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IAENG international Journal of computer science 2025年第1期52卷 233-243页

作者： Zhang, Wanpeng Zhou, Ziwei School of Computer Science and Software Engineering University of Science and Technology LiaoNing Anshan114051 China School of Computer Science and Software Engineering University of Science and Technology LiaoNing Anshan114051 China

Point cloud completion is crucial in point cloud processing, as it can repair and refine incomplete 3D data, ensuring more accurate models. However, current point cloud completion methods commonly face a challenge: they fail to fully utilize multi-scale information from local features, leading to limitations in accuracy and detail preservation. To address this issue, this paper proposes a multi-scale feature optimization algorithm for point cloud completion that integrates SoftPool. Based on DGCNN, the method combines dilated convolution and bottleneck attention mechanisms to extract features at different scales, enhancing the ability to capture detailed information in point clouds. The bottleneck attention mechanism is used to optimize important detail features. The extracted local features are concatenated with their corresponding positional information to form point proxies, enhancing the effective extraction of local geometric features, resulting in more refined completed point cloud shapes. A Transformer architecture is employed to model these features. Finally, SoftPool is introduced for fine-grained feature downsampling, improving the network's ability to recover point cloud details. FoldingNet is used to reconstruct missing structures and output the completed point cloud. To validate the model's completion performance, training and testing are conducted on the PCN and ShapeNet55 datasets. Experimental results demonstrate that the model has better feature detail retention and more accurate completion results. On the PCN dataset, the average CD value is reduced by 6.5% compared to the best-performing model among the comparison methods. On the ShapeNet55 dataset, the average CD value across three difficulty levels is reduced by 6.9% compared to the best-performing model among the comparison methods. Additionally, the model also achieved a 2.1% improvement in F-score. © (2025), (international Association of Engineers). All rights reserved.

关键词： Ability testing

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A Tourist Customer Comment and Feedback Emotion Analysis Model Based on Artificial Neural network Algorithm 24

A Tourist Customer Comment and Feedback Emotion Analysis Mod...

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5th international conference on computer science and Management technology, ICCSMT 2024

作者： Yang, Xianmin Business and Administration School Xi'an Eurasia University Shaanxi Xi'an China

ISBN: (纸本)9798400709999

Text sentiment analysis has become a key technology in smart *** tourism review text is lengthy and complex in sentence structure, and existing tourism sentiment analysis algorithms do not consider text characteristics and syntactic change rules, resulting in a decrease in classification *** order to enhance the reputation and competitiveness of tourist destinations such as scenic spots and hotels, how to obtain relevant data from massive user reviews and organize valuable information, and apply it to the construction of smart travel, has become a highly valued task for cultural and tourism authorities and tourism related *** article proposes a tourism customer comment and feedback sentiment analysis model based on artificial neural network (ANN) *** features are extracted to obtain the sentiment classification results of ***, sentiment analysis is performed on the sentiment classification results to obtain user satisfaction with the scenic *** the existing sentiment lexicon has been expanded to improve the accuracy of the model in sentiment classification in the tourism *** experimental results show that the model proposed in this article has high accuracy in sentiment classification, can accurately capture user interest points, and improve the effectiveness of personalized recommendations. © 2024 Copyright held by the owner/author(s). Publication rights licensed to ACM.

关键词： Sales

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SRv6-PPO network Nodes Deployment Method 24

SRv6-PPO Network Nodes Deployment Method

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3rd international conference on Signal Processing, computer networks and Communications, SPCNC 2024

作者： Wang, Pengrui Hu, Yuxiang Cui, Pengshuai Bai, Luxin Wang, Yu Dong, Yongji Institute of Information Technology Research Information Engineering University Henan Zhengzhou China

ISBN: (纸本)9798400710834

Aiming at the issues of high economic cost and incomplete consideration of node attributes in the current SRv6 network nodes deployment method, we proposed an SRv6 network node deployment method based on deep reinforcement learning. Firstly, based on constructing a network communication scenario that integrates IPv6 nodes and SR nodes, we proposed an SRv6 network node optimization model to ensure that the selection of SRv6 node locations is more rational. Next, we designed an SRv6 network node optimization model integrating traffic engineering to assess the advantages and disadvantages of SRv6 node deployment locations. Then, an SRv6 network node deployment method based on proximal policy optimization was devised from offline and online phases. Finally, we assessed the proposed method through three typical datasets. The empirical results indicated that, relative to a network environment where all nodes are equipped with SRv6 capabilities, deploying merely 20%-40% of SRv6 nodes within a hybrid network can achieve comparable link utilization. Furthermore, the proposed method significantly outperforms alternative approaches in minimizing the maximum link utilization, thereby enhancing overall network efficiency and stability. © 2024 Copyright held by the owner/author(s).

关键词： Deep reinforcement learning

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network SLO-Aware Container Orchestration on Kubernetes Clusters 22nd

Network SLO-Aware Container Orchestration on Kubernetes Clus...

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22nd international conference on Service Oriented Computing

作者： Marchese, Angelo Tomarchio, Orazio Univ Catania Dept Elect Elect & Informat Engn Catania Italy

ISBN: (纸本)9789819608072;9789819608089

Orchestrating microservices in geo-distributed Cloud-toEdge environments introduces challenges, particularly with maintaining response time SLOs due to network instability. Kubernetes, the standard for container orchestration, faces limitations in scheduling and descheduling when applied to such complex, distributed applications. Its default policies do not account for response time SLOs or the dynamic state of applications and infrastructure. This study proposes an enhancement to Kubernetes with a network SLO-aware scheduling and descheduling strategy, enabling adaptive placement based on the observed runtime application response times. Our approach is benchmarked against default Kubernetes scheduling policies to demonstrate its effectiveness.

关键词： Microservices applications Container technology Cloud-to-Edge continuum Kubernetes scheduler Kubernetes descheduler

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Design and Implementation of a Flexible Wireless Sensor network for Environmental Monitoring with in Digital Cities Framework 1

Design and Implementation of a Flexible Wireless Sensor Netw...

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1st international conference on Intelligent Systems and Computational networks, ICISCN 2025

作者： Manogna, B. Sai Rao, R. Gowri Shankar Chythanya, K. Ravi Navamani, C. Raghuram, K.S. Isaac, J. Samson Marri Laxman Reddy Institute of Technology and Management Department of Computer Science and Engineering Hyderabad India Vel Tech Rangarajan Dr. Sagunthala R&d Institute of Science and Technology Department of Physics Chennai India Sr University School of Computer Science and Artificial Intelligence Warangal India Department of Computer Science and Engineering Erode India Department of Mechanical Engineering Visakhapatnam India School of Engineering and Technology Karunya Institute of Technology and Sciences Department of Biomedical Engineering Coimbatore India

ISBN: (纸本)9798331529246

The paper highlights a Wireless Sensor network (WSN) implementation for environmental monitoring, emphasizing cost-effectiveness and adaptability. APIs designed to handle values instead of voltage levels increase system resilience, while open standards promote security, cost efficiency, and auditability. The data shows a diurnal temperature range from 20°C (night) to 38°C (day), stable humidity at 38%, and UV radiation peaking at 6 (day) and dropping to 1.5 (night). Smoke levels are consistently high at 490 μg/m3, while toxic gas concentrations slightly rise to 0.5 ppm during the day from 0.45 ppm at night. Fire metrics remain low and stable. These findings highlight the need for UV protection, air quality controls, and consistent fire safety measures. The system achieves effective environmental monitoring while remaining adaptable for future needs, underscoring its value in scalable, cost-efficient, and sustainable public management solutions. © 2025 IEEE.

关键词： Environmental monitoring

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Outline of a Theoretical and Technological Approach for Reducing Inequalities in the Design of a 360 Synchronous Interactive Telepresence System 10th

Outline of a Theoretical and Technological Approach for Redu...

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10th international conference of the Immersive Learning Research network

作者： Garavaglia, Andrea Terrenghi, Ilaria De Nino, Maurizio Univ Milan Via Festa Perdono I-20122 Milan Italy

ISBN: (纸本)9783031804717;9783031804724

The paper discusses the development of an immersive prototype for synchronous learning, emphasizing pedagogical and technological choices aimed at supporting equity and inclusion in an interdisciplinary perspective. Rooted in the pedagogical approach, it focuses on enhancing synchronous 360-degree video for interactive telepresence in higher education. Addressing the lack of immersive synchronous videoconferencing systems, the project aims to facilitate synchronous interaction between teachers, students, peers, and the learning environment, and to promote feedback loop. The prototype, called ISL360 (ImmerSyncLearn360), aims to promote equity and inclusion by creating student-centered post-pandemic educational pathways that are accessible to all. It ensures synchronous presence for those who experience various types of barriers to movement (physical, psychological, or otherwise) and enables everyone to reach spaces that would otherwise be inaccessible. Beginning with a review of the literature on equity and inclusion with immersive technologies, we will present some design choices, both pedagogical and technological.

关键词： Telepresence Immersive Education Inclusive technology

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Facial expression recognition using Two-Stream Convolutional Neural networks (TSCNNs) and inception 3D Convolutional Neural network (CNN) 4th

Facial expression recognition using Two-Stream Convolutional...

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4th international conference on Computational Methods in science and technology, ICCMST 2024

作者： Kumar, Pramod Singh, Anuj Kumar Kumar, Manish Sabia Verma, Shorav Swami Rama Himalayan University Dehradun India Galgotias University Greater Noida India Chandigarh Engineering College CGC Landran Mohali India

ISBN: (纸本)9781032911571

Facial Expression Recognition (FER) is a hot topic in computer vision, thanks to its many uses in the fields including psychology, security, and human-computer interaction. In this paper, we present a method for face expression recognition using Inception 3D CNNs in conjunction with TSCNNs. A static picture stream and a facial sequences stream make up the structure. In order to record the spatial and temporal changes in facial expressions, it employs a three-dimensional convolutional neural network called Inception. The spatial properties from the image sequence stream can also be learned by the TSCNN architecture. This research applies the TSCNN architecture to picture sequences that are not provided by individual frames. The TSCNN architecture is used to process still images. The properties of both streams are combined using the late fusion approach. After testing the suggested framework with three publicly available datasets, the suggested method becomes clear. By comparing its outcomes to those of other state- of-the-art methods, the implemented approach proves to be more accurate. © 2025 the Author(s).

关键词： Convolutional neural networks

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CACA: Context-Aware Cross-Attention network for Extractive Aspect Sentiment Quad Prediction 31

CACA: Context-Aware Cross-Attention Network for Extractive A...

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31st international conference on Computational Linguistics, COLING 2025

作者： Chen, Bingfeng Xu, Haoran Luo, Yongqi Xu, Boyan Cai, Ruichu Hao, Zhifeng School of Computer Science Guangdong University of Technology China China College of Science Shantou University China

ISBN: (纸本)9798891761964

Aspect Sentiment Quad Prediction(ASQP) enhances the scope of aspect-based sentiment analysis by introducing the necessity to predict both explicit and implicit aspect and opinion terms. Existing leading generative ASQP approaches do not modeling the contextual relationship of the review sentence to predict implicit terms. However, introducing the contextual information into the pre-trained language models framework is non-trivial due to the inflexibility of the generative encoder-decoder architecture. To well utilize the contextual information, we propose an extractive ASQP framework, CACA, which features with Context-Aware Cross-Attention network. When implicit terms are present, the Context-Aware Cross-Attention network enhances the alignment of aspects and opinions, through alternating updates of explicit and implicit representations. Additionally, contrastive learning is introduced in the implicit representation learning process. Experimental results on three benchmarks demonstrate the effectiveness of CACA. Our implementation will be open-sourced at https://***/DMIRLAB-Group/CACA. © 2025 Association for Computational Linguistics.

关键词： Computational linguistics

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AMSFuse:Adaptive Multi-Scale Feature Fusion network for Diabetic Retinopathy Classification

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computers, Materials & Continua 2025年第3期82卷 5153-5167页

作者： Chengzhang Zhu Ahmed Alasri Tao Xu Yalong Xiao Abdulrahman Noman Raeed Alsabri Xuanchu Duan Monir Abdullah School of Computer Science and Engineering Central South UniversityChangsha410083China School of Humanities Central South UniversityChangsha410083China Department of Human Anatomy and Histology & Embryology Basic Medical SciencesChangsha Health Vocational CollegeChangsha410100China Glaucoma Institute Changsha Aier Eye HospitalChangsha410000China Department of Computer Science and Artificial Intelligence College of Computing and Information TechnologyUniversity of BishaBisha67714Saudi Arabia

Globally,diabetic retinopathy(DR)is the primary cause of blindness,affecting millions of people *** widespread impact underscores the critical need for reliable and precise diagnostic techniques to ensure prompt diagnosis and effective *** learning-based automated diagnosis for diabetic retinopathy can facilitate early detection and ***,traditional deep learning models that focus on local views often learn feature representations that are less discriminative at the semantic *** the other hand,models that focus on global semantic-level information might overlook critical,subtle local pathological *** address this issue,we propose an adaptive multi-scale feature fusion network called(AMSFuse),which can adaptively combine multi-scale global and local features without compromising their individual ***,our model incorporates global features for extracting high-level contextual information from retinal ***,local features capture fine-grained details,such as microaneurysms,hemorrhages,and exudates,which are critical for DR *** global and local features are adaptively fused using a fusion block,followed by an Integrated Attention Mechanism(IAM)that refines the fused features by emphasizing relevant regions,thereby enhancing classification accuracy for DR *** model achieves 86.3%accuracy on the APTOS dataset and 96.6%RFMiD,both of which are comparable to state-of-the-art methods.

关键词： Diabetic retinopathy multi-scale feature fusion global features local features integrated attention mechanism retinal images

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An Iterative PRISMA Review of GAN Models for Image Processing, Medical Diagnosis, and network Security

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computers, Materials & Continua 2025年第2期82卷 1757-1810页

作者： Uddagiri Sirisha Chanumolu Kiran Kumar Sujatha Canavoy Narahari Parvathaneni Naga Srinivasu Department of Computer Science and Engineering Prasad V Potluri Siddhartha Institute of TechnologyVijayawada520007India Department of Computer Science and Engineering Koneru Lakshmaiah Education FoundationVaddeswaram522302India Department of Electronics and Communication Engineering Sreenidhi Institute of Science and TechnologyHyderabad501301India Amrita School of Computing Amrita Vishwa VidyapeethamAmaravati522503India Department of Teleinformatics Engineering Federal University of CearáFortaleza60455-970Brazil Inti International University Nilai71800Malaysia

The growing spectrum of Generative Adversarial network (GAN) applications in medical imaging, cyber security, data augmentation, and the field of remote sensing tasks necessitate a sharp spike in the criticality of review of Generative Adversarial networks. Earlier reviews that targeted reviewing certain architecture of the GAN or emphasizing a specific application-oriented area have done so in a narrow spirit and lacked the systematic comparative analysis of the models’ performance metrics. Numerous reviews do not apply standardized frameworks, showing gaps in the efficiency evaluation of GANs, training stability, and suitability for specific tasks. In this work, a systemic review of GAN models using the PRISMA framework is developed in detail to fill the gap by structurally evaluating GAN architectures. A wide variety of GAN models have been discussed in this review, starting from the basic Conditional GAN, Wasserstein GAN, and Deep Convolutional GAN, and have gone down to many specialized models, such as EVAGAN, FCGAN, and SIF-GAN, for different applications across various domains like fault diagnosis, network security, medical imaging, and image segmentation. The PRISMA methodology systematically filters relevant studies by inclusion and exclusion criteria to ensure transparency and replicability in the review process. Hence, all models are assessed relative to specific performance metrics such as accuracy, stability, and computational efficiency. There are multiple benefits to using the PRISMA approach in this setup. Not only does this help in finding optimal models suitable for various applications, but it also provides an explicit framework for comparing GAN performance. In addition to this, diverse types of GAN are included to ensure a comprehensive view of the state-of-the-art techniques. This work is essential not only in terms of its result but also because it guides the direction of future research by pinpointing which types of applications require some

关键词： GAN CGAN WGAN DCGAN image analysis

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