Journal articles: 'Point cloud recovery'

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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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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 (November 16, 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 geometries. In this paper, a methodology is presented for the automated recovery of cross-sectional shapes using centrally located curves. We assume a triangulated surface mesh is generated from the scanned point cloud. This surface mesh is the starting point for our methodology. We then find the curve skeleton of the part which abstractly describes the global geometry and topology. Next after segmenting the curve skeleton into non-branching segments, orthogonal planes to the curve skeleton segments, at preset or adaptive intervals, make slices through the surface mesh edges. The intersection points are extracted creating a 2D point cloud of the cross section. A number of application specific post-processing operations can be performed after obtaining the 2D point cloud cross sections and the curve skeleton paths including: calculations such as area or area moments of inertia, feature fitting or recognition, and digital shape reconstruction. Case studies are presented to demonstrate capabilities and limitations, and to provide insight into appropriate uses and adaptations for the presented methodology. Highlights Automated cross-sectional extraction for branching structures is presented. Methodology utilized skeletonization of object as reference for sampling planes. Surface mesh is sliced to extract a 2D point cloud. Filter algorithm for exclusion of peripheral slicing is presented. Several case studies demonstrate capabilities and limitations of the method.

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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 (January 9, 2003): 3591–607. http://dx.doi.org/10.1081/ss-120023420.

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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 (September 12, 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 understory vegetation. This paper describes the design and use of a field frame to co-register point intercept measurements with point cloud data to act as a validation source. Validation results show high correlation of point matching in forests with understory vegetation elements with large mass and/or surface area, typically consisting of broad leaves, twigs and bark 0.02 m diameter or greater in size (SfM, MCC 0.51–0.66; TLS, MCC 0.37–0.47). In contrast, complex environments with understory vegetation elements with low mass and low surface area showed lower correlations between validation measurements and point clouds (SfM, MCC 0.40 and 0.42; TLS, MCC 0.25 and 0.16). The results of this study demonstrate that the validation frame provides a suitable method for comparing the relative performance of different point cloud generation processes.

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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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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 (November 1, 2020): 3255–70. http://dx.doi.org/10.1109/tvcg.2019.2920817.

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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 boundaries and it preserves topology of the object.

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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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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 (August 27, 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 (February 2018): 1569–75. http://dx.doi.org/10.1016/j.jece.2018.05.007.

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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 (July 4, 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 by the untrusted or unauthorized user remotely. The attacker may modify, delete or replace the data. Therefore, different models are proposed for a data integrity check and proof of retrievability. This paper includes the literature review related to various techniques for data integrity, data recovery and proof of retrievability.

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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, classification and feature relevance assessment. To analyze the impact of the main influencing factors which are represented by the given point sampling and the selected neighborhood type, we present the results derived with different configurations of our framework for a commonly used benchmark dataset for which a reference labeling with respect to three structural classes (linear structures, planar structures and volumetric structures) as well as a reference labeling with respect to five semantic classes (Wire, Pole/Trunk, Façade, Ground and Vegetation) is available.

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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 system provides fast and accurate service.

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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 (January 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 (amitriptyline and nortriptyline) and 0.5 µg mL−1 (paracetamol and clomipramine). The method was linear over the ranges: 0.125–1.0 µg mL−1 (promazine and chlorpromazine), 0.25–1.0 µg mL−1 (amitriptyline and nortriptyline), 0.5–1.0 µg mL−1 (clomipramine) and 0.5–10 µg mL−1 (paracetamol). The procedure is a good alternative to the SPE or LLE sample preparation usually used.

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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 (July 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 extraction, pH, interference study and the performance of different additives on methylphenol extraction are investigated. CPE-Sylgard-GLDA is chosen because it gives us a high peak and good peak area compared with CPE-Sylgard and CPE-Sylgard-BMIMBr. The recovery extractions of CPE-Sylgard-GLDA are obtained in the range of 80–99% as the percentage of relative standard deviation (RSD) is less than 10. The LOD and LOQ are 0.05 ppm and 0.18 ppm, respectively. The method developed for CPE-Sylgard-GLDA coupled with HPLC is feasible for the determination of methylphenol because it is simple, effective, cheap, and produces a high percentage of recovery.

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Curbelo, F., A. Garnica, and E. Neto. "Salinity Effect in Cloud Point Phenomena by Nonionic Surfactants Used in Enhanced Oil Recovery Tests." Petroleum Science and Technology 31, no. 15 (August 3, 2013): 1544–52. http://dx.doi.org/10.1080/10916466.2010.547906.

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Wang, Zhilong. "Predicting organic compound recovery efficiency of cloud point extraction with its quantitative structure–solubilization relationship." Colloids and Surfaces A: Physicochemical and Engineering Aspects 349, no. 1-3 (October 2009): 214–17. http://dx.doi.org/10.1016/j.colsurfa.2009.08.010.

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Phasukarratchai, Naphatsarnan, Seelawut Damrongsiri, and Chantra Tongcumpou. "Recovery of phorbol esters from pressed jatropha seeds by surfactant extraction and cloud-point separation." Industrial Crops and Products 95 (January 2017): 549–57. http://dx.doi.org/10.1016/j.indcrop.2016.11.009.

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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 extraction efficiency, different experimental parameters like surfactant concentration, salt type and its concentration, equilibrium time and temperature, pH were observed. At the optimum conditions, linear regression coefficient of the standard curves was greater than 0.9924. The limit of detection of imidacloprid, flusilazole and atrazine were 0.10 μg L-1, 0.24 μg L-1, 0.15 μg L-1 and recovery percent are 99.71 %, 88.1% and 89.74%, respectively.

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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 (October 1, 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 cloud probe measuring a thin horizontal “skewer” through a cloud). The measured RDF and PCF of these one-dimensional transects are related to (but not, in general, equal to) the RDF/PCF of the intrinsic three-dimensional systems from which the sample was taken. Previous work examined the formal mathematical relationship between the statistics of the intrinsic three-dimensional system and the one-dimensional transect; this study extends the previous work within the context of realistic sampling variability. Natural sampling variability is found to constrain substantially the usefulness of applying previous theoretical relationships. Implications for future sampling strategies are discussed.

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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 approach for the intelligent storage of 3D point clouds using a spatial database. For a given region of interest, the database is queried for the data available. All resulting point clouds are fused in a model generation process, utilizing the fact that low density airborne measurements could be used to supplement higher density mobile or terrestrial laser scans. The octree based modeling approach divides and subdivides the world into cells of varying size and fits one plane per cell, once a specified amount of points is present. The resulting model exceeds the completeness and precision of every single data source and enables for real time visualization. This is especially supported by data compression ratios of about 90%.

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Kojro, Grzegorz, and Piotr Wroczyński. "Cloud Point Extraction in the Determination of Drugs in Biological Matrices." Journal of Chromatographic Science 58, no. 2 (November 4, 2019): 151–62. http://dx.doi.org/10.1093/chromsci/bmz064.

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Abstract Cloud point extraction (CPE) is a simple, safe and environment-friendly technique used in the preparation of various samples. It was primarily developed for the assessment of environmental samples, especially analyzed for metals. Recently, this technique has been used in the extraction and determination of various chemical compounds (e.g., drugs, pesticides and vitamins), in various matrices (e.g., human plasma, human serum, milk and urine). In this review, we show that CPE is a reliable method of extraction and can be used in analytical laboratories in combination with other techniques that can be used in the determination of drugs and other chemicals in the human biological matrix. According to the literature, a combination of different methods provides good recovery and can be used in the simultaneous determination of many drugs in a single analysis. CPE can be optimized by changing its conditions (e.g., type of surfactant used, incubation temperature, pH and the addition of salts). In this review, we present the optimized CPE methods used in the determination of various pharmaceuticals and describe how the conditions affect the performance of extraction. This data might support future designing of the new CPE applications that are simple and more accurate. We compared CPE with other extraction methods and also showed the advantages and disadvantages of various extraction techniques along with a discussion on their environmental impact. According to the publications reviewed, it is obvious that CPE is an easy, safe, rapid and inexpensive method of extraction.

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de Araújo Padilha, Carlos Eduardo, Juliana Chris Silva de Azevedo, Francisco Canindé de Sousa, Sérgio Dantas de Oliveira, Domingos Fabiano de Santana Souza, Jackson Araújo de Oliveira, Gorete Ribeiro de Macedo, and Everaldo Silvino dos Santos. "Recovery of polyphenols from camu-camu (Myrciaria dubia H.B.K. McVaugh) depulping residue by cloud point extraction." Chinese Journal of Chemical Engineering 26, no. 12 (December 2018): 2471–76. http://dx.doi.org/10.1016/j.cjche.2017.10.032.

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Bullinger, S., C. Bodensteiner, and M. Arens. "3D SURFACE RECONSTRUCTION FROM MULTI-DATE SATELLITE IMAGES." International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLIII-B2-2021 (June 28, 2021): 313–20. http://dx.doi.org/10.5194/isprs-archives-xliii-b2-2021-313-2021.

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Abstract. The reconstruction of accurate three-dimensional environment models is one of the most fundamental goals in the field of photogrammetry. Since satellite images provide suitable properties for obtaining large-scale environment reconstructions, there exist a variety of Stereo Matching based methods to reconstruct point clouds for satellite image pairs. Recently, a Structure from Motion (SfM) based approach has been proposed, which allows to reconstruct point clouds from multiple satellite images. In this work, we propose an extension of this SfM based pipeline that allows us to reconstruct not only point clouds but watertight meshes including texture information. We provide a detailed description of several steps that are mandatory to exploit state-of-the-art mesh reconstruction algorithms in the context of satellite imagery. This includes a decomposition of finite projective camera calibration matrices, a skew correction of corresponding depth maps and input images as well as the recovery of real-world depth maps from reparameterized depth values. The paper presents an extensive quantitative evaluation on multi-date satellite images demonstrating that the proposed pipeline combined with current meshing algorithms outperforms state-of-the-art point cloud reconstruction algorithms in terms of completeness and median error. We make the source code of our pipeline publicly available.

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Saleh, Noorashikin Md, N. M. Hafiz, and Nik Nur Atiqah NikWee. "Determination of Parabens from Water Samples Using Cloud Point Extraction, Vortex Extraction and Liquid–Liquid Extraction Method Coupled with High Performance Liquid Chromatography." Journal of Computational and Theoretical Nanoscience 17, no. 2 (February 1, 2020): 765–72. http://dx.doi.org/10.1166/jctn.2020.8717.

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A straightforward and efficient way for extraction of parabens that is methylparaben, ethylparaben, propylparaben and benzylparaben in environmental water samples was developed through optimizing parameters for each method of extraction. In this study, methods involved were cloud point extraction, vortex extraction, and liquid–liquid extraction. The parameters affecting the method of extraction were such as salt concentration, surfactant concentration, type of solvent, temperature, ratio of solvent to water and extraction time. The optimum parameter for cloud point extraction method were 1.0 M of salt, 1.0% v/v of surfactant, ratio of surfactant to water is 1:1, extraction time is 1 minute at 30 °C while vortex extraction method, optimum parameter is 1.0 M salt, using acetonitrile as a solvent, ratio 1 solvent: 4 water, and extracted at 1 minute. For the liquid–liquid extraction method, the optimum parameter was at 1.0 M salt, acetonitrile as a solvent, ratio of solvent to water is 1:1 and extraction time at 1 minute. The correlation coefficient for the calibration of paraben at concentration 0.2 ppm–1.0 ppm was in the range from 0.9703 to 0.9942. The limit of detection of studied paraben were 0.1627, 0.0837, 0.1156 and 0.1918 ppm, respectively. Percentage recovery for cloud point extraction, vortex extraction and liquid–liquid extraction were between 41%–147.9%, 26.5%–134.7%, and 31.4%–142.4% respectively. Each sample is repeated with triplication which the value of the relative standard deviation is less than 17.9%. Thus, the most suitable, efficient and effective method in extraction of paraben from water samples is cloud point extraction. The cloud point extraction shows the potential to be explore on the future extraction of others organic pollutants from water samples.

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Collén, Anna, Klaus Selber, Teppo Hyytiä, Josefine Persson, Tiina Nakari-Setlä, Michael Bailey, Richard Fagerström, et al. "Primary recovery of a genetically engineeredTrichoderma reeseiendoglucanase I (Cel 7B) fusion protein in cloud point extraction systems." Biotechnology and Bioengineering 78, no. 4 (March 29, 2002): 385–94. http://dx.doi.org/10.1002/bit.10232.

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Zhang, Hong, Xiaoyu Yang, Zhaohui Liu, and Yanzhao Yang. "Recovery of Ru(III) from hydrochloric acid by cloud point extraction with 2-Mercaptobenzothiazole-functionalized ionic liquid." Chemical Engineering Journal 308 (January 2017): 370–76. http://dx.doi.org/10.1016/j.cej.2016.09.027.

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Abedi, Shahnaz, and Farzin Nekouei. "Removal of Direct Yellow 12 from Water Samples by Cloud Point Extraction Using Triton X-100 as Nonionic Surfactant." E-Journal of Chemistry 8, no. 4 (2011): 1588–95. http://dx.doi.org/10.1155/2011/207640.

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A surfactant mediated cloud point extraction (CPE) procedure has been developed to remove color from wastewater containing direct yellow 12 (Chrysophenine G), using triton x-100 (TX-100) as nonionic surfactant. The effects of the concentration of the surfactant, pH, temperature and salt concentration on the different concentration of dye have been studied and optimum conditions were obtained for the removal of direct yellow 12 (DY 12). The concentration of DY 12 in the dilute phase was measured using UV-Vis spectrophotometer. It was found that the separation of phases was complete and the recovery of DY 12 was very effective in the presence of NaCl as an electrolyte. The results showed that up to 600 mg L−1of DY 12 can quantitatively be removed (>96%) by Cloud point extraction procedure in a single extraction using optimum conditions.

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Mousavi, Raziyeh, and Farzin Nekouei. "Cloud Point Extraction of Toxic Reactive Black 5 Dye from Water Samples Using Triton X-100 as Nonionic Surfactant." E-Journal of Chemistry 8, no. 4 (2011): 1606–13. http://dx.doi.org/10.1155/2011/287352.

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A surfactant mediated cloud point extraction (CPE) procedure has been developed to remove color from wastewater containing reactive black 5, using triton x-100 (TX-100) as non-ionic surfactant. The effects of the concentration of the surfactant, pH, temperature and salt concentration on the different concentrations of dye have been studied and optimum conditions were obtained for the removal of reactive black 5 (RB 5). The concentration of RB 5 in the dilute phase was measured using UV-Vis spectrophotometer. It was found that the separation of phases was complete and the recovery of RB 5 was very effective in the presence of NaCl as an electrolyte. The results showed that up to 600 mg L-1of RB 5 can quantitatively be removed (>97%) by cloud point extraction procedure in a single extraction using optimum conditions.

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Karadaş, Cennet, and Derya Kara. "A new ligandless cloud point extraction method for preconcentration of iron from natural water samples and FAAS detection." Water Supply 17, no. 5 (March 18, 2017): 1347–55. http://dx.doi.org/10.2166/ws.2017.035.

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A simple, efficient and inexpensive ligandless cloud point extraction method was developed for the preconcentration of trace amounts of iron from natural water samples, followed by flame atomic absorption spectrometry detection. The proposed method is based on the extraction of Fe(III) ions at pH 7.0 using the non-ionic surfactant Triton X-114 without the addition of any chelating ligand. The effect of parameters influencing the extraction efficiency such as sample pH, concentration of surfactant, incubation temperature and time, concentration of NaCl and sample volume were investigated and optimized. The effect of potentially interfering ions on the recovery of iron was also examined. Under optimum conditions, the detection limit (3σ) was 0.95 μg L−1 for Fe using a sample volume of 10 mL. A preconcentration factor of 20 was achieved. The accuracy of the method was checked through the analysis of certified reference materials (SLRS-5 river water, SPS-SW2 Batch 127 surface water) and spiked water samples. The percentage recovery values for spiked water samples were between 92% and 101%.

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Hadi, Hind, and Hawraa M. Abdulkareem. "Determination and Extraction of Carbofuran Pesticide in Different Matrices using Cloud Point Extraction Method." Current Analytical Chemistry 16, no. 3 (May 15, 2020): 256–62. http://dx.doi.org/10.2174/1573411015666191028114446.

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Background: Pesticides are increasingly used in agriculture and households, but they are also considered a major pollutant to the environment. Carbofuran (CAR; 2,3-dihydro-2,2- dimethylbenzofuran-7-yl methylcarbamate) is a widely used pesticide due to its effectiveness on soybean aphids. Objectives: A simple and green method was suggested for the extraction and determination of CAR in different matrices. Methods: A diazotization reaction involving the use of the drug compound metoclopramide was utilized in this study. A red dye product, which was formed from the diazotization coupling between CAR and diazotized metoclopramide (DMCP), was extracted using cloud point extraction with the nonionic surfactant Triton X-114 and measured at a wavelength of 515 nm. Results: The linearity of the extracted method was over a concentration range of 0.1-0.5 µg/mL (r2 = 0.996) for CAR with a detection limit of 0.064 µg/mL and enrichment factors of about 148 folds for CAR. The mean recovery percentage was in the range of 99-102% for water and soil samples with precision (RSD%) of less than 0.4%. Conclusion: The described method was effectively utilized in the simultaneous extraction of CAR from water and soil samples.

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Mohammadzadeh, Mozhgan, Masoud Honarvar, Ali Reza Zarei, Masoud Mashhadi Akbar Boojar, and Hossein Bakhoda. "A new approach for separation and recovery of betaine from beet molasses based on cloud point extraction technique." Journal of Food Science and Technology 55, no. 4 (March 5, 2018): 1215–23. http://dx.doi.org/10.1007/s13197-017-2999-4.

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Suoranta, Terhi, Oihane Zugazua, Matti Niemelä, and Paavo Perämäki. "Recovery of palladium, platinum, rhodium and ruthenium from catalyst materials using microwave-assisted leaching and cloud point extraction." Hydrometallurgy 154 (April 2015): 56–62. http://dx.doi.org/10.1016/j.hydromet.2015.03.014.

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Liu, Kaifeng, Kouki Nagamune, Keisuke Oe, Ryosuke Kuroda, and Takahiro Niikura. "Migration Measurement of Pins in Postoperative Recovery of the Proximal Femur Fractures Based on 3D Point Cloud Matching." Medicina 57, no. 5 (April 22, 2021): 406. http://dx.doi.org/10.3390/medicina57050406.

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Background and objectives: Internal fixation is one of the most effective methods for the treatment of proximal femur fractures. The migration of implants after the operation can seriously affect the reduction of treatment and even cause complications. Traditional diagnosis methods can not directly measure the extent of displacement. Methods: Based on the analysis of Hansson pins, this paper proposes a measurement method based on three-dimensional matching, which uses computerized tomography (CT) images of different periods of patients after the operation to analyze the implants’ migration in three-dimensional space with the characteristics of fast speed and intuitive results. Results and conclusions: The measurement results show that the method proposed in this paper has more minor errors, more flexible coordinate system conversion, and more explicit displacement analysis than the traditional method of manually finding references in CT images and measuring displacement.

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Alibrahim, Moussa. "Cloud Point Extraction of Direct Blue 71 Dye using Triton X-100 as Nonionic Surfactant." Tenside Surfactants Detergents 58, no. 1 (January 1, 2021): 27–32. http://dx.doi.org/10.1515/tsd-2018-2091.

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Abstract A surfactant-mediated cloud point extraction (CPE) method using the non-ionic surfactant Triton X-100 (TX-100) has been developed to remove the dye Direct Blue 71 (DB71) from a waste water. Most of the dye molecules are solubilized in the coacervate phase so that the dilute phase remains free of the dye. The effects of surfactant concentration, temperature and salt concentration on the different dye concentrations were studied to determine the optimal conditions for removing DB71. The concentration of DB71 in the dilute phase was measured using UV-Vis spectrophotometer. It was found that the separation of phases was complete and the recovery of DB71 was very effective in the presence of NaCl as an electrolyte. The results showed that up to 25 ppm DB71, i.e. more than 95%, can be quantitatively removed by cloud point extraction procedures in a single extraction at optimal conditions. It was also observed that at a dye concentration of 1 ppm, 100% of the blue dye DB71 can be directly removed with a TX-100 concentration of 12% by weight. At higher dye concentrations of up to 30 ppm, 94.7%-100% dye can be removed. The TX-100 concentration was 12 wt%, the salt concentration (NaCl) 0.005 M and the temperature 75°C. It is concluded that the surfactant mediated cloud point extraction method for dye removal can be an alternative to current dye removal methods.

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Novo, A., H. González-Jorge, J. Martínez-Sánchez, and H. Lorenzo. "REMOTE SENSING APPROACH TO EVALUATE POST-FIRE VEGETATION STRUCTURE." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLIII-B3-2020 (August 21, 2020): 1031–38. http://dx.doi.org/10.5194/isprs-archives-xliii-b3-2020-1031-2020.

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Abstract. Spain is included in the top five European countries with the highest number of wildfires. Forest fire can produce significant impacts on the structure and functioning of natural ecosystems. After a forest fire, the evaluation of the damage severity and spatial patterns are important for forest recovery planning, which plays a critical role in the sustainability of the forest ecosystem. The process of forest recovery and the ecological and physiological functions of the burned forest area should be continuously monitored. Remote sensing technologies and in special LiDAR are useful to describe the structure of vegetation. The vegetation modelling and the initial changes of forest plant composition are studied in the forest after mapping the burned areas using Landsat-7 images and Sentinel-2 images. Normalized Burn Ratio (NBR) index and Normalized Difference Vegetation Index (NVVI) is calculated as well as the difference before and after fire. The evaluation of temporal changes of vegetation are analysed by statistical variables of the point cloud, average height, standard deviation and variance. Fraction Canopy Cover (FCC) also is calculated and the point cloud is classified following the fuel model by Prometheus. An analysis method based on satellite images was completed in order to analyse the evolution of vegetation in areas that suffer forest fire.

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Griesbaum, Luisa, Sabrina Marx, and Bernhard Höfle. "Direct local building inundation depth determination in 3-D point clouds generated from user-generated flood images." Natural Hazards and Earth System Sciences 17, no. 7 (July 14, 2017): 1191–201. http://dx.doi.org/10.5194/nhess-17-1191-2017.

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Abstract. In recent years, the number of people affected by flooding caused by extreme weather events has increased considerably. In order to provide support in disaster recovery or to develop mitigation plans, accurate flood information is necessary. Particularly pluvial urban floods, characterized by high temporal and spatial variations, are not well documented. This study proposes a new, low-cost approach to determining local flood elevation and inundation depth of buildings based on user-generated flood images. It first applies close-range digital photogrammetry to generate a geo-referenced 3-D point cloud. Second, based on estimated camera orientation parameters, the flood level captured in a single flood image is mapped to the previously derived point cloud. The local flood elevation and the building inundation depth can then be derived automatically from the point cloud. The proposed method is carried out once for each of 66 different flood images showing the same building façade. An overall accuracy of 0.05 m with an uncertainty of ±0.13 m for the derived flood elevation within the area of interest as well as an accuracy of 0.13 m ± 0.10 m for the determined building inundation depth is achieved. Our results demonstrate that the proposed method can provide reliable flood information on a local scale using user-generated flood images as input. The approach can thus allow inundation depth maps to be derived even in complex urban environments with relatively high accuracies.

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Karim, U., H. C. Inyiama, and R. Karim. "User-Centric Cyber Disaster Recovery as a Service." NIGERIAN ANNALS OF PURE AND APPLIED SCIENCES 1 (December 30, 2019): 238–46. http://dx.doi.org/10.46912/napas.126.

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In a world of interdependent economies and online transactions, a large volume of data hosted on the cyberspace a daily bases. Cyber threats and attacks are steadily increasing. Most time, these threats and attacks are targeted at service providers but service users are greatly affected by the attacks due to their vulnerability level. When disasters knockdown the infrastructures of a single service provider, it will have ripple effects on thousands of innocent service users. Therefore, service users need more than ever to prepare for major crises targeted at their service providers. To cope with this trends, every service user requires an independent business continuity plan (BCP) or disaster recovery plan (DRP) and data backup policy which falls within their cost constraints while achieving the target recovery requirements in terms of recovery time objective (RTO) and recovery point objective (RPO). The aim of this paper is to develop a model for a user-centric disaster recovery system to enable service users to independently develop their data backup policies that best suits their remote databases, and host same as a cloud service deployable on public cloud for users to subscribe to and be billed on pay-as-you-go billing model. The system developed is highly compatible with MYSQL, MSSQL and Oracle databases. A combination of Dynamic System Development Methodology (DSDM) and Object- Oriented Analysis and Design Methodology (OOADM) were used to design the system while Java Enterprise Edition (JEE) is used to develop the system. The encryption and compression mechanisms of the system were tested with various sizes of backup files ranging from 64 Kb to 20Mb and several performance metrics such as (1) Encryption time; (2) Compression size; (3) CPU clock cycles and battery power are compared and analysed with some well-known encryption and compression algorithms.

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Akita, Shigendo, Miquel Rovira, Ana M. Sastre, and Hiroshi Takeuchi. "Cloud-Point Extraction of Gold(lll) with Nonionic Surfactant—Fundamental Studies and Application to Gold Recovery from Printed Substrate." Separation Science and Technology 33, no. 14 (January 1998): 2159–77. http://dx.doi.org/10.1080/01496399808545721.

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Chen, Xin, Hong Zhao, and Ping Zhou. "Lung Lobe Segmentation Based on Lung Fissure Surface Classification Using a Point Cloud Region Growing Approach." Algorithms 13, no. 10 (October 15, 2020): 263. http://dx.doi.org/10.3390/a13100263.

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In anatomy, the lung can be divided by lung fissures into several pulmonary lobe units with specific functions. Identifying the lung lobes and the distribution of various diseases among different lung lobes from CT images is important for disease diagnosis and tracking after recovery. In order to solve the problems of low tubular structure segmentation accuracy and long algorithm time in segmenting lung lobes based on lung anatomical structure information, we propose a segmentation algorithm based on lung fissure surface classification using a point cloud region growing approach. We cluster the pulmonary fissures, transformed into point cloud data, according to the differences in the pulmonary fissure surface normal vector and curvature estimated by principal component analysis. Then, a multistage spline surface fitting method is used to fill and expand the lung fissure surface to realize the lung lobe segmentation. The proposed approach was qualitatively and quantitatively evaluated on a public dataset from Lobe and Lung Analysis 2011 (LOLA11), and obtained an overall score of 0.84. Although our approach achieved a slightly lower overall score compared to the deep learning based methods (LobeNet_V2 and V-net), the inter-lobe boundaries from our approach were more accurate for the CT images with visible lung fissures.

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Lee, Seung-Joong, and Sung-Oong Choi. "Analyzing the Stability of Underground Mines Using 3D Point Cloud Data and Discontinuum Numerical Analysis." Sustainability 11, no. 4 (February 13, 2019): 945. http://dx.doi.org/10.3390/su11040945.

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This study describes a precise numerical analysis process by adopting the real image of mine openings obtained by light detection and ranging (LiDAR), which can produce a point cloud data by measuring the target surface numerically. The analysis target was a section of an underground limestone mine, to which a hybrid room-and-pillar mining method that was developed to improve ore recovery was applied. It is important that the center axis and the volume of the vertical safety pillar in the lower parts match those in the upper parts. The 3D survey of the target section verified that the center axis of the vertical safety pillar in the lower parts had deviated in a north-westerly direction. In particular, the area of the lower part of the vertical safety pillar was approximately 34 m2 lower than the designed cross-sectional area, which was 100 m2. In order to analyze the stability of the vertical safety pillar, a discontinuum numerical analysis and safety factor analysis were conducted using 3D surveying results. The analysis verified that instability was caused by the joints distributed around the vertical safety pillar. In conclusion, investigation of the 3D survey and 3D numerical analysis techniques performed in this study are expected to provide higher reliability than the current techniques used for establishing whether mining plans require new mining methods or safety measures.

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Soylak, Mustafa, Erkan Yilmaz, Mehrorang Ghaedi, Mortaza Montazerozohori, and Marjan Sheibani. "Cloud Point Extraction and Flame Atomic Absorption Spectrometry Determination of Lead (II) in Environmental and Food Samples." Journal of AOAC INTERNATIONAL 95, no. 6 (November 1, 2012): 1797–802. http://dx.doi.org/10.5740/jaoacint.10-370.

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Abstract A cloud point extraction procedure for the preconcentration of Pb2+ in various samples following complexation with 2,2-(1E,1′E)-1,1′-(2,2′-azanediylbis(ethane-2,1-diyl)bis(azan-1-yl-1-ylidene)) bis(ethan-1-yl-1-ylidene)diphenol in Triton X-114 after centrifugation is reported. A 0.5 mL portion of methanol acidified with 1.0 M HNO3 was added to the surfactant-rich phase prior to analysis by flame atomic absorption spectrometry. The influence of analytical parameters—including pH, concentrations of ligand, Triton X-114, and HNO3, bath temperature, heating time, and centrifugation rate and time—were optimized, and the effect of the matrix ions on the recovery of Pb2+ was investigated. An LOD of 1.9 ng/mL along with a preconcentration factor of 50 with RSD of 1.0% for Pb2+ were achieved. The proposed procedure was applied to the analysis of various real samples.

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Ning, Jinyan, Yang Jiao, Jiao Zhao, Lifen Meng, and Yaling Yang. "Cloud point extraction–flame atomic absorption spectrometry method for preconcentration and determination of trace cadmium in water samples." Water Science and Technology 70, no. 4 (June 13, 2014): 605–11. http://dx.doi.org/10.2166/wst.2014.263.

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A method based on cloud point extraction (CPE) separation/preconcentration of trace cadmium (Cd) as a prior step to its determination by flame atomic absorption spectrometry has been developed. Cadmium reacted with 8-hydroxyquinoline to form hydrophobic chelates, which were extracted into the micelles of nonionic surfactant oligoethylene glycol monoalkyl ether (Genapol X-080) in an alkaline medium. Octanol was used to depress the cloud point of Genapol X-080 in the extraction process. The chemical variables that affect the CPE, such as pH of complexation reaction, amount of chelating agent, Genapol X-080 and octanol were evaluated and optimized. Under optimized conditions, linearity was obeyed in the range of 10–500 μg/L, with the correlation coefficient of 0.9993. For 5 mL of sample solution, the enhancement factor was about 20. The limit of detection and limit of quantification of the method were 0.21 and 0.63 μg/L, respectively. The relative standard deviations (n = 6) was 3.2% for a solution containing 100 μg/L of Cd. The accuracy of the preconcentration system was evaluated by recovery measurements on spiked water samples. Recoveries of spiked samples varied in the range of 94.1–103.8%.

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Gniazdowska, Elżbieta, Natalia Korytowska, Grzegorz Kłudka, and Joanna Giebułtowicz. "Determination of Antidepressants in Human Plasma by Modified Cloud-Point Extraction Coupled with Mass Spectrometry." Pharmaceuticals 13, no. 12 (December 12, 2020): 458. http://dx.doi.org/10.3390/ph13120458.

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Cloud-point extraction (CPE) is rarely combined with liquid chromatography coupled to mass spectrometry (LC–MS) in drug determination due to the matrix effect (ME). However, we have recently shown that ME is not a limiting factor in CPE. Low extraction efficiency may be improved by salt addition, but none of the salts used in CPE are suitable for LC–MS. It is the first time that the influences of a volatile salt—ammonium acetate (AA)—on the CPE extraction efficiency and ME have been studied. Our modification of CPE included also the use of ethanol instead of acetonitrile to reduce the sample viscosity and make the method more environmentally friendly. We developed and validated CPE–LC–MS for the simultaneous determination of 21 antidepressants in plasma that can be useful for clinical and forensic toxicology. The selected parameters included Triton X-114 concentration (1.5 and 6%, w/v), concentration of AA (0, 10, 20 and 30%, w/v), and pH (3.5, 6.8 and 10.2). The addition of 10% of AA increased recovery twice. For 20 and 30% (w/v) of AA, three phases were formed that prolonged the extraction process. The developed CPE method (6% Triton X-114, 10% AA, pH 10.2) was successfully validated through LC–MS/MS simultaneous determination of 21 antidepressants in human plasma. The linearity was in the range of 10–750 ng/mL (r2 > 0.990).

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H.L., Meghana, Asish Oommen Mathew, and Lewlyn L. R. Rodrigues. "Prioritizing the factors affecting cloud ERP adoption – an analytic hierarchy process approach." International Journal of Emerging Markets 13, no. 6 (November 29, 2018): 1559–77. http://dx.doi.org/10.1108/ijoem-10-2017-0404.

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Purpose In today’s competitive world, the adoption of cloud enterprise resource planning (ERP) has become one of the critical criteria for running a successful business. In this regard, knowing the factors that influence cloud ERP adoption plays a significant role. The purpose of this paper is to rank the factors influencing the cloud ERP adoption in multi-national companies (MNCs) in India. This research would enable the cloud ERP vendors to identify the expectations of MNC customers and develop suitable strategies. Design/methodology/approach The research is being conducted among the cloud ERP consultants of designation middle managers and above from 29 different ERP consulting firms located in India. Analytical hierarchical processing approach was used to rank the factors influencing the cloud ERP adoption in MNCs located in India. The primary factors considered for this study are usability, assurance, agility, security and privacy, and vendor-related factors. Findings The three most preferred criteria were usability, assurance and agility. The five most preferred sub-criteria were data accessibility, availability, user friendliness, scalability, and data backup and recovery. Research limitations/implications The study is limited to the perspective of cloud ERP consultants in India. Practical implications The outcome of this research provides cloud ERP vendors with a better understanding of factors that influence the adoption of cloud ERP in MNCs so that they can develop a focused strategy. From the MNCs point of view, the study provides a guideline on what factors they should consider while going for a cloud ERP implementation. Originality/value The research model is developed based on the cloud ERP literature, and the research results and findings would add value to the body of knowledge.

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Gnanesh, K. E., T. Dheeraj Bhavan Narayana, and M. D. Kamalesh. "Retrieval of Encrypted Data Using Trapdoor Method in Cloud Computing." Journal of Computational and Theoretical Nanoscience 16, no. 8 (August 1, 2019): 3237–41. http://dx.doi.org/10.1166/jctn.2019.8169.

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Cloud computing is a well-known innovation which licenses putting away and getting to information over Internet as opposed to putting away it on nearby machines’ hard drive. Cloud clients can empower to store their information on cloud with no nervousness about its exactness and dependability. Anyway putting away information on cloud forces certain security challenges. Redistributing information in cloud result may lose physical authority over their information. Putting away and recovering such a lot of information devours part of time as information in the cloud should be constantly put away in encoded arrangement while putting away and should be decoded while looking. There are various recommendations for executing questions over encoded information. This actualizes the customer to scramble information before re-appropriating it to the cloud in a database conspire. To stay away from this monstrous utilization of time, information looking rate can be expanded by straightforwardly seeking over scrambled information in the cloud. There are numerous techniques utilized for looking through the encoded information over cloud. In catchphrase based hunt plans overlook the semantic portrayal data of clients recovery, and can’t totally meet with clients seek goal. In this paper, propose ECSED, a novel semantic inquiry plot dependent on the idea chain of importance and the semantic connection between ideas in the scrambled datasets. ECSED utilizes two cloud servers. One cloud server is utilized to store the reCloud datasets and restore the positioned outcomes to information clients. The other cloud server is utilized to figure the comparability scores between the archives and the question and send the scores to the principal server. To additionally enhance the hunt proficiency, framework uses a tree-based file structure to sort out all the archive list vectors. At that point utilize the multi watchword positioned hunt over scrambled cloud information as our essential casing to propose two secure plans.

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Shyam Sunder, Govind Sharma, Sandhya Adhikari, Ahmad Rohanifar, Abiral Poudel, and Jon R. Kirchhoff. "Evolution of Environmentally Friendly Strategies for Metal Extraction." Separations 7, no. 1 (January 6, 2020): 4. http://dx.doi.org/10.3390/separations7010004.

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The demand for the recovery of valuable metals and the need to understand the impact of heavy metals in the environment on human and aquatic life has led to the development of new methods for the extraction, recovery, and analysis of metal ions. With special emphasis on environmentally friendly approaches, efforts have been made to consider strategies that minimize the use of organic solvents, apply micromethodology, limit waste, reduce costs, are safe, and utilize benign or reusable materials. This review discusses recent developments in liquid- and solid-phase extraction techniques. Liquid-based methods include advances in the application of aqueous two- and three-phase systems, liquid membranes, and cloud point extraction. Recent progress in exploiting new sorbent materials for solid-phase extraction (SPE), solid-phase microextraction (SPME), and bulk extractions will also be discussed.

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Gebrehiwot, A., and L. Hashemi-Beni. "A METHOD TO GENERATE FLOOD MAPS IN 3D USING DEM AND DEEP LEARNING." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLIV-M-2-2020 (November 17, 2020): 25–28. http://dx.doi.org/10.5194/isprs-archives-xliv-m-2-2020-25-2020.

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Abstract. High-resolution remote sensing imagery has been increasingly used for flood applications. Different methods have been proposed for flood extent mapping from creating water index to image classification from high-resolution data. Among these methods, deep learning methods have shown promising results for flood extent extraction; however, these two-dimensional (2D) image classification methods cannot directly provide water level measurements. This paper presents an integrated approach to extract the flood extent in three-dimensional (3D) from UAV data by integrating 2D deep learning-based flood map and 3D cloud point extracted from a Structure from Motion (SFM) method. We fine-tuned a pretrained Visual Geometry Group 16 (VGG-16) based fully convolutional model to create a 2D inundation map. The 2D classified map was overlaid on the SfM-based 3D point cloud to create a 3D flood map. The floodwater depth was estimated by subtracting a pre-flood Digital Elevation Model (DEM) from the SfM-based DEM. The results show that the proposed method is efficient in creating a 3D flood extent map to support emergency response and recovery activates during a flood event.

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Hadj Youcef, M., T. Benabdallah, and H. Reffas. "Cloud point extraction studies on recovery of nickel(II) from highly saline sulfate medium using salicylideneaniline mono-Schiff base chelating extractant." Separation and Purification Technology 149 (July 2015): 146–55. http://dx.doi.org/10.1016/j.seppur.2015.05.034.

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Journal articles on the topic 'Point cloud recovery'

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