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Journal articles on the topic 'Morphology characterization'

Author: Grafiati

Published: 4 June 2021

Last updated: 4 February 2022

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1

Barrientos, Cristián, Jorge Diaz, Julian Brañes, Felipe Chaparro, Maximiliano Barahona, Alfonso Salazar, and Jaime Hinzpeter. "Hip Morphology Characterization." Orthopaedic Journal of Sports Medicine 2, no. 10 (October 2014): 232596711455280. http://dx.doi.org/10.1177/2325967114552800.

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2

Unterlass, Miriam M., Shinji Ando, and Ophelia K. C. Tsui. "Polymer Characterization and Morphology." Macromolecular Chemistry and Physics 219, no. 3 (February 2018): 1800001. http://dx.doi.org/10.1002/macp.201800001.

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3

H. Kh. Al-Lamy, H. Kh Al-Lamy. "Morphology Characterization of InSb Films and Correlation with Optical Properties." Indian Journal of Applied Research 3, no. 5 (October 1, 2011): 549–51. http://dx.doi.org/10.15373/2249555x/may2013/177.

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4

Vesterinen, Heidi M., Ian J. Corfe, Ville Sinkkonen, Antti Iivanainen, Jukka Jernvall, and Juha Laakkonen. "Teat Morphology Characterization With 3D Imaging." Anatomical Record 298, no. 7 (November 20, 2014): 1359–66. http://dx.doi.org/10.1002/ar.23091.

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5

Mukhija, Babita, and Veena Khanna. "Isolation, Characterization and Crystal Morphology Study of Bacillus thuringiensis Isolates from Soils of Punjab." Journal of Pure and Applied Microbiology 12, no. 1 (March 30, 2018): 189–93. http://dx.doi.org/10.22207/jpam.12.1.24.

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6

Sharma, Raghvendra, and B. S. Daya Sagar. "MATHEMATICAL MORPHOLOGY BASED CHARACTERIZATION OF BINARY IMAGE." Image Analysis & Stereology 34, no. 2 (June 29, 2015): 111. http://dx.doi.org/10.5566/ias.1291.

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This paper reports the results of a theoretical study on morphological characterization of foreground (X) and background (Xc) of a discrete binary image. Erosion asymmetry and dilation asymmetry, defined to elaborate smoothing of an image respectively by contraction and expansion, are generalized for multiscale smoothing, and their relationships with morphological skeleton and ridge (background skeleton) transformations are discussed. Then we develop algorithms identifying image topology in terms of critical scales corresponding to close-hulls and open-skulls, along with a few other salient characteristics, as respective smoothing by expansion and contraction proceeds. For empirical demonstration of these algorithms, essentially to unravel the hidden characteristics of topological and geometrical relevance, we considered deterministic and random binary Koch quadric fractals. A shape-size based zonal quantization technique for image and its background is introduced as analytical outcome of these algorithms. The ideas presented and demonstrated on binary fractals could be easily extended to the grayscale images and fractals.

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7

Wachinger, Christian, Polina Golland, William Kremen, Bruce Fischl, and Martin Reuter. "BrainPrint: A discriminative characterization of brain morphology." NeuroImage 109 (April 2015): 232–48. http://dx.doi.org/10.1016/j.neuroimage.2015.01.032.

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8

Walton, D. E., and C. J. Mumford. "Spray Dried Products—Characterization of Particle Morphology." Chemical Engineering Research and Design 77, no. 1 (January 1999): 21–38. http://dx.doi.org/10.1205/026387699525846.

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9

Hadjichristidis, N., Y. Tselikas, H. Iatrou, V. Efstratiadis, and A. Avgeropoylos. "Model nonlinear block copolymers: Synthesis, Characterization, Morphology." Journal of Macromolecular Science, Part A 33, no. 10 (October 1996): 1447–57. http://dx.doi.org/10.1080/10601329608014919.

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10

Hopkins, Alan R., Russell A. Lipeles, and Son-Jong Hwang. "Morphology characterization of polyaniline nano- and microstructures." Synthetic Metals 158, no. 14 (August 2008): 594–601. http://dx.doi.org/10.1016/j.synthmet.2008.04.018.

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11

Cattarin, S., C. Pagura, L. Armelao, R. Bertoncello, and N. Dietz. "Surface Characterization of CuInS2 with Lamellar Morphology." Journal of The Electrochemical Society 142, no. 8 (August 1, 1995): 2818–23. http://dx.doi.org/10.1149/1.2050097.

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12

Ottewill, Ronald H., Sarah J. Cole, and Julian A. Waters. "Characterization of particle morphology by scattering techniques." Macromolecular Symposia 92, no. 1 (April 1995): 97–107. http://dx.doi.org/10.1002/masy.19950920110.

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13

Song, Jingnan, Ming Zhang, Meng Yuan, Yuhao Qian, Yanming Sun, and Feng Liu. "Morphology Characterization of Bulk Heterojunction Solar Cells." Small Methods 2, no. 3 (February 2, 2018): 1700229. http://dx.doi.org/10.1002/smtd.201700229.

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14

An, Qiufeng, Guangwen Cheng, and Linsheng Li. "Synthesis, characterization, and film morphology of dodecylpolysiloxane." Journal of Applied Polymer Science 101, no. 6 (2006): 4480–86. http://dx.doi.org/10.1002/app.24288.

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15

Koo, J. H., S. C. Lao, J. Lee, D. Z. Chen, C. Lam, W. Yong, M. Londa, and L. A. Pilato. "Morphology and thermal characterization of nanographene platelets." Journal of Materials Science 46, no. 10 (February 1, 2011): 3583–89. http://dx.doi.org/10.1007/s10853-011-5272-7.

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16

Ferris, Sean P., Jeffrey W. Hofmann, David A. Solomon, and Arie Perry. "Characterization of gliomas: from morphology to molecules." Virchows Archiv 471, no. 2 (July 4, 2017): 257–69. http://dx.doi.org/10.1007/s00428-017-2181-4.

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17

Bechteler, Christian, Hannes Kühl, and Ralf Girmscheid. "Morphology and structure characterization of ceramic granules." Journal of the European Ceramic Society 40, no. 12 (September 2020): 4232–42. http://dx.doi.org/10.1016/j.jeurceramsoc.2020.04.044.

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18

Badawy, Waheed A., Rabab M. El-Sherif, and Shaaban A. Khalil. "Porous Si layers—Preparation, characterization and morphology." Electrochimica Acta 55, no. 28 (December 2010): 8563–69. http://dx.doi.org/10.1016/j.electacta.2010.07.057.

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19

Amar, Jacques G., and Fereydoon Family. "Characterization of surface morphology in epitaxial growth." Surface Science 365, no. 1 (September 1996): 177–85. http://dx.doi.org/10.1016/0039-6028(96)00692-9.

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20

Li, Luo-ke, Hai-ming Liu, Zhen-guo Zhang, Peng Cao, and Yuan Yan. "Quantitative Characterization of 3D Road Aggregate Morphology." Journal of Highway and Transportation Research and Development (English Edition) 15, no. 1 (March 2021): 22–30. http://dx.doi.org/10.1061/jhtrcq.0000762.

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21

Teo, Lay Lian, and B. S. Daya Sagar. "Modeling, description, and characterization of fractal pore via mathematical morphology." Discrete Dynamics in Nature and Society 2006 (2006): 1–24. http://dx.doi.org/10.1155/ddns/2006/89280.

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The aim of this paper is to provide description of fast, simple computational algorithms based upon mathematical morphology techniques to extract descriptions of pore channels—throats—and bodies and to represent them in 3D space, and to produce statistical characterization of their descriptions. Towards this goal, a model fractal binary pore is considered and is eroded recursively to generate different slices possessing decreasing degrees of porosity. By employing simple morphology-based approach, each slice of this pore space is decomposed into pore-channel, pore-throat, and pore-body, which are abstract structures that summarize the overall connectivity, orientation, and shape of the pore space. We consider the pore slices and their corresponding morphological quantities to stack them to further represent them in 3D space. We further provide a formulation essentially based on set theory to represent these three morphologic quantities to connect them appropriately across slices. The connected quantities are further fragmented to designate each fragmented portion with orders ranging from 1 toN.

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22

Feng, Zhigang, Xuezai Pan, Guoxing Dai, and Hongguang Liu. "Research on Rock Fracture Surface Morphology Characterization under Brazilian Test." Abstract and Applied Analysis 2014 (2014): 1–10. http://dx.doi.org/10.1155/2014/434898.

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In order to test the differences in the morphology characterization of rock fracture surfaces under different loading directions and rates, the following three steps are operated. Firstly, using Brazilian test, the Brazilian discs are loaded to fracture under different loading modes. Secondly, each rock fracture surface is scanned with a highly accurate laser profilometer and accordingly the coordinates of three lines on every rock fracture surface and three sections of every line are selected to analyze their fracture morphology characterization. Finally, modulus maximum method of wavelet transform, including a new defined power algorithm and signal to noise ratio, and fractal variation method are used to determine the differences in rock fracture surfaces’ morphology characterization under different loading directions and rates. The result illustrates that both modulus maximum and fractal variation method can detect anisotropy of rock fracture failure. Compared to modulus maximum method, fractal variation method shows stronger sensitivity to the change of loading rates, which is more suitable to differentiate the rock fracture surface’s morphology characterization under different loading modes.

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23

Hammarström, Harald, and Lars Borin. "Unsupervised Learning of Morphology." Computational Linguistics 37, no. 2 (June 2011): 309–50. http://dx.doi.org/10.1162/coli_a_00050.

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This article surveys work on Unsupervised Learning of Morphology. We define Unsupervised Learning of Morphology as the problem of inducing a description (of some kind, even if only morpheme-segmentation) of how orthographic words are built up given only raw text data of a language. We briefly go through the history and motivation of the this problem. Next, over 200 items of work are listed with a brief characterization, and the most important ideas in the field are critically discussed. We summarize the achievements so far and give pointers for future developments.

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24

Wang, Ru, Juan Wang, Ming Sun, Bao Hong Gao, Rui Xia Yang, and Yu Ling Liu. "Characterization of Wafer Surface Topography after CMP." Advanced Materials Research 476-478 (February 2012): 2603–7. http://dx.doi.org/10.4028/www.scientific.net/amr.476-478.2603.

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Characterization of the surface morphology after CMP vital refers to the roughness of surface outline at present. The two dimensional parameters characterization based on scanning the outline of surface as the test foundation already cannot satisfy the requirements of engineering; hence three dimensional detection and quantitative calculation of surface morphology can complete characterization. Characterization of surface morphology has made great development from low to high precision accuracy, from a single variety of touch probe to optical, atomic force, and other varieties, from the contact to non-contact, from two dimensions to three dimensions, from a single roughness measurement to simultaneously measurement of waviness, shape error outline information. Scanning probe microscopy can give surface topography of the whole measured area. Because discrimination all can reach the nanometer level surface roughness in x, y and z three directions, Scanning probe microscopy is suitable for measured structure with vertical structure units in nm magnitude and horizontal area in μm scale.

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25

Wollschläger, J. "Morphology and Defect Characterization of Epitaxial Oxide Films." Defect and Diffusion Forum 164 (September 1998): 37–56. http://dx.doi.org/10.4028/www.scientific.net/ddf.164.37.

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26

Zaikina, Julia V., Elayaraja Muthuswamy, Kristina I. Lilova, Zachary M. Gibbs, Michael Zeilinger, G. Jeffrey Snyder, Thomas F. Fässler, Alexandra Navrotsky, and Susan M. Kauzlarich. "Thermochemistry, Morphology, and Optical Characterization of Germanium Allotropes." Chemistry of Materials 26, no. 10 (May 5, 2014): 3263–71. http://dx.doi.org/10.1021/cm5010467.

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27

Preatoni, Ezio, Renato Rodano, Roberto Squadrone, Dario Cazzola, Marco Mazzola, Giancarlo Moroni, Giuseppe Andreoni, and Antonio Pedotti. "Characterization of Foot Morphology through 3D Optical Measures." SAE International Journal of Passenger Cars - Electronic and Electrical Systems 1, no. 1 (June 17, 2008): 585–89. http://dx.doi.org/10.4271/2008-01-1880.

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28

Brasil, A. M., T. L. Farias, M. G. Carvalho, and U. O. Koylu. "Numerical characterization of the morphology of aggregated particles." Journal of Aerosol Science 32, no. 4 (April 2001): 489–508. http://dx.doi.org/10.1016/s0021-8502(00)00097-5.

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29

Nuansing, Wiwat, Siayasunee Ninmuang, Wirat Jarernboon, Santi Maensiri, and Supapan Seraphin. "Structural characterization and morphology of electrospun TiO2 nanofibers." Materials Science and Engineering: B 131, no. 1-3 (July 2006): 147–55. http://dx.doi.org/10.1016/j.mseb.2006.04.030.

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30

Huang, Yangfeng, Yebin Cai, Dongkai Qiao, and Hao Liu. "Morphology-controllable synthesis and characterization of CeO2 nanocrystals." Particuology 9, no. 2 (April 2011): 170–73. http://dx.doi.org/10.1016/j.partic.2010.07.023.

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31

Karpowich, L., S. Wilcke, Rong Yu, G. Harley, J. A. Reimer, and L. C. De Jonghe. "Synthesis and characterization of mixed-morphology CePO4 nanoparticles." Journal of Solid State Chemistry 180, no. 3 (March 2007): 840–46. http://dx.doi.org/10.1016/j.jssc.2006.12.009.

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32

Ben-Jacob, E., P. Garik, T. Mueller, and D. Grier. "Characterization of morphology transitions in diffusion-controlled systems." Physical Review A 38, no. 3 (August 1, 1988): 1370–80. http://dx.doi.org/10.1103/physreva.38.1370.

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33

Fabre, Andrea, Teun Steur, Wim G. Bouwman, Michiel T. Kreutzer, and J. Ruud van Ommen. "Characterization of the Stratified Morphology of Nanoparticle Agglomerates." Journal of Physical Chemistry C 120, no. 36 (September 2016): 20446–53. http://dx.doi.org/10.1021/acs.jpcc.6b07437.

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34

Chen, Wei, Maxim P. Nikiforov, and Seth B. Darling. "Morphology characterization in organic and hybrid solar cells." Energy & Environmental Science 5, no. 8 (2012): 8045. http://dx.doi.org/10.1039/c2ee22056c.

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35

Kimler, Victoria A., Mary Tracy-Bee, Candace D. Ollie, Renee M. Langer, James M. Montante, Charles R. C. Marks, D. Carl Freeman, R. Anton Hough, and John D. Taylor. "Characterization of Melanophore Morphology by Fractal Dimension Analysis." Pigment Cell Research 17, no. 2 (April 2004): 165–72. http://dx.doi.org/10.1046/j.1600-0749.2003.00125.x.

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36

Givand, Jeffrey C., Ronald W. Rousseau, and Peter J. Ludovice. "Characterization of -isoleucine crystal morphology from molecular modeling." Journal of Crystal Growth 194, no. 2 (November 1998): 228–38. http://dx.doi.org/10.1016/s0022-0248(98)00535-1.

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37

., Parveen Kumar. "MORPHOLOGY AND CHARACTERIZATION OF SRXCU1-XO [X=0.1]." International Journal of Research in Engineering and Technology 04, no. 10 (October 25, 2015): 238–42. http://dx.doi.org/10.15623/ijret.2015.0410042.

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38

Lowery, Laura Anne, Gianluca De Rienzo, Jennifer H. Gutzman, and Hazel Sive. "Characterization and Classification of Zebrafish Brain Morphology Mutants." Anatomical Record: Advances in Integrative Anatomy and Evolutionary Biology 292, no. 1 (January 2009): 94–106. http://dx.doi.org/10.1002/ar.20768.

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39

Zhang, Huaijin, Xianlin Meng, Li Zhu, Pu Wang, Xuesong Liu, Zhaohe Yang, Judith Dawes, and P. Dekker. "Growth, Morphology and Characterization of Yb : YVO4 Crystal." physica status solidi (a) 175, no. 2 (October 1999): 705–10. http://dx.doi.org/10.1002/(sici)1521-396x(199910)175:2<705::aid-pssa705>3.0.co;2-n.

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40

Sánchez, Bárbara, Martín S. Gross, Bruno Dalla Costa, and Carlos A. Querini. "Coke analysis by temperature-programmed oxidation: Morphology characterization." Applied Catalysis A: General 364, no. 1-2 (July 2009): 35–41. http://dx.doi.org/10.1016/j.apcata.2009.05.018.

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41

Moody, John A., and Brent M. Troutman. "Characterization of the spatial variability of channel morphology." Earth Surface Processes and Landforms 27, no. 12 (2002): 1251–66. http://dx.doi.org/10.1002/esp.403.

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42

LV, YUZHEN, CHUNPING LI, PING CHE, LIN GUO, and HUIBIN XU. "MORPHOLOGY CONTROLLING AND OPTICAL CHARACTERIZATION OF ZnO NANOMATERIALS." International Journal of Modern Physics B 20, no. 25n27 (October 30, 2006): 3635–39. http://dx.doi.org/10.1142/s0217979206040118.

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Wurtzite ZnO nanomaterials including nanoparticles, nanocolumns and nanorods were successfully synthesized by a solution route. Concentrations of modifying reagent and differences of solvent employed in the synthetic process can effectively adjust the morphologies of the as-grown products. Photoluminescence measurements of the ZnO nanocolumns and nanorods have been carried out at room temperature. A sharp Ultraviolet emission at 386 nm and a weak visible emission centered at 515 nm were observed in the PL spectrum of the nanocolumns, while a UV emission of the nanorods was observed at 377 nm.

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43

BILLAUD, MARIE, ALEXANDER W. LOHMAN, ADAM C. STRAUB, THIBAUD PARPAITE, SCOTT R. JOHNSTONE, and BRANT E. ISAKSON. "Characterization of the Thoracodorsal Artery: Morphology and Reactivity." Microcirculation 19, no. 4 (April 24, 2012): 360–72. http://dx.doi.org/10.1111/j.1549-8719.2012.00172.x.

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44

Ahmadi, Seyed Javad, Yu Dong Huang, and Wei Li. "Morphology and Characterization of Clay-reinforced EPDM Nanocomposites." Journal of Composite Materials 39, no. 8 (April 2005): 745–54. http://dx.doi.org/10.1177/0021998305048154.

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45

Li, Shao-Xiang, Wen-Fang Wang, Lu-Mei Liu, and Guang-Ye Liu. "Morphology and Characterization of Epoxy-acrylate Composite Particles." Polymer Bulletin 61, no. 6 (September 20, 2008): 749–57. http://dx.doi.org/10.1007/s00289-008-1000-0.

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46

Small, Christopher. "Multisensor Characterization of Urban Morphology and Network Structure." Remote Sensing 11, no. 18 (September 17, 2019): 2162. http://dx.doi.org/10.3390/rs11182162.

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The combination of decameter resolution Sentinel 2 and hectometer resolution VIIRS offers the potential to quantify urban morphology at scales spanning the range from individual objects to global scale settlement networks. Multi-season spectral characteristics of built environments provide an independent complement to night light brightness compared for 12 urban systems. High fractions of spectrally stable impervious surface combined with persistent deep shadow between buildings are compared to road network density and outdoor lighting inferred from night light. These comparisons show better spatial agreement and more detailed representation of a wide range of built environments than possible using Landsat and DMSP-OLS. However, they also show that no single low luminance brightness threshold provides optimal spatial correlation to built extent derived from Sentinel in different urban systems. A 4-threshold comparison of 6 regional night light networks shows consistent spatial scaling, spanning 3 to 5 orders of magnitude in size and number with rank-size slopes consistently near −1. This scaling suggests a dynamic balance among the processes of nucleation, growth and interconnection. Rank-shape distributions based on √Area/Perimeter of network components scale similarly to rank-size distributions at higher brightness thresholds, but show both progressive then abrupt increases in fractal dimension of the largest, most interconnected network components at lower thresholds.

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47

Tung, Kuo-Lun, Kai-Shiun Chang, Tian-Tsair Wu, Nien-Jung Lin, Kueir-Rarn Lee, and Juin-Yih Lai. "Recent advances in the characterization of membrane morphology." Current Opinion in Chemical Engineering 4 (May 2014): 121–27. http://dx.doi.org/10.1016/j.coche.2014.03.002.

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48

Clausse, D., F. Gomez, I. Pezron, L. Komunjer, and C. Dalmazzone. "Morphology characterization of emulsions by differential scanning calorimetry." Advances in Colloid and Interface Science 117, no. 1-3 (December 2005): 59–74. http://dx.doi.org/10.1016/j.cis.2005.06.003.

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49

Fang, Hong Wei, Hui Ming Zhao, Zhi He Chen, Ming Hong Chen, and Yue Feng Zhang. "3D shape and morphology characterization of sediment particles." Granular Matter 17, no. 1 (January 9, 2015): 135–43. http://dx.doi.org/10.1007/s10035-014-0545-x.

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50

He, Jinyun, Weimin Wang, Linlang Zhang, Zhengguang Zou, Zhengyi Fu, and Zhe Xu. "Morphology controlled synthesis and characterization of Bi2WO6 photocatalysts." Journal of Wuhan University of Technology-Mater. Sci. Ed. 28, no. 2 (April 2013): 231–34. http://dx.doi.org/10.1007/s11595-013-0670-0.

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