检索结果-内蒙古大学图书馆

4th International Conference on Ubiquitous computing and Intelligent Information Systems, ICUIS 2024

作者： Srishwal, Dhruvi Shibu, P.S. Vardan, Harsha Sajjad Ibrahim, A. Gouthaman, P. School of Computing College of Engineering and Technology Srm Institute of Science and Technology Department Of Networking And Communications Kattankulathur603203 India Srm Institute of Science and Technology Faculty of Engineering and Technology and Technology Department Of Networking And Communications Kattankulathur603203 India

ISBN: (纸本)9798331529635

Heart arrhythmias, if not detected early, can lead to severe conditions like stroke or heart failure, making timely and accurate classification critical. Traditional methods of analyzing Electrocardiogram (ECG) data are manual, time-consuming, and prone to errors due to the complexity of ECG signals. This paper presents an automated approach for arrhythmia classification using vector databases and similarity search algorithms. By converting raw ECG time-series data into vectorized representations, the system enables efficient pattern recognition and real-time analysis. Machine learning models applied to the vectorized data enhance classification accuracy, while the use of a vector database allows for quick similarity searches, facilitating real-time comparison of patient data with known arrhythmia patterns. The proposed method significantly reduces analysis time and increases precision, offering a robust framework for real-time monitoring and early detection, thereby improving patient outcomes and enabling timely medical interventions. © 2024 IEEE.

关键词： Dimensionality reduction

来源：评论

学校读者我要写书评

暂无评论

Dual-Task Dialogue Understanding

Dual-Task Dialogue Understanding

引用

2024 SICSA Workshop on Reasoning, Evaluation and Application of Large Language Models, SICSA-REALLM 2024

作者： Anwar, Sibgha Wiratunga, Nirmalie Snaith, Mark School of Computing Engineering and Technology Robert Gordon University AberdeenAB10 7GJ United Kingdom

In dialogue systems, utterances do not occur in isolation. One conversation might involve interactions between several speakers. It’s crucial to determine the intentions behind utterances in multi-party conversations when more than two interlocutors are interacting. Beyond directly capturing the speaker’s intention, our proposed model first focuses on identifying speakers from utterances, and based on this knowledge, it classifies the corresponding dialogue acts. For the speaker identification process, the study extracted linguistic features related to speakers from conversations and incorporated them during the fine-tuning process, which is particularly beneficial in dealing with multiple speakers. After that our model aims to improve dialogue act recognition baselines on shorter utterances by implementing a pipe-lining approach based on speaker model predictions. The effectiveness of our approach is demonstrated using two benchmark datasets, MRDA and SwDA, which are based on multiparty and twofold conversations, respectively. © 2024 Copyright for this paper by its authors.

关键词： Speech recognition

来源：评论

学校读者我要写书评

暂无评论

Investigating Naive Bayes Algorithms for Network Time Series Analysis 5th

Investigating Naive Bayes Algorithms for Network Time Series...

引用

5th International Conference on Data Science, Machine Learning and Applications, ICDSMLA 2023

作者： Nidhya, M.S. Verma, Sunny Mohamed, H. B. Asif Agarwal, Trapty Karnataka Bangalore India Department of Electronic & Communication Engineering School of Engineering and Computing Dev Bhoomi Uttarakhand University Navgaon Manduwala Dehradun India School of Computer Science and Engineering Presidency University Karnataka Bengaluru India Maharishi School of Engineering & Technology Maharishi University of Information Technology Uttar Pradesh Lucknow India

ISBN: (纸本)9789819780426

Naive Bayes algorithms are a class of supervised gadget mastering models which are typically used for a variety of obligations, together with statistics mining, textual content category, and regression. This studies explores the ability of applying these algorithms to the evaluation of community time series statistics. Thru empirical experimentation, the effectiveness of diverse Naive Bayes algorithms is as compared the usage of empirical performance metrics. The results show that Naive Bayes algorithms can successfully be used to identify patterns in community time series, carry out regression responsibilities, and offer feature representations. The results spotlight the capability of Naive Bayes algorithms as a tool for the evaluation of network time collection statistics. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Time series

来源：评论

学校读者我要写书评

暂无评论

Machine Learning Algorithms for Auto Insurance Fraud detection: Comparative Study 1

Machine Learning Algorithms for Auto Insurance Fraud detecti...

引用

1st IEEE International Conference on Green Industrial Electronics and Sustainable Technologies, GIEST 2024

作者： Gupta, Prashant K. Bhatnagar, Risabh Tyagi, Shalu Jain, Achin Panwar, Arvind Dubey, Arun Kumar Bennett University School of Computer Science & Engineering Technology Uttar Pradesh India Bharati Vidyapeeth College of Engineering Delhi India Raj Kumar Goel Institute of Technology Ghaziabad India Galgotias University School of Computing Science Engineering India

ISBN: (纸本)9798331540142

Insurance fraud is a massive burden for the industry and causes billions in economic damage yearly. This research deals with the difficulties in fraud detection of insurance companies, focusing on machine learning approaches. Based on factual data from an insurance company the study kind use SVM, Decision Tree model, Random Forest Ada Boost Gradient Boosting and Stochastic Gradient Boosting, XGBoosts Extra Trees in this case. The assessment of this models is through various proper analysis which include confusion matrix and main performance metrics like accuracy, precision, recall, F1 and so on. This study aims to provide insights that would be beneficial to improve the fraud detection strategy in insurance industry by comparing the performance of models used. © 2024 IEEE.

关键词： Support vector machines

来源：评论

学校读者我要写书评

暂无评论

Multi-Criteria Decision-Making for Energy Management in Smart Homes Using Hybridized Neuro-Fuzzy Approach

引用

Distributed Generation and Alternative Energy Journal 2024年第1期39卷 83-109页

作者： Anbazhagu, U.V. Koti, Manjula Sanjay Muthukumaran, V. Geetha, V. Munrathnam, Meram Department of Computing Technologies School of Computing Faculty of Engineering and Technology SRM Institute of Science and Technology SRM Nagar Kattankulathur TN Chennai India Department of MCA Dayananda Sagar Academy of Technology and Management Bangalore560082 India Department of Mathematics College of Engineering and Technology SRM Institute of Science and Technology Tamilnadu Kattankulathur Campus 603 203 India Department of Computer Science School of Applied Sciences REVA University Bangalore India Department of Mathematics Rajiv Gandhi University of Knowledge Technologies R.k.Valley Idupulapaya Andhra Pradesh Kadapa516330 India

The necessity for smart energy oversight solutions has arisen in response to the rising popularity of energy-efficient home automation and other energy-saving technologies. Optimizing smart home energy use using multi-criteria decision-making (MCDM) is a proven methodology. However, the procedure for making decisions and MCDM’s capacity to handle various criteria are typically limiting factors. Hybrid methods, which integrate multiple decision-making approaches like Fuzzy Logic (FL) and Modular Neural Networks (MNN), could potentially be able to circumvent these restrictions and boost energy management systems’ efficacy and precision. This investigation presents a hybrid Neuro-Fuzzy (H-NF) method for MCDM in regulating energy for smart homes by combining FL with an MNN. The suggested approach would optimize energy use in smart homes by considering several parameters, notably cost, ease of use, and environmental effects. In addition, this study aims to examine how the H-NF model fares in comparison to other methods of making important decisions in terms of several performance metrics. The suggested hybridized approach has the potential to deliver more precise and effective decision-making processes for energy management in smart homes, allowing users to optimize their energy consumption while preserving comfort and lowering environmental impact. © 2024 Taylor and Francis Inc.. All rights reserved.

关键词： Decision making

来源：评论

学校读者我要写书评

暂无评论

Optimized Learning Model for Brain-Computer Interface Using Electroencephalogram (EEG) for Neuroprosthetics Robotic Arm Design for Society 5.0

Optimized Learning Model for Brain-Computer Interface Using ...

引用

2024 IEEE International Conference on computing, Semiconductor, Mechatronics, Intelligent Systems and Communications, COSMIC 2024

作者： Arun Kumar, S. Anand, L. Kannur, Anil School of Computing SRM Institute of Science and Technology Department of Computer Science and Engineering Tamil Nadu India School of Computing SRM Institute of Science and Technology Department of Networking and Communications Tamil Nadu Potheri SRM Nagar Kattankulathur India Dr. P.G. Halakatti College of Engineering and Technology Department of Computer Science and Engineering Karnataka Vijayapura India

ISBN: (纸本)9798331517892

The brain activity can be represented by EEG, which does it by measuring voltage fluctuations in the brain. in this paper, the work intends to develop a Brain-computer Interface-based system that can identify and forecast the class of motor action corresponding to the left or right direction. There are two datasets used in this study, relating to motor movements - left/right-hand movement and eye open/close. The collected data is pre-processed by applying a Convolution Neuron Network to obtain a frequency domain matrix. The result computed by applying CNN provides a condensed representation of the data. The second dataset captured brain impulses corresponding to two states of the eyes opened and eyes closed, over a period of two minutes. This system is designed to effectively separate and utilize signals, with the adoption of AI techniques in these devices emerging as the most viable option for Society. The overall efficiency of this system ranges from 80% to 87%. © 2024 IEEE.

关键词： Frequency domain analysis

来源：评论

学校读者我要写书评

暂无评论

Collaborative learning-based inter-dependent task dispatching and co-location in an integrated edge computing system

引用

Digital Communications and Networks 2024年第6期10卷 1837-1850页

作者： Uchechukwu Awada Jiankang Zhang Sheng Chen Shuangzhi Li Shouyi Yang School of Software Henan Institute of Science and TechnologyXinxiang 453003China School of Electrical and Information Engineering Zhengzhou UniversityZhengzhou 450001China Department of Computing and Informatics Bournemouth UniversityPoole BH125BBUK School of Electronics and Computer Science University of SouthamptonSouthampton SO171BJUK Faculty of Information Science and Engineering Ocean University of ChinaQingdao 266100China

Recently,several edge deployment types,such as on-premise edge clusters,Unmanned Aerial Vehicles(UAV)-attached edge devices,telecommunication base stations installed with edge clusters,etc.,are being deployed to enable faster response time for latency-sensitive *** fundamental problem is where and how to offload and schedule multi-dependent tasks so as to minimize their collective execution time and to achieve high resource *** approaches randomly dispatch tasks naively to available edge nodes without considering the resource demands of tasks,inter-dependencies of tasks and edge resource *** approaches can result in the longer waiting time for tasks due to insufficient resource availability or dependency support,as well as provider ***,we present Edge Colla,which is based on the integration of edge resources running across multi-edge *** Colla leverages learning techniques to intelligently dispatch multidependent tasks,and a variant bin-packing optimization method to co-locate these tasks firmly on available nodes to optimally utilize *** experiments on real-world datasets from Alibaba on task dependencies show that our approach can achieve optimal performance than the baseline schemes.

关键词： Edge computing Collaborative learning Resource utilization Execution time Edge federation Gang scheduling

来源：评论

学校读者我要写书评

暂无评论

Recent progress of iron-based electrocatalysts for nitrogen reduction reaction

引用

Journal of Materials Science & technology 2023年第9期140卷 121-134页

作者： Tianyi Wang Zhongyuan Guo Xiaoli Zhang Qinye Li Aimin Yu Chengzhang Wu Chenghua Sun Department of Chemistry and Biotechnology School of ScienceComputing and Engineering TechnologiesSwinburne University of TechnologyHawthornVIC3122Australia School of Material Science and Engineering Zhengzhou UniversityZhengzhou 450001China State Key Laboratory of Advanced Special Steel Shanghai Key Laboratory of Advanced FerrometallurgySchool of Materials Science and EngineeringShanghai UniversityShanghai 200444China

Ammonia is a critical feedstock for modern industry and agriculture,which is also a promising carbonfree energy *** nitrogen reduction reaction(ENRR)is a sustainable and efficient approach to synthesize ammonia under ambient reaction *** relies on the development of highly efficient *** far various strategies have been applied to enhance the performance of catalysts including tuning the electronic structure,binding strength,coordination configuration as well as the introduction of multiple active sites and *** this review,the recent progress of Fe-based electrocatalysts and their coordination effect,syner gistic effect and def ect effect for nitrogen reduction reaction have been *** critical review focuses on the discussion of theoretical advancement,the performance origin of ENRR activity and selectivity of Fe-based electrocatalysts.

关键词： effect coordination critical

来源：评论

学校读者我要写书评

暂无评论

GPNST: An Improved Graphical Password Authentication Scheme Leveraging Neural Style Transfer Technique on Smartphones

引用

International Journal of Information Security 2025年第3期24卷 1-34页

作者： Ray, Palash Giri, Debasis Obaidat, Mohammad S. Jana, Manasi Sasmal, Mahuya Alenazi, Mohammed J. F. Haldia Institute of Technology West Bengal Haldia India Maulana Abul Kalam Azad University of Technology West Bengal Nadia India King Abdullah II School of Information Technology The University of Jordan Amman Jordan School of Computer and Communication Engineering University of Science and Technology Beijing Beijing China Department of Computational Intelligence School of Computing SRM University SRM Nagar TN Kattankulathur603203 India School of Engineering The Amity University UP Noida201301 India King Saud University Riyadh Saudi Arabia

The growing prevalence of smartphones and the increasing dependence on digital services have made it crucial to have authentication techniques that are both secure and user-friendly. This study examines the effectiveness and usability of graphical passwords named GPNST as an alternative authentication method on mobile devices. Graphical passwords use users’ capacity to remember visuals or patterns, offering a possible equilibrium between security and user pleasure. GPNST is a two-factor authentication technique that requires users to remember content and style images, or stylized images, as portfolio images. Additionally, a unique key token is assigned to each user device and securely sent to the server using the reversible data hiding approach, therefore mitigating several potential attacks. The research uses a combination of quantitative analysis to evaluate the strength of passwords and qualitative evaluations to measure user satisfaction and memorability. We investigate the influence of several design elements in graphical passwords, such as the intricacy of images and the layout of grids, on both the level of security and ease of use. In addition, the study evaluates the robustness of graphical passwords against popular forms of attacks, such as shoulder surfing and brute-force efforts. The findings provide valuable insights regarding the practicality of incorporating graphical passwords into smartphone authentication systems. This has implications for designers, developers, and users who are looking for secure and user-friendly solutions in the constantly changing field of mobile technology. The GPNST scheme demonstrates outstanding performance in our assessment test, with an accuracy rate of up to 94.80% and a login time of 9.61 seconds. © The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature 2025.

关键词： Static random access storage

来源：评论

学校读者我要写书评

暂无评论

Image Tampering Detection With Frequency-Aware Attention and Multiview Fusion

IEEE Transactions on Artificial Intelligence

引用

IEEE Transactions on Artificial Intelligence 2025年第3期6卷 614-625页

作者： Xu, Xu Chen, Junxin Lv, Wenrui Wang, Wei Zhang, Yushu Dalian University of Technology School of Software Dalian116621 China Northeastern University School of Computer Science and Engineering Shenyang110004 China Shenzhen MSU-BIT University Guangdong-Hong Kong-Macao Joint Laboratory for Emotion Intelligence and Pervasive Computing Artificial Intelligence Research Institute Shenzhen518172 China Jiangxi University of Finance and Economics School of Computing and Artificial Intelligence Nanchang330013 China

Manipulated images are flooding our daily lives, which poses a threat to social security. Recently, many studies have focused on image tampering detection. However, they have poor performance on independent validation due to differences in image scenes and tampering methods. The key question is how to design a network that is able to adaptively enhance the tampering information and suppress the generalization features during training. To this end, we propose a dual-branch network with a frequency adaptation paradigm and a feature fusion module for robust tampering image detection. First, this paradigm is designed to adaptively highlight tampering features through frequency conversion and learnable weight. Second, a feature fusion module is developed to filter redundant features and dynamically fuse two-branch features. Experiments on eight typical datasets demonstrate that our model has advantages over state-of-the-art algorithms, and our paradigm can well empower semantic segmentation networks for tampering detection. © 2024 IEEE.

关键词： Semantic Segmentation

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：