Enhancing Clear Radiance Generation for Geostationary Hyperspectral Infrared Sounder Using High Temporal Resolution Information by Di Di, Jun Li, Zhenglong Li, Jing Zheng, Xinya Gong

“…Abstract With high spatio‐temporal resolution geostationary hyperspectral infrared sounder (GeoHIS) observations, monitoring, and predicting rapidly changing weather events are expected to be improved with continuous information of 3D weather cube. However, due to the nature of radiation, clouds prevent an adequate retrieval of atmospheric thermodynamic information under clear‐sky conditions due to large uncertainties in the current radiative transfer model. …”
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A comparative cloud-based view of adherence data over 1 year of CPAP versus APAP uses in OSA patients: Adherence depends on PAP device by Arup K. Haldar, Raja Dhar, Somnath Maity, Shyam Krishnan, Amrita Bhattacharya, Milind Sovani

“…The telemonitoring gives an opportunity to track a group of patients on cloud-based devices. In this study, we followed up patients with this cloud-based method for more than a year and followed up two different cohorts who are on continuous PAP (CPAP) and auto adjusting PAP (APAP) devices. …”
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Penerapan Mekanisme Continuous Deployment dalam Pengembangan dan Pembaruan Perangkat Lunak Sistem Benam Berbasis Internet of Things by Yohanna Fransiska Aladina, Adhitya Bhawiyuga, Reza Andria Siregar, Primantara Hari Trisnawan

“…This research on software updates on IoT devices using continuous deployment is carried out in the cloud from these problems. …”
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Robust Pose Estimation for Noncooperative Spacecraft Under Rapid Inter-Frame Motion: A Two-Stage Point Cloud Registration Approach by Mingyuan Zhao, Long Xu

“…The second stage refines the solution through geometry-aware fine registration using raw point cloud data, enhancing precision through a multi-scale iterative ICP-like framework. …”
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A Cloud-Based Framework for Creating Scalable Machine Learning Models Predicting Building Energy Consumption from Digital Twin Data by Elham Mahamedi, Alaeldin Suliman, Martin Wonders

“…This study aims to address both drawbacks by developing a scalable cloud-based framework for the prediction of the building energy consumption. …”
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Unsupervised Deep Clustering on Spatiotemporal Objects Extracted from 4D Point Clouds for Automatic Identification of Topographic Processes in Natural Environments by J. Wang, K. Anders

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A Multi-Sensor Fusion Approach Combined with RandLA-Net for Large-Scale Point Cloud Segmentation in Power Grid Scenario by Tianyi Li, Shuanglin Li, Zihan Xu, Nizar Faisal Alkayem, Qiao Bao, Qiang Wang

“…With the continuous expansion of power grids, traditional manual inspection methods face numerous challenges, including low efficiency, high costs, and significant safety risks. …”
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Extraction of typical oyster pile columns in the Maowei Sea, Beibu Gulf, based on unmanned aerial vehicle laser point cloud orthophotos by Jinze Du, Jinze Du, Meiqin Huang, Zhenjun Kang, Zhenjun Kang, Zhenjun Kang, Yichao Tian, Yichao Tian, Yichao Tian, Jin Tao, Jin Tao, Qiang Zhang, Qiang Zhang, Yutong Xie, Yutong Xie, Yutong Xie, Jinying Mo, Jinying Mo, LiYan Huang, LiYan Huang, Yusheng Feng, Yusheng Feng

“…It utilizes multi-spectral image data from unmanned aerial vehicles (UAVs), light detection and ranging (LiDAR) point cloud technology, and deep learning algorithms to extract representative oyster pile columns in Maowei Sea within Beibu Gulf. …”
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Transfer Learning Based on Multi-Branch Architecture Feature Extractor for Airborne LiDAR Point Cloud Semantic Segmentation with Few Samples by Jialin Yuan, Hongchao Ma, Liang Zhang, Jiwei Deng, Wenjun Luo, Ke Liu, Zhan Cai

“…The proposed MFE is based on a novel multi-branch architecture integrating Neighborhood Embedding Block (NEB) and Point Transformer Block (PTB); it aims to extract heterogeneous features (e.g., geometric features, reflectance features, and internal structural features) by leveraging the parameters contained in ALS point clouds. To address model transfer, a three-stage strategy was developed: (1) A pre-training subtask was employed to pre-train the proposed MFE if the source domain consisted of multi-source ALS data, overcoming parameter differences. (2) A domain adaptation subtask was employed to align cross-domain feature distributions between source and target domains. (3) An incremental learning subtask was proposed for continuous learning of novel categories in the target domain, avoiding catastrophic forgetting. …”
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LiDGS: An efficient 3D reconstruction framework integrating lidar point clouds and multi-view images for enhanced geometric fidelity by Li Yan, Jiang Song, Hong Xie, Pengcheng Wei, Gang Li, Longze Zhu, Zhongli Fan, Shucheng Gong

“…To address this challenge, we propose a novel 3D reconstruction approach within the 3DGS framework, integrating lidar point clouds and multi-view images, named LiDGS, which achieves high-fidelity 3D scene reconstruction by introducing high-precision geometric a priori information and multiple geometric constraints from lidar point clouds, while guaranteeing efficient and accurate scene rendering. …”
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Study of optical scattering properties and direct radiative effects of high-altitude cirrus clouds in Barcelona, Spain, with 4 years of lidar measurements by C. Gil-Díaz, M. Sicard, M. Sicard, M. Sicard, O. Sourdeval, A. Saiprakash, C. Muñoz-Porcar, A. Comerón, A. Rodríguez-Gómez, D. C. F. D. S. Oliveira

“…This study presents a comprehensive analysis of optical scattering properties and direct radiative effect of cirrus clouds based on 4 years of continuous ground-based lidar measurements with the Barcelona (Spain) Micro Pulse Lidar. …”
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Survey on Replay-Based Continual Learning and Empirical Validation on Feasibility in Diverse Edge Devices Using a Representative Method by Heon-Sung Park, Hyeon-Chang Chu, Min-Kyung Sung, Chaewoon Kim, Jeongwon Lee, Dae-Won Kim, Jaesung Lee

“…The limitations of replay-based continuous learning are (1) the limited amount of historical training data that can be stored due to limited memory capacity, and (2) the computational resources of on-device systems are significantly lower than those of servers or cloud infrastructures. …”
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Adapting Sensory Analysis to the Pandemic Era: Exploring “Remote Home Tasting” of Sous-Vide Chicken Breast for Research Continuity by Francesca Masino, Giuseppe Montevecchi, Andrea Antonelli, Domenico Pietro Lo Fiego, Patrizia Fava, Roberta Foligni, Andrea Pulvirenti

“…Judges tasted 6 out of 13 randomized samples, recording intensities on a cloud-based sensory card. Results: Judges demonstrated good repeatability and panel homogeneity (RSD ≤ 30%). …”
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Tomographic reconstruction algorithms for retrieving two-dimensional ice cloud microphysical parameters using along-track (sub)millimeter-wave radiometer observations by Y. Liu, Y. Liu, I. S. Adams

“…<p>The submillimeter-wave radiometer operating in the along-track scanning mode continuously collects brightness temperature (TB) data over a two-dimensional (2D) cloud cross-section as the platform moves forward. …”
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Continuous Estimates of Glacier Mass Balance in High Mountain Asia Based on ICESat‐1,2 and GRACE/GRACE Follow‐On Data by Qiuyu Wang, Shuang Yi, Wenke Sun

“…We determined the recent status of HMA glaciers based on the first analysis of Ice, Cloud, and Land Elevation Satellite‐2 (ICESat‐2) data. …”
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Mimic storage scheme based on regenerated code by Yue CHEN, Longjiang WANG, Xincheng YAN, Xinyue ZHANG

“…Aiming to solve security threats in the cloud storage system due to static storage architecture and storage mode,a mimic storage scheme based on regenerated code was proposed.The scheme used network coding scheme to store the data in the cloud data node,and used mimicry transformation mechanism based on regeneration code to change data storage state dynamically according to the random time-varying factors,which could guarantee data integrity and data availability continuously.The mimicry transformation mechanism is a random,time-varying and dynamic scheme,which increases the uncertainty of storage system.It blocks and interferes with the attack chain,increases the difficulty and cost of the attack operation,and improves the security and reliability of the system.…”
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Evaluating DL Model Scaling Trade-Offs During Inference via an Empirical Benchmark Analysis by Demetris Trihinas, Panagiotis Michael, Moysis Symeonides

“…However, with recent advancements in edge computing and 5G networks, DL models are now aggressively being deployed and utilized across the cloud–edge–IoT continuum for the realization of in situ intelligent IoT services. …”
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Uso de Métodos Monte Carlo na Modelagem de uma Nuvem Radioativa Natural by Gutemberg Luiz Sales Claudino, José Wilson Vieira, Viriato Leal Neto, Fernando Roberto Andrade Lima, Alisson Fernando Silva, Joana Caroline Lopes Soares

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Assessing the Potential of the Cloud-Based EEFlux Tool to Monitor the Water Use of <i>Moringa oleifera</i> in a Semi-Arid Region of South Africa by Shaeden Gokool, Alistair Clulow, Nadia A. Araya

“…(<i>M. oleifera</i>) has steadily increased over the past few decades, and interest in the crop continues to rise due to its unique multi-purpose properties. …”
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Algorithms for online fault tolerance server consolidation by Boyu Li, Bin Wu, Meng Shen, Hao Peng, Weisheng Li, Hong Zhang, Jie Gan, Zhihong Tian, Guangquan Xu

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