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Relevant bibliographies by topics / Chernoff faces

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Academic literature on the topic 'Chernoff faces'

Author: Grafiati

Published: 4 June 2021

Last updated: 11 February 2022

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Journal articles on the topic "Chernoff faces"

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DIRGANTARA, I. WAYAN WIDHI, KOMANG GDE SUKARSA, and KOMANG DHARMAWAN. "POTRET KESEJAHTERAAN RAKYAT DI PROVINSI BALI MENGGUNAKAN METODE CHERNOFF FACES." E-Jurnal Matematika 2, no. 3 (2013): 1. http://dx.doi.org/10.24843/mtk.2013.v02.i03.p040.

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Chernoff Faces method is a graphical method of visualization techniques to present data with many variables in the form of a cartoon face which can be determined by 20 parameters or less. In this research it was shown how the Chernoff Faces method was used to see welfare of the people in the province of Bali and Bali's nine regencies. To pair the variables and Chernoff’s facial features, then we used Principal Component Analysis and survey to make the faces look more human. The result from 18 indicators of welfare of the people in the province of Bali, only 8 indicators were not really well. I

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Hunt, Neville. "Chernoff Faces in Microsoft Excel." Teaching Statistics 26, no. 3 (2004): 75–77. http://dx.doi.org/10.1111/j.1467-9639.2004.00173.x.

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Battagel, Joanna M. "Chernoff Faces: An Orthodontic Application." British Journal of Orthodontics 22, no. 2 (1995): 135–44. http://dx.doi.org/10.1179/bjo.22.2.135.

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This retrospective study examined 21 children (12 males and nine females) with Class III malocclusions, who had been successfully treated by a non-extraction technique and for whom follow-up records were available at least 2 years after all treatment and retention had ceased. On the basis of their post-retention records, children were divided into two groups: those who remained stable (n=10) and those whose treatment relapsed (n=11). A graphical technique of data description, Chernoff faces, in which variables for each individual may be portrayed by appropriate scaling of selected facial featu

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HARADA, Masae, and Masaaki SIBUYA. "Effectiveness of the Classification Using Chernoff Faces." Japanese journal of applied statistics 20, no. 1 (1991): 39–48. http://dx.doi.org/10.5023/jappstat.20.39.

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Nel, Deon, Leyland Pitt, and Trevor Webb. "Using Chernoff faces to portray service quality data." Journal of Marketing Management 10, no. 1-3 (1994): 247–55. http://dx.doi.org/10.1080/0267257x.1994.9964271.

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Siva, N., A. Chaparro, D. Nguyen, and E. Palmer. "Visual Search Efficiency for Features in Chernoff Faces." Journal of Vision 13, no. 9 (2013): 689. http://dx.doi.org/10.1167/13.9.689.

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Raciborski, Rafal. "Graphical Representation of Multivariate Data using Chernoff Faces." Stata Journal: Promoting communications on statistics and Stata 9, no. 3 (2009): 374–87. http://dx.doi.org/10.1177/1536867x0900900302.

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RAHU, MATI. "Graphical Representation of Cancer Incidence Data: Chernoff Faces." International Journal of Epidemiology 18, no. 4 (1989): 763–67. http://dx.doi.org/10.1093/ije/18.4.763.

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Osadchaya, I. A., O. G. Berestneva, and Ye V. Nemerov. "ANALYSIS OF MULTIDIMENSIONAL MEDICAL DATA USING PICTOGRAPHICS «CHERNOFF FACES»." Bulletin of Siberian Medicine 13, no. 4 (2014): 89–93. http://dx.doi.org/10.20538/1682-0363-2014-4-89-93.

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Battagel, Joanna M. "Identification of the Relapsing Class III Face: Chernoff Faces in Orthodontics." British Journal of Orthodontics 20, no. 3 (1993): 193–202. http://dx.doi.org/10.1179/bjo.20.3.193.

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Thirty Class III patients, treated by a standard non-extraction technique, provided the material for this study. Records were examined at the beginning of treatment and a minimum of 2 years out of all retention. On the basis of their post-retention occlusions, children were sub-divided into three groups: stable, borderline, and relapsed. Using this classification, a four-variable discriminant model had been generated which correctly indicated the eventual Outcome from the pretreatment data. A graphical technique not previously described in orthodontics and suitable for displaying multivariate

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Dissertations / Theses on the topic "Chernoff faces"

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Santos, Levi Alã Neves dos. "Contribuição da mineração de dados e da otimização heurística para a interpretação dos dados da produção científica brasileira." reponame:Repositório Institucional da UFBA, 2011. http://www.repositorio.ufba.br/ri/handle/ri/7837.

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Submitted by Duarte Zeny (zenydu@gmail.com) on 2013-01-13T13:09:21Z No. of bitstreams: 1 Dissertação_Levi_2011.pdf: 3299266 bytes, checksum: 6f8ae17be138738ad5e24c3ea563ff0a (MD5)<br>Made available in DSpace on 2013-01-13T13:09:21Z (GMT). No. of bitstreams: 1 Dissertação_Levi_2011.pdf: 3299266 bytes, checksum: 6f8ae17be138738ad5e24c3ea563ff0a (MD5)<br>Estudo experimental com métodos de mineração de dados e de otimização heurística. Destaca a aplicação de mapas temáticos, faces de Chernoff e lógica difusa na análise de dados multivariados, possibilitando estabelecer classificação a partir de

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BUENO, Márcio Augusto Silva. "Meta3d - uma ferramenta para visualização de informações em 3d." Universidade Federal de Pernambuco, 2005. https://repositorio.ufpe.br/handle/123456789/2804.

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Made available in DSpace on 2014-06-12T16:01:16Z (GMT). No. of bitstreams: 2 arquivo7284_1.pdf: 2836057 bytes, checksum: 6c52cb49399f14761d49267eaea4b610 (MD5) license.txt: 1748 bytes, checksum: 8a4605be74aa9ea9d79846c1fba20a33 (MD5) Previous issue date: 2005<br>Informação é o bem mais precioso para as mais diversas organizações. Uma das formas de obter informação a partir de um conjunto de dados é através de técnicas de visualização que combinam o poder de processamento dos computadores com a capacidade visual humana de reconhecer formas, padrões e tendências. O objetivo deste trabal

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Aleksikj, Stefan. "Visualization of Quantified Self data from Spotify using avatars." Thesis, Linnéuniversitetet, Institutionen för datavetenskap och medieteknik (DM), 2018. http://urn.kb.se/resolve?urn=urn:nbn:se:lnu:diva-78293.

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The increased interest for self-tracking through the use of technology has given birth to the Quantified Self movement. The movement empowers users to gain self-knowledge from their own data. The overall idea is fairly recent and as such it provides a vast space for exploration and research. This project contributes to the Quantified self movement by proposing a concept for visualization of personal data using an avatar. The overall work finds inspiration in Chernoff faces visualization and it uses parts of the presentation method within the project design. This thesis presents a visualizati

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Chin-ShiuLin and 林敬修. "The Application of the Cluster Analysis and the Chernoff Faces in the Business Classification." Thesis, 2013. http://ndltd.ncl.edu.tw/handle/66281806796977339847.

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碩士<br>國立成功大學<br>高階管理碩士在職專班(EMBA)<br>101<br>If company operation continues to create a competitive advantage, it is necessary to understand the relative competitiveness of companies in the industry. In the benchmarking study, the companies are the object of study that used the operating performance to select the benchmarking ones in different industries. Whether it is the research of the operating performance, the stock object choice or market analysis will need to do the multivariate data analysis. If using the simple chart to show the situation of the multivariate data and further to compare

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Kuan-YuLu and 陸冠佑. "The Application of Two-stage Cluster Analysis and the Chernoff Faces in the Stocks of Food Industry." Thesis, 2013. http://ndltd.ncl.edu.tw/handle/31111149774462497007.

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碩士<br>國立成功大學<br>統計學系碩博士班<br>101<br>The purpose of this research is to study the companies cluster and to present the situation of financial ratios by Chernoff faces. The data is from the stocks of food industry, using financial ratios is in five categories of indicators: financial structure, solvency, business capacity, profitability, and cash flow. The statistics methods are the two-stage cluster analysis of multivariate analysis and the Chernoff faces. R software is a tool to draw Chernoff faces, but its support of the variable is limited to 15 variables; however, the financial ratios are 20

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Cheng, H. J., and 鄭馨蓉. "The Application of The Chernoff Face under The Cluster Analysis." Thesis, 1995. http://ndltd.ncl.edu.tw/handle/17128137073715687033.

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Books on the topic "Chernoff faces"

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Chusna, Siti Fu'adah. Metode grafis chernoff-faces dalam analisis kelompok dan penerapannya pada kasus industri kerajinan rumah tangga di Indonesia: Laporan penelitian. Fakultas Pertanian, Universitas Islam Malang, 2005.

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Book chapters on the topic "Chernoff faces"

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Chernoff, Herman. "Chernoff Faces." In International Encyclopedia of Statistical Science. Springer Berlin Heidelberg, 2011. http://dx.doi.org/10.1007/978-3-642-04898-2_171.

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Nuñez, José Jesús Reyes, Anita Rohonczi, Cristina E. Juliarena de Moretti, et al. "Updating Research on Chernoff Faces for School Cartography." In Lecture Notes in Geoinformation and Cartography. Springer Berlin Heidelberg, 2011. http://dx.doi.org/10.1007/978-3-642-19214-2_1.

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Iurgel, Ido Aharon, Andreas Petker, Björn Herrmann, Christina Martens, and Pedro Ribeiro. "Living Chernoff Faces: Bringing Drama and Infotainment to Public Displays." In Lecture Notes in Computer Science. Springer International Publishing, 2013. http://dx.doi.org/10.1007/978-3-319-03161-3_51.

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Guha, Aioub H., and Gabriel J. Assaf. "Representing Collected Road Condition Data with Chernoff Faces for Evaluation of Pavement Conditions." In Testing and Characterization of Asphalt Materials and Pavement Structures. Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-95789-0_13.

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Moiz, Salman Abdul, and Raghavendra Rao Chillarige. "Method Level Code Smells: Chernoff Face Visualization." In Learning and Analytics in Intelligent Systems. Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-24322-7_63.

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Fazlagić, Jan, Windham Loopesko, Leszek Matuszak, and Rigby Johnson. "Perspectives and Good Practices in Visualization of Knowledge About Public Entities." In Advances in Human and Social Aspects of Technology. IGI Global, 2018. http://dx.doi.org/10.4018/978-1-5225-4990-1.ch011.

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Visualization of knowledge in public entities is becoming more and more popular due to the development of information technology tools, the demand for solutions allowing for reduction of information overload (IO), and new approaches to local government, including citizen participation. The chapter presents some case study examples of knowledge visualization in public entities with some conclusions and recommendations for policy makers. Additionally, it presents a complete map of certain Polish counties prepared by the authors. The authors applied, apart from the visualization in the form a map, the “Chernoff Faces” method (invented by Herman Chernoff in 1973). This method displays multivariate data on Polish counties in the shape of a human face. The individual parts, such as eyes, ears, mouth, and nose, represent values of the variables by their shape, size, placement, and orientation. The idea behind using faces is that humans easily recognize faces and notice small changes without difficulty. Chernoff Faces handle each variable differently.

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"John Hart Discusses High Dimensional Visualizations and Chernoff Faces." In Glyphs: Part 2. University of Illinois, 2016. http://dx.doi.org/10.4135/9781529773057.n2.

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Conference papers on the topic "Chernoff faces"

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Kabulov, B. T., and N. B. Tashpulatova. "Enhanced Chernoff faces." In 2010 4th International Conference on Application of Information and Communication Technologies (AICT). IEEE, 2010. http://dx.doi.org/10.1109/icaict.2010.5612059.

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Morris, Christopher J., David S. Ebert, and Penny L. Rheingans. "Experimental analysis of the effectiveness of features in Chernoff faces." In 28th AIPR Workshop: 3D Visualization for Data Exploration and Decision Making, edited by William R. Oliver. SPIE, 2000. http://dx.doi.org/10.1117/12.384865.

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Ruixia Song, Zhaoxia Zhao, and Meifang Ou. "A novel clustering method for Chernoff faces based on V-system." In 2009 International Conference on Information and Automation (ICIA). IEEE, 2009. http://dx.doi.org/10.1109/icinfa.2009.5205165.

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VanHoudnos, Nathan, William Casey, David French, et al. "This Malware Looks Familiar: Laymen Identify Malware Run-time Similarity with Chernoff faces and Stick Figures." In 10th EAI International Conference on Bio-inspired Information and Communications Technologies (formerly BIONETICS). EAI, 2017. http://dx.doi.org/10.4108/eai.22-3-2017.152417.

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