Engineering National Institute of Technology Goa Kottamoll Plateau Goa Cuncolim 403703 India Information Technology Department Goa College of Engineering Farmagudi Goa Ponda 403401 India

Brain–computer interface (BCI) technology has huge potential to transform human–computer interaction across multiple disciplines. Despite efforts, achieving high accuracy in motor imagery (MI) task classification remains difficult. This proposed solution addresses the MI tasks classification challenge utilizing the BCI IV 2a and 2b datasets. Using optimization methods, optimal frequency bands associated with event-related desynchronization were identified to enhance classification accuracy to 90.44% for 2a and 93.78% for 2b datasets. Following band selection, the electroencephalography data were pre-processed, focusing on the identified frequency band, and quadratic interpolation was employed for data augmentation, introducing synthetic data points to improve model generalization and robustness. The proposed method used wavelet scattering transform for feature extraction, which captures both temporal and spectral characteristics. The extracted features set was reduced using common spatial patterns, which utilizes spatial distribution to find discriminative spatial filters. After feature selection simple classifier, recurrent neural network was implemented and compared with many state-of-the-art methods. The system proposed is computationally efficient and lightweight making it applicable to IoT-based applications. The proposed methodology shows that the technique improves BCI classification performance, providing useful insights for applications in healthcare and assistive technologies. © The Author(s), under exclusive licence to Springer Nature Singapore Pte Ltd. 2025.

关键词： Common spatial patterns Event-related desynchronization Interpolation Motor imagery Optimization Recurrent neural network Wavelet scattering transform

来源：评论

学校读者我要写书评

暂无评论

Developing a multi-user virtual reality training system for emergency medical technicians: Determinants of acceptance and adoption

引用

Educational technology and Society 2025年第2期28卷 416-433页

作者： Chen, Shih-Yeh Lai, Ying-Hsun Lin, Pei-Hsuan Su, Yu-Sheng Department of Engineering Science National Cheng Kung University Taiwan Department of Computer Science and Information Engineering National Taitung University Taiwan Department of Information Management National Taichung University of Science and Technology Taiwan Department of Computer Science and Information Engineering National Chung Cheng University Taiwan Advanced Institute of Manufacturing with High-tech Innovations National Chung Cheng University Taiwan Department of Computer Science and Engineering National Taiwan Ocean University Taiwan

There is an increasing international focus on multi-user virtual reality (VR) training for all emergency medical technicians within the framework of their respective disaster medical preparedness initiatives. While multiuser VR is often deployed in a variety of digital educational settings, it has not been meaningfully explored in emergency medicine. This study was conducted to fill this research gap by developing a multi-user VR training system for the donning and doffing procedures associated with Level C protective gear. Furthermore, the current investigation also considered the determinants influencing whether emergency medical technicians are willing to adopt and accept multi-user VR training courses via conceptualizing the extended unified theory of acceptance and use of technology. An empirical survey was conducted involving 80 emergency medical technicians in the eastern region of Taiwan to evaluate their experiences with the multi-user VR system. The data were analyzed using Partial Least Squares Structural Equation Modeling, and the results showed that performance expectancy, social impact, facilitating conditions, price value, and habit significantly influenced emergency medical technicians’ readiness to adopt multi-user VR training courses. Moreover, performance expectancy, facilitating conditions, and behavioral intention emerged as pivotal determinants of course adoption. However, effort expectancy and hedonic motivation did not exert a significant influence on adoption behavior. The findings of the study have important theoretical and practical implications. © (2024), (International Forum of Educational technology and Society). All Rights Reserved.

关键词： Behavioral intention Emergency medical preparedness Extended unified theory of acceptance and use of technology (UTAUT 2) Multi-user virtual reality Virtual environment for emergency medical technicians

来源：评论

学校读者我要写书评

暂无评论

An integrated strategy of AEF attribute evaluation for reliable thunderstorm detection

引用

Digital Communications and Networks 2025年第1期11卷 234-245页

作者： Xu Yang Hongyan Xing Xinyuan Ji Xin Su Witold Pedrycz School of Electronics and Information Engineering Nanjing University of Information Science and TechnologyNanjing 210044China Department of Electrical and Computer Engineering University of AlbertaEdmonton AB T6G 2R3Canada College of Internet of Things Engineering Hohai UniversityChangzhou 213022China Systems Research Institute Polish Academy of Sciences00-901 WarsawPoland Department of Computer Engineering Faculty of Engineering and Natural SciencesIstinye UniversitySariyer/IstanbulTurkey

Thunderstorm detection based on the Atmospheric Electric Field(AEF)has evolved from time-domain models to space-domain *** is especially important to evaluate and determine the particularly Weather Attribute(WA),which is directly related to the detection reliability and *** this paper,a strategy is proposed to integrate three currently competitive WA's evaluation ***,a conventional evaluation method based on AEF statistical indicators is *** evaluation approaches include competing AEF-based predicted value intervals,and AEF classification based on fuzzy *** AEF attributes contribute to a more accurate AEF classification to different *** resulting dynamic weighting applied to these attributes improves the classification *** evaluation method is applied to evaluate the WA of a particular AEF,to obtain the corresponding evaluation *** integration in the proposed strategy takes the form of a score *** cumulative score levels correspond to different final WA *** imaging is performed to visualize thunderstorm activities using those AEFs already evaluated to exhibit thunderstorm *** results confirm that the proposed strategy effectively and reliably images thunderstorms,with a 100%accuracy of WA *** is the first study to design an integrated thunderstorm detection strategy from a new perspective of WA evaluation,which provides promising solutions for a more reliable and flexible thunderstorm detection.

关键词： Atmospheric electric field(AEF) Thunderstorm Attribute Fuzzy c-means Imaging

来源：评论

学校读者我要写书评

暂无评论

MLPFormer: MLP-integrated transformer for colorectal histopathology whole slide image segmentation

引用

Neural Computing and Applications 2025年第6期37卷 4651-4661页

作者： Wang, Yuxuan Li, Dan Li, Xuechen Guo, Yan Zuo, Yanfei Shen, Linlin Department of Computer Science Wenzhou-Kean University Wenzhou China School of Electronics and Information Engineering Wuyi University Jiangmen China Department of Histo Pathology Shanghai Histo Pathology Diagnostic Center Shanghai China College of Computer Sicence and Software Engineering Shenzhen University Shenzhen China National Engineering Laboratory for Big Data System Computing Technology Shenzhen University Shenzhen China

Colorectal intraepithelial neoplasia is a precancerous lesion of colorectal cancer, which is mainly diagnosed using pathological images. According to the characteristics of lesions, precancerous lesions can be classified into four different grades, i.e., background, normal, low and high level. However, due to the continuity of lesion development, tissue in different stages has high similarity. Recently, visual transformers have achieved impressive results in different visual tasks, due to their capacity of capturing long-range dependencies. However, due to computational cost, transformer cannot well extract detailed feature, which is important for lesion grading. To accurately segment pathological tissues with high similarity, in this work, we embed the multi-head MLP mixer module in the transformer network to extract cell and edge information. Furthermore, we propose a hierarchical MLP decoder to facilitate multi-scale feature fusion. The proposed transformer, namely MLPFormer, achieves remarkable results against competitive baselines on the Histo-CRC Biopsy dataset. The experimental results demonstrate that MLPFormer significantly outperforms the competitive baselines, i.e., a 3% dice improvement is achieved over the SegFormer series. © The Author(s), under exclusive licence to Springer-Verlag London Ltd., part of Springer Nature 2024.

关键词： Image segmentation

来源：评论

学校读者我要写书评

暂无评论

A Music Recommender system to Identify the Emotional State of a Person Using Machine Learning Algorithms 4

A Music Recommender System to Identify the Emotional State o...

引用

4th International Conference on Sentiment Analysis and Deep Learning, ICSADL 2025

作者： Muruganantham, A. Malarvizhi, C. Divya Vahini, S. Saranya, D. Uthiramoorthy, A. Karnataka Bengaluru India Psg Institute of Advanced Studies Department of Computer Science Coimbatore India Dr.Mahalingam College of Engineering and Technology Department of Computer Applications Tamil Nadu Pollachi India Sri Eshwar College of Engineering Department of Information Technology Coimbatore India Rathinam College of Arts and Science Department of Computer Science India

ISBN: (纸本)9798331523923

In today's digital world, customized recommendation algorithms can improve user experiences in many different areas. Within the sphere of intelligent human-technology interaction, this paper specifically examines a music recommender system driven by machine learning algorithms. It figures out what mood users are in and can provide an appropriate response in real time. The system being propounded in this essay uses advanced technology in facial expression recognition. With the help of a webcam, it aims to accurately detect user emotions, including joy, sadness, and anger. Convolutional Neural Networks (CNN), Recurrent Neural Networks (RNN) and Support Vector Machines (SVM) have been employed to effectively classify people's mood and recommend an appropriate song. Our extensive tests and examinations show that CNN, RNN, and SVM models are all very good at guessing users' moods - with high precision, recall, F1-score, and accuracy percentages. Furthermore, in-depth analyses like confusion matrixes illuminate how well each model serves as an emotion recognizer. This study's findings are representative of future prospects in affective computing around the globe with major implications for intelligent recommendation systems to which it's important that the models are sensitive. In conclusion, the suggested Music Recommender system is something new for taking a more personal view: We can be as deeply entertained as the web allows us to be - make tailored entertainment paths in the digital era. © 2025 IEEE.

关键词： Convolutional neural networks

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：