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检索条件"任意字段=International Conference on Information Technology - Coding and Computing"

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DFMA: Adaptive Dual Fusion for Multimodal Relation Extraction with Mutual Attention

DFMA: Adaptive Dual Fusion for Multimodal Relation Extractio...

引用

2025 IEEE international conference on Acoustics, Speech, and Signal Processing, ICASSP 2025

作者： Li, Yunhao Huang, Tianxi Duan, Guiduo Dong, Yunrui Laboratory of Intelligent Collaborative Computing University of Electronic Science and Technology of China Chengdu China College of Humanities and General Education Chengdu Textile College Chengdu China

ISBN: (纸本)9798350368741

Multimodal relation extraction (MRE) is an emerging research field that combines techniques from natural language processing, computer vision, and machine learning, helping us better understand and interpret data. However, current methods are faced with two main issues. The first issue is that the auxiliary images may focus on irrelevant information, leading the model to place too much attention on unrelated entities when extracting visual features from the global image. The second issue is modality imbalance during the multimodal fusion stage, where the encoder might overly focus on one modality's information over the other. Therefore, we propose a MRE method using Dual Fusion with Mutual Attention (DFMA). To address the first issue, we introduce the Pyramid Feature Extraction (PFE) module. To tackle the second issue, we propose the Multimodal Mutual Fusion (MMF) module. PFE dynamically generates prompt vectors to mitigate the impact of irrelevant information, while MMF, designed with mutual attention, can balance the fusion of textual and visual information simultaneously. Experiments show that our approach achieves the state-of-the-art performances on the multimodal neural relation extraction (MNRE) dataset. © 2025 IEEE.

关键词： Dual fusion Multimodal Mutual Attention Multimodal relation extraction Pyramid Feature Extraction

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GRU-Based Winner Subcarrier Detection in Frequency Domain Contention 24

GRU-Based Winner Subcarrier Detection in Frequency Domain Co...

引用

7th international conference on information Science and Systems, ICISS 2024

作者： Yao, Shumin Zhao, Qinglin Xu, Zezhou Feng, Li Li, Guanghui Tian, Liwei Sun, Yi School of Computer Science and Engineering Macau University of Science and Technology China Department of Broadband Communication Pengcheng Laboratory China School of Artificial Intelligence and Computer Science Jiangnan University China Department of Computer Guangdong University of Science and Technology China Institute of Computing Technology Chinese Academy of Sciences China

ISBN: (纸本)9798400717567

Single-carrier frequency domain contention (S-FDC) is an efficient wireless contention mechanism based on orthogonal frequency-division multiplexing (OFDM). In each round of S-FDC, each node randomly selects and signals on one of the OFDM subcarriers while listening to all subcarriers simultaneously. Each node independently detects the activated subcarrier with the smallest index and regards it as the winner subcarrier. Accurately detecting the winner subcarrier is crucial to ensuring the functionality of the network. However, it is extremely difficult in practice due to power leakage problems that arise from frequency asynchronization among nodes. In this paper, we propose a gated-recurrent-unit (GRU)-based model that incorporates S-FDC’s unique features as domain knowledge to enable accurate winner subcarrier detection. Extensive simulation experiments verify that our DL model is effective and outperforms state of the art. This research highlights the potential of DL in improving wireless communication systems. © 2024 Copyright held by the owner/author(s).

关键词： Frequency domain analysis

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Utilization of Virtual Reality technology for Enhancement of E-Commerce Experience 6

Utilization of Virtual Reality Technology for Enhancement of...

引用

6th international conference on Mobile computing and Sustainable Informatics, ICMCSI 2025

作者： Sultanpure, Kavita Dighe, Aditya Agrawal, Shiven Borse, Chirayu Deshpande, Shashwat Agashe, Avani Information Technology Vishwakarma Institute of Technology 37 Pune India

ISBN: (纸本)9798331522667

Web technology has gone through quite significant evolution since the past three decades-from relatively rudimentary static pages to rather sophisticated and framework-based web applications able to carry out computation and logical tasks, besides handling advanced graphics with ease. All this has been big enough for new directions computer devices take from simple, traditional desktops and laptops into smart mobile devices that are tablets and smartphones. HTML, CSS, and JavaScript are the basic languages of the web, and over time, they have adapted to newer form factors by including media queries, allowing responsive web pages adaptive to different screen sizes. Then, with the appearance of React, web development was revolutionized in the sense that developers were able to create lightweight yet powerful application-based interfaces. However, with the dawn of AR and VR comes a new frontier in web designing and requires changed paradigms. Websites today not only need to be designed to work on classic desktops and handheld devices but are instead built considering experiences in AR/VR. In the field of augmented reality and virtual reality, virtual reality is taking a transforming role, and websites should be strategically designed to cope with this changing technological scenario. Our project is particularly aligned to deal with this aspect and integrate the perspectives of augmented reality and virtual reality in web design so that these immersive and interactive features are not lost in the experience of the user. © 2025 IEEE.

关键词： Virtual environments

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Developing Predictive Models for Future Stress Likelihood and Recovery Time Using Behavioral and Emotional Data 5

Developing Predictive Models for Future Stress Likelihood an...

引用

5th international conference on Advanced Research in computing, ICARC 2025

作者： Weerasinghe, W.P.D.J.N. Gunasekera, H.D.P.M. Wickramasinghe, B.G.W.M.C.R. Jayathunge, K.A.D.T.R. Wijesiri, Pipuni Dassanayake, Thamali Sri Lanka Institute of Information Technology Dept of Information Technology Malabe Sri Lanka

ISBN: (纸本)9798331530983

Stress has a serious impact on mental and physical well-being, but treatments as usual are often unavailable and not effective over the long term. The AyurAura application combines imaginative Ayurvedic therapies with modern AI techniques to deliver customized stress reduction by way of Mandala art and music. This research develops two predictive models for the application. In its first model, the stress prediction probability is estimated from users' behavior in a questionnaire and the result can be used to proactively intervene. The second model forecasts time needed for recovery into a stress-free state by using the changes in daily emotional state and participation in app activities. Machine learning algorithms are used to prepare behavioral and emotional data for improved prediction performance. Trained on multi-institution datasets, both models delivered 90-95% accuracy, enabling the user to detect behavior eliciting stress and the degree needed for recovery. These results highlight the possibility of combining conventional therapeutics with contemporary tech for ongoing, affordable stress relief interventions with personalized needs in mind. © 2025 IEEE.

关键词： Logistic regression

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Breast Cancer Stage Identification Using Machine Learning 11th

Breast Cancer Stage Identification Using Machine Learning

引用

11th EAI international conference on Advancement of Science and technology, ICAST 2023

作者： Arega, Birtukan Shegaw Mengsitu, Tesfahunegn Minwuyelet Faculty of Computing Bahir Dar Institute of Technology Bahir Dar University Bahir Dar Ethiopia Department of Information Convergence Engineering Pusan National University Busan Korea Republic of

ISBN: (纸本)9783031641503

This paper presents a machine learning model for determining the stages of breast cancer. The model normalizes images, eliminates noise, and removes artifacts through preprocessing, segmentation, and classification. Patching is used to extract the region of interest (ROI), while multi-thresholding is used for segmentation. The suggested models, including CNN-KNN, VGGNet-16, CNN-naïve Bayes, and CNN-SVM, were tested on a dataset of images from the CBIS-DDSM database. Experiments were conducted using full mammogram images and segmented ROI images, resulting in accuracies of 39%, 85%, 86%, and 91%, respectively. The CNN-SVM model achieved a 6% increase in classification accuracy compared to the state-of-the-art VGGNet-16 model. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： Image segmentation

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Web Vulnerability Scanner 5th

Web Vulnerability Scanner

引用

5th international conference on Advances in information Communication technology and computing, AICTC 2024

作者： Kumaran, U. Sree, Pothireddy Sneha Udaya Sree, S. Sowgandhi, Vadlamudi Krishna Balasubramanian, Sundaravadivazhagn Amrita School of Computing Amrita Vishwa Vidyapeetham Bengaluru India University of Technology and Applied Sciences Al Mussanah Oman

ISBN: (纸本)9789819761050

A Web Vulnerabilities Scanner scans the website’s web pages for comprehensive vulnerabilities. The recently constructed web application is a dynamic site that necessitates frequent changes for both clients and the developer. The ultimate goal of the project is to uncover vulnerabilities in the relevant websites. Client-side submission of unexpected inputs is used for exploiting an extensive range of web application vulnerabilities. While it is evident that these vulnerabilities are complicated and extensive, it is unclear why, after more than a decade of work, they remain so ubiquitous. This study explores numerous types of techniques for addressing this type of danger. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Crawler Dir scan Full scanning Live hosts OWASP Scanner Web vulnerabilities

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A Consumption-Based Picture Extraction Procedure for Static Images Using a User Opinion Choice Method 12th

A Consumption-Based Picture Extraction Procedure for Static ...

引用

12th international conference on Frontiers of Intelligent computing: Theory and Applications, FICTA 2024

作者： Saravanan, D. Kaushik, S. Handaragall, Vijayalaxmi C. Raja Vikram, G. Sudha, C. Kalaivani, J. Hyderabad Hyderabad India ICFAI Foundation for Higher Education Hyderabad Hyderabad India School of Computing and Information Technology REVA University Bengaluru Bengaluru India Department of Computer Science & Engineering Vignan Institute of Technology and Science Hyderabad India Hyderabad India Department of Computing Technologies SRM Institute of Science and Technologies Kattankulathur Chennai India

ISBN: (纸本)9789819601387

Extracting the necessary information from the stored database is one of the most demanded research areas today, especially in the field of subject-based information extraction. This application is a crucial area of focus for many researchers. The existing technique in this area relies on user observation-based responses. In this approach, each time a user submits a query, they need to select the most relevant content from the query extraction and then rank the items. The search is then refined, and the process continues in the next iteration. This method is time-consuming and requires domain knowledge about the system. To overcome these issues in subject-based information extraction, creating an index of datasets can improve search time and enhance information extraction efficiency. Initially, this process may take some time to train the input datasets, but the extraction will yield the most relevant data. Experimental results and practical applications indicate that the proposed technique performs well overall. The outputs confirm that even if the query is designed by an unprofessional user or lacks specific query points, the technique produces effective results. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Creation of evidence Evidence-based search Identify the patterns Response Subject-based content User Assessment

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Enhancing Supply Chain Transparency and Integrity: A Permissioned Blockchain Framework 5

Enhancing Supply Chain Transparency and Integrity: A Permiss...

引用

5th international conference on Emerging Systems and Intelligent computing, ESIC 2025

作者： Soma, Arun Kumar Park University Department of Information Systems & Business Analytics 8700 NW River Park Dr ParkvilleMO64152 United States

ISBN: (纸本)9798331522100

Traditional international trade practices have often been plagued by opaque information flows, impeding traceability, and complicating seamless trade operations. Although blockchain technology has emerged as a potential solution for the supply chain and logistics sector, the existing literature predominantly addresses isolated issues such as asset monitoring and traceability, overlooking critical factors such as data integrity and access. This paper proposes a comprehensive blockchain-acquired framework designed to secure supply chain and logistics operations by integrating relevant processes and functions. Through a detailed case study, we demonstrate the effectiveness of the framework in addressing significant vulnerabilities within current supply chain systems. Our findings reveal that the proposed framework not only enhances traceability, but also fortifies data integrity and access controls, thus mitigating critical loopholes that have hindered operational efficiency. Furthermore, we outline several avenues for future research, emphasizing the need for continued exploration of blockchain applications in supply chain management. This work aims to contribute to the development of more transparent, efficient, and reliable trade practices in the global marketplace. © 2025 IEEE.

关键词： Supply chain management

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AI Enabled Virtualization and Fault Detection in Machines 5

AI Enabled Virtualization and Fault Detection in Machines

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5th international conference on Emerging Systems and Intelligent computing, ESIC 2025

作者： Nachane, Akash Narwadkar, Sanved Pasare, Ameya Kure, Siddhi Dedgaonkar, Suruchi Futane, Pravin BRACT's Vishwakarma Institute of Information Technology Department Of Information Technology Pune411048 India

ISBN: (纸本)9798331522100

Modern machines like automobile, PC, mobile, and wearable machines are prone to inefficient and unreliable fault detection and service. Service providers are mostly at the wrong end due to vague diagnostics and repair processes. It aims to design an AI-based fault detection and servicing system that will boost the accuracy, transparency, and efficiency of several devices when faults are detected and rectified. It involves fault detection through machine learning models, analysis of sensor data and performance logs, and comparison with ideal benchmarks. Virtualization is achieved by creating 3D models from image processing to visualize and explain faults. Virtual calibration is also implemented through a virtual simulation environment for device testing and calibration before manual repair. This physical mapping is integrated by real-time sensor data for continuous monitoring and mapping of device states. The outcome shows that the AI-based system increased the accuracy of fault detection, provided clear visual explanations, and made it easy and quick to repair while minimizing the downtime of users as well as creating trust in service providers. It enhances the fault detection and servicing process of modern machines, with much more effective diagnostics, transparent explanations, and efficient repairs for the satisfaction of the customers. © 2025 IEEE.

关键词： Virtualization

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An Abnormal Behavior Recognition System for Bathrooms with Using Toilet Based on Thermal Image AI Edge computing technology 16th

An Abnormal Behavior Recognition System for Bathrooms with U...

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16th international conference on Genetic and Evolutionary computing, ICGEC 2024

作者： Chang, Wan-Jung Liu, Jia-Hong Chen, Yi-Jia Chen, Liang-Bi Department of Electronic Engineering National Kaohsiung University of Science and Technology Kaohsiung807618 Taiwan Department of Electronic Engineering Southern Taiwan University of Science and Technology Tainan710301 Taiwan Department of Computer Science and Information Engineering National Penghu University of Science and Technology Penghu880011 Taiwan

ISBN: (纸本)9789819615346

With the gradual increase in the proportion of the global elderly population, the number of bathroom accidents also increases yearly. Due to the humid environment in bathrooms, the floors are mostly made of tiles, which are relatively prone to slips and falls. However, the existing pose recognition methods mostly use color images, and color images have concerns about personal privacy and are susceptible to lighting changes and complex spatial interference. Therefore, this paper proposes an abnormal behavior recognition system based on thermal image AI edge technology. Use a dangerous posture when using the toilet to avoid accidents in the bathroom, such as using the toilet being discovered too late, increasing the risk. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Differential privacy

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