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Journal articles on the topic 'Point cloud recovery'

Author: Grafiati

Published: 24 June 2021

Last updated: 29 July 2025

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1

Nie, Ziming, Qiao Wu, Chenlei Lv, et al. "SPU-IMR: Self-supervised Arbitrary-scale Point Cloud Upsampling via Iterative Mask-recovery Network." Proceedings of the AAAI Conference on Artificial Intelligence 39, no. 6 (2025): 6236–44. https://doi.org/10.1609/aaai.v39i6.32667.

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Point cloud upsampling aims to generate dense and uniformly distributed point sets from sparse point clouds. Existing point cloud upsampling methods typically approach the task as an interpolation problem. They achieve upsampling by performing local interpolation between point clouds or in the feature space, then regressing the interpolated points to appropriate positions. By contrast, our proposed method treats point cloud upsampling as a global shape completion problem. Specifically, our method first divides the point cloud into multiple patches. Then a masking operation is applied to remove

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Zhou, Rong, Hua Sun, Kaisen Ma, et al. "Improving Estimation of Tree Parameters by Fusing ALS and TLS Point Cloud Data Based on Canopy Gap Shape Feature Points." Drones 7, no. 8 (2023): 524. http://dx.doi.org/10.3390/drones7080524.

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Airborne laser scanning (ALS) and terrestrial laser scanning (TLS) are two ways to obtain forest three-dimensional (3D) spatial information. Due to canopy occlusion and the features of different scanning methods, some of the forest point clouds acquired by a single scanning platform may be missing, resulting in an inaccurate estimation of forest structure parameters. Hence, the registration of ALS and TLS point clouds is an alternative for improving the estimation accuracy of forest structure parameters. Currently, forest point cloud registration is mainly conducted based on individual tree at

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Zhang, Jianmin, Jiale Long, Zihao Du, Yi Ding, Yuyang Peng, and Jiangtao Xi. "Three-Dimensional Point Cloud-Filtering Method Based on Image Segmentation and Absolute Phase Recovery." Electronics 12, no. 12 (2023): 2749. http://dx.doi.org/10.3390/electronics12122749.

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In three-dimensional (3D) shape measurement based on fringe projection, various factors can degrade the quality of the point cloud. Existing point cloud filtering methods involve analyzing the geometric relationship between 3D space and point cloud, which poses challenges such as complex calculation and low efficiency. To improve the accuracy and speed of point cloud filtering, this paper proposes a new point cloud filtering method based on image segmentation and the absolute phase for the 3D imaging obtained by fringe projection. Firstly, a two-dimensional (2D) point cloud mapping image is es

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Hitesh Premshankar Rai, Pavan Ogeti, Narendra Sharad Fadnavis, Gireesh Bhaulal Patil, and Uday Krishna Padyana. "Disaster Recovery in Cloud Environments: Strategies for Business Continuity." International Journal for Research Publication and Seminar 10, no. 3 (2019): 111–21. http://dx.doi.org/10.36676/jrps.v10.i3.1460.

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The most important components of a firm are business continuity and disaster recovery planning, although they are often disregarded. Even before a crisis strikes, businesses need to have a well-organized strategy and documentation for business continuity and recovery after a disaster. A single cloud is characterised as a collection of servers housed in one or more data centres that are provided by a single supplier. Nonetheless, there are several reasons why switching from a single cloud to multiple clouds is sensible and crucial. For example, single cloud providers are still vulnerable to out

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Kresslein, Jacob, Payam Haghighi, Jaejong Park, Satchit Ramnath, Alok Sutradhar, and Jami J. Shah. "Automated cross-sectional shape recovery of 3D branching structures from point cloud." Journal of Computational Design and Engineering 5, no. 3 (2017): 368–78. http://dx.doi.org/10.1016/j.jcde.2017.11.010.

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Abstract Many applications rely on scanned data, which can come from a variety of sources: optical scanners, coordinate measuring machines, or medical imaging. We assume that the data input to these applications is an unorganized point cloud or mesh of vertices. The objective may be to find particular features (medical diagnostics or reverse engineering) or comparison to some reference geometry (e.g. dimensional metrology). This paper focuses on the feature fitting of a segmented point cloud, specifically for branched, organic structures or structural frames, and targets non-monolithic geometr

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Li, Lin, Huajun Wang, and Sen Wang. "Compressing and Recovering Short-Range MEMS-Based LiDAR Point Clouds Based on Adaptive Clustered Compressive Sensing and Application to 3D Rock Fragment Surface Point Clouds." Sensors 24, no. 17 (2024): 5695. http://dx.doi.org/10.3390/s24175695.

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Short-range MEMS-based (Micro Electronical Mechanical System) LiDAR provides precise point cloud datasets for rock fragment surfaces. However, there is more vibrational noise in MEMS-based LiDAR signals, which cannot guarantee that the reconstructed point cloud data are not distorted with a high compression ratio. Many studies have illustrated that wavelet-based clustered compressive sensing can improve reconstruction precision. The k-means clustering algorithm can be conveniently employed to obtain clusters; however, estimating a meaningful k value (i.e., the number of clusters) is challengin

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Su, Yunlian, Zhibo Chen, and Xiaojing Xue. "TreeDBH: Dual Enhancement Strategies for Tree Point Cloud Completion in Medium–Low Density UAV Data." Forests 16, no. 4 (2025): 667. https://doi.org/10.3390/f16040667.

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Medium–low density UAV point clouds often suffer from incomplete lower canopy structures and sparse distributions due to self-occlusion. While existing point cloud completion models achieve high metric accuracy, they inadequately address missing regions in trunks and lower canopy areas. To resolve these issues, this paper proposes a hierarchical random sampling strategy and a spatially constrained loss function. First, we dynamically stratify point clouds based on density distribution characteristics, employing hierarchical random sampling to preserve proportional representation of lower-level

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Barazzetti, Luigi. "Point cloud occlusion recovery with shallow feedforward neural networks." Advanced Engineering Informatics 38 (October 2018): 605–19. http://dx.doi.org/10.1016/j.aei.2018.09.007.

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Liang, Yan, Ye Hua Sheng, and Ka Zhang. "Method on 3D Dense Point Cloud Recovery of Geographical Scene." Advanced Materials Research 748 (August 2013): 619–23. http://dx.doi.org/10.4028/www.scientific.net/amr.748.619.

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The object of this research is to reconstruct 3D dense point cloud of geographical scene. With the technology and method of computer vision , first affine invariant features are extracted and matched, then cameras parameters and 3D dense point cloud are recovered and united under geographical reference. The experimental results show that this method with low cost and high precision of centimeters can satisfy the requirements of measurement, modeling and virtual reality.

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Yu, Fan, and Xue Fan. "3D Reconstruction System Based on Multi Sensor." International Journal of Advanced Network, Monitoring and Controls 7, no. 2 (2022): 58–66. http://dx.doi.org/10.2478/ijanmc-2022-0016.

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Abstract In the 3d dense map construction system of indoor scene by mobile robot, the existing single sensor method cannot improve the positioning accuracy and reconstruction accuracy of robot, as well as the requirement of rapidity. Therefore, it is applied to THE ORB-SLAM with three parallel threads of track tracking, map reconstruction and loopback detection. Through depth camera pose to splice point cloud of building three-dimensional dense point cloud, in the 3 d reconstruction, a computer can not rely on GPU parallel computing, using only the CPU recovery environment three-dimensional de

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Wongwailikhit, Kanda, Pienpak Tasakorn, Pattarapan Prasassarakich, and Makoto Aratono. "Gold Recovery by pH-Switching Process via Cloud Point Extraction." Separation Science and Technology 38, no. 14 (2003): 3591–607. http://dx.doi.org/10.1081/ss-120023420.

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Monisha., S., and S. Venkateshkumar Dr. "Cloud Computing in Data Backup and Data Recovery." International Journal of Trend in Scientific Research and Development 2, no. 6 (2018): 865–67. https://doi.org/10.31142/ijtsrd18652.

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Data backup and Disaster Recovery Business Continuity issues are appropriate essential in networks since the importance and shared value of digital data is continuously rising. Every organization requires business continuity plan or disaster recovery plan and data backup which reduce within the cost constraints while achieving the target recovery requirements in terms of recovery time objective and recovery point objective. The aim of this paper is to overview of various techniques in data backup and disaster recovery in the cloud environment. Monisha. S | Dr. S. Venkateshkumar "Cloud Com

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Dileep, Valiki. "Approaches to Disaster Recovery in Cloud Databases: A Comparative Analysis of Current Mechanisms." International Journal of Engineering and Computer Science 11, no. 12 (2024): 25634–46. http://dx.doi.org/10.18535/ijecs/v11i12.4709.

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Disaster recovery (DR) is a critical aspect of maintaining the availability, integrity, and continuity of cloud databases, which store and manage vast amounts of mission-critical data. With the increasing reliance on cloud platforms for business operations, organizations must implement effective disaster recovery mechanisms to safeguard against data loss, downtime, and system failures. This paper presents a comparative analysis of current disaster recovery approaches in cloud databases, examining the strengths and weaknesses of various strategies, including backup and restore, data replication

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Velmurugan, Dhakshnamoorthy. "Revolutionizing Disaster Recovery: Fully Automated Cloud Solutions." European Journal of Advances in Engineering and Technology 11, no. 12 (2024): 1–2. https://doi.org/10.5281/zenodo.14540055.

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In today's digital landscape, seamless business continuity and disaster recovery (DR) are essential. This article explores an innovative DR solution implemented in Oracle Cloud Infrastructure (OCI) across Ashburn and Singapore regions, using Ansible and Jenkins for full automation. The solution allows for independent, on-demand DR switches with minimal manual intervention, achieving excellent recovery time objectives (RTO) and recovery point objectives (RPO). It includes real-time data synchronization using Oracle Data Guard, automated switch-over processes, and integration with third-party sy

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Prasetio, Barlian Henryranu, Edita Rosana Widasari, Adi Setiawan, and Hanifa Maulani Ramadhan. "Village Data Backup and Disaster Recovery: A Comparative Study of Cloud Solutions with Traditional Methods." Journal of Information Technology and Computer Science 9, no. 3 (2024): 218–35. https://doi.org/10.25126/jitecs.93681.

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This study presents a comparative analysis of traditional disk-based and cloud-based Backup and Disaster Recovery (DR) approaches, focusing on the challenges inherent in existing solutions, such as high infrastructure costs, extended recovery times, and operational disruptions during software updates. Conventional disk-based systems often require periodic reboots and manual interventions, which can interrupt ongoing operations. In contrast, cloud-based solutions, particularly Asigra, offer a streamlined alternative by reducing infrastructure dependency, enhancing recovery metrics—specifically

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Hillman, Samuel, Luke Wallace, Karin Reinke, Bryan Hally, Simon Jones, and Daisy S. Saldias. "A Method for Validating the Structural Completeness of Understory Vegetation Models Captured with 3D Remote Sensing." Remote Sensing 11, no. 18 (2019): 2118. http://dx.doi.org/10.3390/rs11182118.

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Characteristics describing below canopy vegetation are important for a range of forest ecosystem applications including wildlife habitat, fuel hazard and fire behaviour modelling, understanding forest recovery after disturbance and competition dynamics. Such applications all rely on accurate measures of vegetation structure. Inherent in this is the assumption or ability to demonstrate measurement accuracy. 3D point clouds are being increasingly used to describe vegetated environments, however limited research has been conducted to validate the information content of terrestrial point clouds of

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Michałowska, Aleksandra, Olga Kupczyk, and Andrzej Czyrski. "The Chemometric Evaluation of the Factors Influencing Cloud Point Extraction for Fluoroquinolones." Pharmaceutics 15, no. 6 (2023): 1774. http://dx.doi.org/10.3390/pharmaceutics15061774.

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This study aimed to analyze the factors that impact the cloud point extraction of ciprofloxacin, levofloxacin, and moxifloxacin. The following independent variables were analyzed: Triton X-114 concentration, NaCl concentration, pH, and incubation temperature. The dependent variable studied was recovery. A central composite design model was used. The applied quantitation method was HPLC. The method was validated for linearity, precision, and accuracy. The results underwent ANOVA® analysis. The polynomial equations were generated for each analyte. The response surface methodology graphs visualiz

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Zein Samira, Yodit Wondaferew Weldegeorgise, Olajide Soji Osundare, Harrison Oke Ekpobimi, and Regina Coelis Kandekere. "Disaster recovery framework for ensuring SME business continuity on cloud platforms." Computer Science & IT Research Journal 5, no. 10 (2024): 2244–62. http://dx.doi.org/10.51594/csitrj.v5i10.1620.

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Disaster recovery (DR) is a critical component of ensuring business continuity, especially for Small and Medium-sized Enterprises (SMEs) that rely heavily on cloud platforms for their operations. SMEs face unique challenges, including limited financial and technical resources, making it essential to develop a disaster recovery framework that is both cost-effective and robust. This proposes a disaster recovery framework that minimizes downtime and data loss, leveraging the capabilities of cloud platforms to ensure continuous business operations. The proposed framework focuses on three key objec

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Lu, Rui, Bihai Zhang, and Dan Wang. "VVRec: Reconstruction Attacks on DL-based Volumetric Video Upstreaming via Latent Diffusion Model with Gamma Distribution." Proceedings of the AAAI Conference on Artificial Intelligence 39, no. 18 (2025): 19133–42. https://doi.org/10.1609/aaai.v39i18.34106.

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With the popularity of 3D volumetric video applications, such as Autonomous Driving, Virtual Reality, and Mixed Reality, current developers have turned to deep learning for compressing volumetric video frames, i.e., point clouds for video upstreaming. The latest deep learning-based solutions offer higher efficiency, lower distortion, and better hardware support compared to traditional ones like MPEG and JPEG. However, privacy threats arise, especially reconstruction attacks targeting to recover the original input point cloud from the intermediate results. In this paper, we design VVRec, to the

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Researcher. "SIMPLIFYING AZURE SITE RECOVERY: A COMPREHENSIVE ANALYSIS OF CLOUD-BASED DISASTER RECOVERY SOLUTIONS." International Journal of Computer Engineering and Technology (IJCET) 15, no. 6 (2024): 1091–98. https://doi.org/10.5281/zenodo.14287093.

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This article presents a comprehensive analysis of Azure Site Recovery as a cloud-based disaster recovery solution, examining its architecture, implementation frameworks, and real-world performance metrics in orchestrated failover scenarios. The article evaluates the platform's effectiveness across multiple dimensions, including replication mechanisms, manually initiated recovery processes, integration capabilities, and economic implications. Through extensive analysis of deployment scenarios and performance data, the research demonstrates significant improvements in recovery time objectives (R

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Zein Samira, Yodit Wondaferew Weldegeorgise, Olajide Soji Osundare, Harrison Oke Ekpobimi, and Regina Coelis Kandekere. "Comprehensive data security and compliance framework for SMEs." Magna Scientia Advanced Research and Reviews 12, no. 1 (2024): 043–55. http://dx.doi.org/10.30574/msarr.2024.12.1.0146.

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Small and Medium-sized Enterprises (SMEs) are increasingly relying on cloud platforms to support critical business operations, making effective disaster recovery (DR) strategies essential for ensuring business continuity. This review proposes a robust disaster recovery framework tailored for SMEs, designed to minimize downtime and data loss in the event of a system failure, cyberattack, or natural disaster. The framework integrates advanced cloud technologies to create a cost-effective, scalable solution that aligns with the resource constraints of SMEs while providing enterprise-grade resilie

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Xue, Jiaming, Chaoguang Men, Yongmei Liu, and Shun Xiong. "Adaptive neighbourhood recovery method for machine learning based 3D point cloud classification." International Journal of Remote Sensing 44, no. 1 (2023): 311–40. http://dx.doi.org/10.1080/01431161.2022.2162354.

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Giovanoudis, Ioannis, Vassilis Athanasiadis, Theodoros Chatzimitakos, Olga Gortzi, George D. Nanos, and Stavros I. Lalas. "Development of a Cloud Point Extraction Technique Based on Lecithin for the Recovery of Carotenoids from Liquid Tomato Wastewater." Waste 1, no. 1 (2022): 105–14. http://dx.doi.org/10.3390/waste1010008.

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The traditional extraction methods used to recover natural antioxidants from food industry wastes involve significant amounts of hazardous solvents. A viable alternative is the use of non-toxic surfactants to remove organic compounds from wastes at temperatures above the cloud point. Cloud point extraction has only recently begun to be used to recover high-value added compounds from food industry wastes. In the current work, a method for the isolation of high-value added components from liquid tomato wastewater using a cloud point extraction method was developed and optimized. Food-grade lecit

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Venkata, Raman Immidisetti. "Seamless VMware Workload Migration to Microsoft Azure Using Zerto: A Hypervisor-Based Replication Approach." INTERNATIONAL JOURNAL OF INNOVATIVE RESEARCH AND CREATIVE TECHNOLOGY 8, no. 5 (2022): 1–6. https://doi.org/10.5281/zenodo.14944996.

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The adoption of hybrid cloud architectures is strategic for enterprises integrating on-premises VMware environments with Microsoft Azure for enhanced scalability, flexibility, and disaster recovery (DR). Organizations face challenges migrating workloads to different Azure regions due to conflicts between Azure Site Recovery (ASR) and Azure Migrate, which use agent-based replication. These conflicts cause operational inefficiencies, replication failures, and data inconsistencies, complicating cloud migration efforts. This study investigates Zerto as an efficient alternative for workload migrati

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Hosseinyalamdary, S., and A. Yilmaz. "3D SUPER-RESOLUTION APPROACH FOR SPARSE LASER SCANNER DATA." ISPRS Annals of Photogrammetry, Remote Sensing and Spatial Information Sciences II-3/W5 (August 19, 2015): 151–57. http://dx.doi.org/10.5194/isprsannals-ii-3-w5-151-2015.

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Laser scanner point cloud has been emerging in Photogrammetry and computer vision to achieve high level tasks such as object tracking, object recognition and scene understanding. However, low cost laser scanners are noisy, sparse and prone to systematic errors. This paper proposes a novel 3D super resolution approach to reconstruct surface of the objects in the scene. This method works on sparse, unorganized point clouds and has superior performance over other surface recovery approaches. Since the proposed approach uses anisotropic diffusion equation, it does not deteriorate the object bounda

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Liu, Zhiqi, Geling Yin, Mingqiang Luo, Jinrong Zhang, and Cheekeat Heng. "Integrated Waverider Forebody/Inlet Fusion Method Based on Discrete Point Cloud Reconstruction." Aerospace 11, no. 7 (2024): 597. http://dx.doi.org/10.3390/aerospace11070597.

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The integrated design of waverider forebodies and inlets is considered a critical challenge in high Mach number vehicle development. To facilitate the rapid construction of integrated geometrical models for waverider forebodies and inlets during the conceptual design phase, a method based on discrete point cloud reconstruction has been proposed. In this method, the geometries of the waverider body and inlet are used as inputs and decomposed into the point cloud under discrete rules. This point cloud is refitted to generate new section lines, which are then lofted into an integrated shape under

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Jones, Caren E., Angeline Van Dongen, Jolan Aubry, Stefan G. Schreiber, and Dani Degenhardt. "Use of Mobile Laser Scanning (MLS) to Monitor Vegetation Recovery on Linear Disturbances." Forests 13, no. 11 (2022): 1743. http://dx.doi.org/10.3390/f13111743.

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Seismic lines are narrow, linear corridors cleared through forests for oil and gas exploration. Their inconsistent recovery has led to Alberta’s forests being highly fragmented, resulting in the need for seismic line restoration programs and subsequent monitoring. Light detection and ranging (LiDAR) is becoming an increasingly popular technology for the fast and accurate measurement of forests. Mobile LiDAR scanners (MLS) are emerging as an alternative to traditional aerial LiDAR due to their increased point cloud density. To determine whether MLS could be effective for collecting vegetation d

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Researcher. "LEVERAGING KUBERNETES AND AI FOR IMPROVED DISASTER RECOVERY IN CLOUD COMPUTING." International Journal of Computer Engineering and Technology (IJCET) 15, no. 6 (2024): 1160–67. https://doi.org/10.5281/zenodo.14330367.

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This article presents a groundbreaking approach to disaster recovery in cloud computing by integrating Artificial Intelligence (AI) capabilities with Kubernetes container orchestration. The article introduces a novel multi-layered architecture that combines deep learning-based predictive analytics, automated recovery mechanisms, and intelligent resource optimization algorithms to enhance system resilience and minimize downtime. Our framework demonstrated remarkable improvements in key performance metrics through extensive testing across geographically distributed clusters, achieving a 73% redu

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Li, Hanxuan, Bin Fu, Ruiping Wang, and Xilin Chen. "Point2Real: Bridging the Gap between Point Cloud and Realistic Image for Open-World 3D Recognition." Proceedings of the AAAI Conference on Artificial Intelligence 38, no. 4 (2024): 3055–63. http://dx.doi.org/10.1609/aaai.v38i4.28088.

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Recognition in open-world scenarios is an important and challenging field, where Vision-Language Pre-training paradigms have greatly impacted the 2D domain. This inspires a growing interest in introducing 2D pre-trained models, such as CLIP, into the 3D domain to enhance the ability of point cloud understanding. Considering the difference between discrete 3D point clouds and real-world 2D images, reducing the domain gap is crucial. Some recent works project point clouds onto a 2D plane to enable 3D zero-shot capabilities without training. However, this simplistic approach leads to an unclear o

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Chen, Honghua, Mingqiang Wei, Yangxing Sun, Xingyu Xie, and Jun Wang. "Multi-Patch Collaborative Point Cloud Denoising via Low-Rank Recovery with Graph Constraint." IEEE Transactions on Visualization and Computer Graphics 26, no. 11 (2020): 3255–70. http://dx.doi.org/10.1109/tvcg.2019.2920817.

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Fellechner, Oliver, and Irina Smirnova. "Feasibility of packed columns for continuous cloud point extraction with subsequent product recovery." Separation and Purification Technology 258 (March 2021): 118046. http://dx.doi.org/10.1016/j.seppur.2020.118046.

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Li, Ren-Wu, Bo Wang, Lin Gao, Ling-Xiao Zhang, and Chun-Peng Li. "High-fidelity point cloud completion with low-resolution recovery and noise-aware upsampling." Graphical Models 126 (April 2023): 101173. http://dx.doi.org/10.1016/j.gmod.2023.101173.

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Narayan Kulkarni, Neha, Shital Kumar A. Jain, and . "Survey on Data Integrity, Recovery, and Proof of Retrievability Techniques in Cloud Storage." International Journal of Engineering & Technology 7, no. 3.6 (2018): 55. http://dx.doi.org/10.14419/ijet.v7i3.6.14938.

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Recently the technologies are growing fast, so they have become the point of source and also the sink for data. Data is generated in large volume introducing the concept of structured and unstructured data evolving "Big Data" which needs large memory for storage. There are two possible solutions either increase the local storage or use the Cloud Storage. Cloud makes data available to the user anytime, anywhere, anything. Cloud allows the user to store their data virtually without investing much. However, this data is on cloud raising a concern of data security and recovery. This attack is made

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Akbar, Fillahi. "PERENCANAAN DISASTER RECOVERY BERBASIS CLOUD PADA WEB JURNAL UIN AR-RANIRY." JINTECH Journal Of Information Technology 5, no. 1 (2024): 24–31. http://dx.doi.org/10.22373/jintech.v5i1.5505.

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Era informasi saat ini telah menjadikan sistem teknologi sebagai landasan utama operasional organisasi. Dalam konteks ini, urgensi rencana Disaster Recovery (DR) menjadi suatu keharusan mutlak. DR adalah proses antisipasi dan penanganan bencana terkait teknologi oleh organisasi. Penelitian ini merupakan perencanaan Disaster Recovery berbasis Cloud dengan menggunakan Amazon Web Service (AWS) pada web Jurnal Universitas Islam Negeri Ar-Raniry (UIN Ar-Raniry). Metode yang digunakan adalah Kualitatif Deskriptif. Peneliti mengumpulkan informasi umum, informasi teknis, dan informasi tentang list ser

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Wang, De Wen, and Xiao Meng Liu. "A Solution for Single Point of Failure of Cloud Computing Platform in Electric Power Corporation." Applied Mechanics and Materials 519-520 (February 2014): 1325–28. http://dx.doi.org/10.4028/www.scientific.net/amm.519-520.1325.

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For the lack of computing, storage, information integration and other aspects in traditional electric power computing platform, it is necessary to introduce cloud computing to it and to build a cloud computing platform based on open source Hadoop to meet the requirements of smart grid. As the single point of failure of Hadoop cannot guarantee the high availability that electric power system requires, this paper gives a solution that based on hot standby mechanism and automatically failover controlled by Zookeeper, analyses availability and disaster recovery times to ensure the electric power s

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Zhao, Yadi, Lei Yan, Jian Wu, and Ximing Song. "Design and Implementation of a Digital Twin System for Log Rotary Cutting Optimization." Future Internet 16, no. 1 (2023): 7. http://dx.doi.org/10.3390/fi16010007.

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To address the low level of intelligence and low utilization of logs in current rotary cutting equipment, this paper proposes a digital twin-based system for optimizing the rotary cutting of logs using a five-dimensional model of digital twins. The system features a log perception platform to capture three-dimensional point cloud data, outlining the logs’ contours. Utilizing the Delaunay3D algorithm, this model performs a three-dimensional reconstruction of the log point cloud, constructing a precise digital twin. Feature information is extracted from the point cloud using the least squares me

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Sznek, Bartosz, Olga Kupczyk, and Andrzej Czyrski. "Cloud Point Extraction as an Environmentally Friendly Technique for Sample Preparation." Processes 13, no. 2 (2025): 430. https://doi.org/10.3390/pr13020430.

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Cloud point extraction is a sample preparation technique that involves using surfactants that are not harmful to the environment. It is based on micelle formation in which the extracted compound is encapsulated in the hydrophobic core of the micelles, which are the extracting agent. The most commonly used surfactants are nonionic. The others are anionic, cationic, or zwitterionic. The effectiveness of cloud point extraction might be enhanced by the addition of neutral salts, the application of proper pH, as well as acidic conditions and temperature. This sample preparation technique may be app

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Joarder, Rajib. "Improvement of a 'SSQuEE' Method for Recovery and Preconcentration of Pesticides from Environmental Samples." Asian Journal of Chemistry 33, no. 10 (2021): 2472–76. http://dx.doi.org/10.14233/ajchem.2021.23235.

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A simple, sensitive, quick, easy and efficient (SSQuEE) analytical technique based on cloud point extraction (CPE) has been developed for the determination of different pesticides present in soil and water with high performance liquid chromatography separation and ultraviolet detection. The environmentally friendliness surfactant like Triton X -100, compared to Tween series of non-ionic surfactant can effectively extract imidacloprid (insecticide), flusilazole (fungicide) and atrazine (herbicide) at cloud point temperature at 67 ºC, 82 ºC and 62 ºC, respectively. To reach the optimum extractio

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Weinmann, M., B. Jutzi, C. Mallet, and M. Weinmann. "GEOMETRIC FEATURES AND THEIR RELEVANCE FOR 3D POINT CLOUD CLASSIFICATION." ISPRS Annals of Photogrammetry, Remote Sensing and Spatial Information Sciences IV-1/W1 (May 30, 2017): 157–64. http://dx.doi.org/10.5194/isprs-annals-iv-1-w1-157-2017.

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In this paper, we focus on the automatic interpretation of 3D point cloud data in terms of associating a class label to each 3D point. While much effort has recently been spent on this research topic, little attention has been paid to the influencing factors that affect the quality of the derived classification results. For this reason, we investigate fundamental influencing factors making geometric features more or less relevant with respect to the classification task. We present a framework which consists of five components addressing point sampling, neighborhood recovery, feature extraction

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Materna, Katarzyna, Elzbieta Goralska, Anna Sobczynska, and Jan Szymanowski. "Recovery of various phenols and phenylamines by micellar enhanced ultrafiltration and cloud point separation." Green Chemistry 6, no. 3 (2004): 176. http://dx.doi.org/10.1039/b312343j.

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Travičić, Vanja, Teodora Cvanić, Senka Vidović, et al. "Sustainable Recovery of Polyphenols and Carotenoids from Horned Melon Peel via Cloud Point Extraction." Foods 13, no. 18 (2024): 2863. http://dx.doi.org/10.3390/foods13182863.

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Using natural plant extracts as food additives is a promising approach for improving food products’ quality, nutritional value, and safety, offering advantages for both consumers and the environment. Therefore, the main goal of this study was to develop a sustainable method for extracting polyphenols and carotenoids from horned melon peel using the cloud point extraction (CPE) technique, intending to utilize it as a natural food additive. CPE is novel promising extraction method for separation and pre-concentration of different compounds while being simple, inexpensive, and low-toxic. Three pa

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Ribeiro, Bernardo Dias, Daniel Weingart Barreto, and Maria Alice Zarur Coelho. "Recovery of Saponins from Jua (Ziziphus joazeiro) by Micellar Extraction and Cloud Point Preconcentration." Journal of Surfactants and Detergents 17, no. 3 (2013): 553–61. http://dx.doi.org/10.1007/s11743-013-1526-5.

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Kiai, Hajar, Jihane Raiti, Abdelilah El-Abbassi, and Abdellatif Hafidi. "Recovery of phenolic compounds from table olive processing wastewaters using cloud point extraction method." Journal of Environmental Chemical Engineering 6, no. 1 (2018): 1569–75. http://dx.doi.org/10.1016/j.jece.2018.05.007.

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Athanasiadis, Vassilis, Theodoros Chatzimitakos, Martha Mantiniotou, Dimitrios Kalompatsios, Eleni Bozinou, and Stavros I. Lalas. "Investigation of the Polyphenol Recovery of Overripe Banana Peel Extract Utilizing Cloud Point Extraction." Eng 4, no. 4 (2023): 3026–38. http://dx.doi.org/10.3390/eng4040170.

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Consuming fruits and vegetables necessitates discarding the inedible parts, which raises issues such as waste management and contamination of the environment. Numerous studies have been conducted in recent years in an effort to identify alternatives that reduce the negative effects of food and agricultural waste. This study aims to investigate the polyphenol recovery and the antioxidant capacity of overripe banana peel through cloud point extraction (CPE), which is a green method. The optimal conditions of the CPE were three steps of CPE with 10% w/v lecithin, which was used as surfactant, pH

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Larsen, Michael L., Clarissa A. Briner, and Philip Boehner. "On the Recovery of 3D Spatial Statistics of Particles from 1D Measurements: Implications for Airborne Instruments." Journal of Atmospheric and Oceanic Technology 31, no. 10 (2014): 2078–87. http://dx.doi.org/10.1175/jtech-d-14-00004.1.

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Abstract The spatial positions of individual aerosol particles, cloud droplets, or raindrops can be modeled as a point processes in three dimensions. Characterization of three-dimensional point processes often involves the calculation or estimation of the radial distribution function (RDF) and/or the pair-correlation function (PCF) for the system. Sampling these three-dimensional systems is often impractical, however, and, consequently, these three-dimensional systems are directly measured by probing the system along a one-dimensional transect through the volume (e.g., an aircraft-mounted clou

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Madej, Katarzyna, and Karolina Persona. "Drug screening in human plasma by cloud-point extraction and HPLC." Open Chemistry 11, no. 1 (2013): 94–100. http://dx.doi.org/10.2478/s11532-012-0134-y.

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AbstractCloud-point extraction (CPE) with RP-HPLC/DAD detection was used to develop a screen for six model basic drugs (paracetamol, promazine, amitriptyline, nortriptyline, clomipramine and chlorpromazine) in human plasma. These drugs’ varied hydrophobicities entail different affinities for the micelle-rich phase and CPE extraction efficiencies. Extraction recovery (except paracetamol) was above 80% and reproducibility (RSD%) ranged from 2.88 to 10.26 intraday and from 3.12 to 12.33 interday. The limits of detection were: 0.125 µg mL−1 (promazine and chlorpromazine), 0.25 µg mL−1 (amitriptyli

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Gordon, M., B. Borgmann, J. Gehrung, M. Hebel, and M. Arens. "AD HOC MODEL GENERATION USING MULTISCALE LIDAR DATA FROM A GEOSPATIAL DATABASE." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XL-3/W3 (August 20, 2015): 535–41. http://dx.doi.org/10.5194/isprsarchives-xl-3-w3-535-2015.

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Due to the spread of economically priced laser scanning technology nowadays, especially in the field of topographic surveying and mapping, ever-growing amounts of data need to be handled. Depending on the requirements of the specific application, airborne, mobile or terrestrial laser scanners are commonly used. Since visualizing this flood of data is not feasible with classical approaches like raw point cloud rendering, real time decision making requires sophisticated solutions. In addition, the efficient storage and recovery of 3D measurements is a challenging task. Therefore we propose an ap

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Imran, Alaa Mousa, Saadiyah Ahmed Dhahir, and Ahmed Jassim Muklive. "Cloud Point Extraction Method for Spectrophotometric Determination of 3-Aminophenol in Environmental Samples." Indonesian Journal of Chemistry 24, no. 4 (2024): 1023. http://dx.doi.org/10.22146/ijc.89922.

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This work describes the development of new spectrophotometric techniques for 3-aminophenol assessment. The first technique involves using benzidine in an alkaline solution to convert 3-aminophenol into a colored complex. The produced complex has a red color with an absorbance of 462 nm. Between the concentration range 5–14 μg mL−1, Beer's law is obeyed with a correlation coefficient (R2) of 0.99781, a limit of detection (LOD) of 0.0423 μg mL−1, and a limit of quantification (LOQ) of 0.1411 μg mL−1. The recovery was between 87.2–95.43%, the relative standard deviation (%RSD) was 2.40–3.31% and

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Manukonda, Anil Kumar. "Implementing Multi-Region Disaster Recovery Solutions in AWS Cloud Environment." INTERNATIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENT 06, no. 09 (2022): 1–8. https://doi.org/10.55041/ijsrem16417.

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Cloud computing depends on multi-region disaster recovery (DR) as a vital practice to maintain business operations during substantial outages. Organizations using Amazon Web Services (AWS) worldwide infrastructure implement disaster recovery through duplicated critical systems that span different geographical areas to minimize data loss and downtime. AWS users can establish multi-region DR strategies which this paper examines through specific implementations targeting e-commerce operations and healthcare as well as financial institutions. This paper explicates multi-region DR strategies includ

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Hazrina, H. Z., M. S. Noorashikin, S. Y. Beh, S. H. Loh, and N. N. M. Zain. "Formulation of chelating agent with surfactant in cloud point extraction of methylphenol in water." Royal Society Open Science 5, no. 7 (2018): 180070. http://dx.doi.org/10.1098/rsos.180070.

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Cloud point extraction (CPE) is a separation and preconcentration of non-ionic surfactant from one liquid phase to another. In this study, Sylgard 309 and three different types of additives for CPE, namely CPE-Sylgard, CPE-Sylgard-BMIMBr and CPE-Sylgard-GLDA, are investigated to extract methylphenol from water samples. The methylphenols are well separated by reversed-phase high-performance liquid chromatography (HPLC) with isocratic elution of acetonitrile : water; 60 : 40 (v/v) and detection at 260 nm. The optimized parameters for the effect of salt, surfactant, temperature, time of extractio

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