Intersection collision prediction and prevention based on vehicle-to-vehicle (V2V) and cloud computing communication by Min Zeng, Mohd Sani Mohamad Hashim, Mohd Nasir Ayob, Abdul Halim Ismail, Qiling Zang

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ALogSCAN: A Self-Supervised Dual Network for Adaptive and Timely Log Anomaly Detection in Clouds by Mahsa Raeiszadeh, Felipe Estrada-Solano, Roch H. Glitho, Johan Eker, Raquel A. F. Mini

“…Logs are prevalent in modern cloud systems and serve as a valuable source of information for system maintenance. …”
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Development of Navigation Network Models for Indoor Path Planning Using 3D Semantic Point Clouds by Jiwei Hou, Patrick Hübner, Dorota Iwaszczuk

“…Three-dimensional semantic point clouds provide valuable spatial and semantic information for navigation tasks. …”
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Ice crystal complexity leads to weaker ice cloud radiative heating in idealized single-column simulations by E. I. Sepulveda Araya, S. C. Sullivan, S. C. Sullivan, A. Voigt

“…To better predict ice cloud radiative effects, there has been a continuous effort to account for more ice crystal habits and complexity in current radiative transfer calculations. …”
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Overview of object detection methods based on LiDAR point cloud under adverse weather conditions by Yutian WU, Qing LI, Wenwei SUN, Heng WANG, Weiran WANG

“…This study comprehensively reviews state-of-the-art object detection methods based on LiDAR point clouds under adverse weather conditions. To establish the research background, we first summarize the basic concepts, tasks, methods, and evaluation metrics of point cloud object detection while analyzing the specific effects of adverse weather on detection performance. …”
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Radiative closure assessment of retrieved cloud and aerosol properties for the EarthCARE mission: the ACMB-DF product by H. W. Barker, J. N. S. Cole, N. Villefranque, Z. Qu, A. Velázquez Blázquez, C. Domenech, S. L. Mason, R. J. Hogan

“…<p>Measurements made by three instruments aboard the EarthCARE satellite, plus data from auxiliary sources, will be used synergistically to retrieve estimates of cloud and aerosol properties. The ACMB-DF processor consists of a continuous radiative closure assessment of these retrievals and is both described and demonstrated in this study. …”
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Assurance in Advanced 5G Edge Continuum by Filippo Berto, Claudio A. Ardagna, Massimo Banzi, Marco Anisetti

“…The implementation of distributed applications is more frequently achieved through the configuration of service-oriented workflows, which are then deployed within the Edge-Cloud Continuum. This approach facilitates the support of distributed processing pipelines. …”
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Achieving cloud resource optimization with trust-based access control: A novel ML strategy for enhanced performance by Bala Subramanian C, Bharathi ST, Shanmugapriya S

“…Cloud computing continues to rise, increasing the demand for more intelligent, rapid, and secure resource management. …”
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Virtual Simulation Management of Data Traffic Optimization of Big Data Cloud Platform considering Multipoint Mapping Algorithm by Haibo Wu

“…With the continuous development of Internet, cloud computing, and other technologies, build a cloud platform based on Cloud Computing Center, but how to effectively carry out operation and maintenance and face users to ensure the continuity and effectiveness of the platform is extremely important. …”
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Machine learning model design for high performance cloud computing &amp; load balancing resiliency: An innovative approach by Nilayam Kumar Kamila, Jaroslav Frnda, Subhendu Kumar Pani, Rashmi Das, Sardar M.N. Islam, P.K. Bharti, Kamalakanta Muduli

“…In this paper, we propose and integrate the concept of high-performance computing with artificial intelligence machine learning techniques in cloud platforms. The networking and computing performance data are used to validate, predict and classify the traffic and performance patterns and ensure system performance and continuous traffic flow resiliency decisions. …”
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SIG-ShapeFormer: A Multi-Scale Spatiotemporal Feature Fusion Network for Satellite Cloud Image Classification by Xuan Liu, Zhenyu Lu, Bingjian Lu, Zhuang Li, Zhongfeng Chen, Yongjie Ma

“…SIG-Shapeformer is particularly suitable for remote sensing applications involving continuous temporal sequences, such as extreme weather warnings and dynamic cloud system monitoring. …”
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Scene Target 3D Point Cloud Reconstruction Technology Combining Monocular Focus Stack and Deep Learning by Yanzhu Hu, Yingjian Wang, Song Wang

“…The method first collects multiple frames of continuous images at different focal lengths of the scene, using a divide and conquer algorithm strategy, uplink uses YOLO neural network to identify the target in 3D space and track the position information; the downlink reconstructs the four-dimensional (4D) light field data based on the focus stack image frequency domain back projection, and then uses light field imaging technology to invert the scene parallax; subsequently, achieve scene depth estimation and reconstruction of all focus image; finally, the uplink and downlink are merged to realize the reconstruction of the 3D point cloud of the space target. …”
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Space‐Borne Cloud‐Native Satellite‐Derived Bathymetry (SDB) Models Using ICESat‐2 And Sentinel‐2 by N. Thomas, A. P. Pertiwi, D. Traganos, D. Lagomasino, D. Poursanidis, S. Moreno, L. Fatoyinbo

“…Here we fuse ICESat‐2 lidar data with Sentinel‐2 optical imagery, within the Google Earth Engine cloud platform, to create openly available spatially continuous high‐resolution bathymetric maps at regional‐to‐national scales in Florida, Crete and Bermuda. …”
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Edge-Cloud Synergy for AI-Enhanced Sensor Network Data: A Real-Time Predictive Maintenance Framework by Kaushik Sathupadi, Sandesh Achar, Shinoy Vengaramkode Bhaskaran, Nuruzzaman Faruqui, M. Abdullah-Al-Wadud, Jia Uddin

“…A K-Nearest Neighbors (KNNs) model is deployed on edge devices to detect anomalies in real-time, reducing the need for continuous data transfer to the cloud. Meanwhile, a Long Short-Term Memory (LSTM) model in the cloud analyzes time-series data for predictive failure analysis, enhancing maintenance scheduling and operational efficiency. …”
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Parallel Simulation Multi-Sample Task Scheduling Approach Based on Deep Reinforcement Learning in Cloud Computing Environment by Yuhao Xiao, Yping Yao, Feng Zhu

“…In a real cloud environment, the proposed method demonstrates runtime reductions of 4–11% and execution cost savings of 11–22% compared to the Round-Robin algorithm, Best Fit algorithm, and genetic algorithm.…”
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CLF3D: A Coarse-Labeling Framework to Facilitate 3D Object Detection in Point Clouds by Nuo Cheng, Chuanyu Luo, Han Li, Sikun Ma, Shengguang Lei, Pu Li

“…Tremendous scenarios have to be considered for autonomous driving, leading to extremely large amount of point cloud data which need to be labeled for model training. …”
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A near-optimal resource allocation strategy for minimizing the worse-case impact of malicious attacks on cloud networks by Yu-Fang Chen, Frank Yeong-Sung Lin, Kuang-Yen Tai, Chiu-Han Hsiao, Wei-Hsin Wang, Ming-Chi Tsai, Tzu-Lung Sun

“…Despite existing detection systems, sophisticated attacks continue to evade identification. This study presents a novel, optimization-based resource allocation strategy designed to mitigate the worst-case impacts of hacker computing attacks in cloud computing centers. …”
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The Research on Path Planning Method for Detecting Automotive Steering Knuckles Based on Phased Array Ultrasound Point Cloud by Yihao Mao, Jun Tu, Huizhen Wang, Yangfan Zhou, Qiao Wu, Xu Zhang, Xiaochun Song

“…To address the challenges of automatic detection caused by the variation of surface normal vectors in automotive steering knuckles, an automatic detection method based on ultrasonic phased array technology is herein proposed. First, a point cloud model of the workpiece was constructed using ultrasonic distance measurement, and Gaussian-weighted principal component analysis was used to estimate the normal vectors of the point cloud. …”
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Multi-Modal Excavator Activity Recognition Using Two-Stream CNN-LSTM with RGB and Point Cloud Inputs by Hyuk Soo Cho, Kamran Latif, Abubakar Sharafat, Jongwon Seo

“…A comprehensive dataset comprising 495,000 video frames of synchronized RGB and point cloud data was collected across multiple construction sites under varying conditions. …”
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Unmanned Ground Vehicles for Continuous Crop Monitoring in Agriculture: Assessing the Readiness of Current ICT Technology by Maurizio Agelli, Nicola Corona, Fabio Maggio, Paolo Vincenzo Moi

“…This review evaluates the current state of ICT technology to determine if it supports autonomous, continuous crop monitoring. The focus is on shifting from traditional cloud-based approaches, where data are sent to remote computers for deferred processing, to a hybrid design emphasizing edge computing for real-time analysis in the field. …”
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