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Journal articles on the topic 'Multidimensional'

Author: Grafiati

Published: 4 June 2021

Last updated: 25 February 2023

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1

Bersisa, Mekonnen, and Almas Heshmati. "A Distributional Analysis of Uni-and Multidimensional Poverty and Inequalities in Ethiopia." Social Indicators Research 155, no. 3 (February 2, 2021): 805–35. http://dx.doi.org/10.1007/s11205-021-02606-w.

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AbstractThis study analyzes uni-and multidimensional poverty and inequalities in rural and small towns in Ethiopia. Unlike the unidimensional measure, the multidimensional measure of poverty shows all the channels through which poverty may manifest itself; it also shows the extent of deprivation. The analysis uses 6 dimensions with 14 indicators to construct a multidimensional index of poverty and inequalities using Ethiopian Households’ Socioeconomic Survey dataset. The study also uses multiple correspondence analyses for determining relative weights in computing a multidimensional index and conducts a stochastic dominance analysis of distribution of poverty for different population segments. The paper sheds light on the degree of inequalities in consumption expenditure and multidimensional deprivations. In addition, it also compares the degree of poverty using the conventional measure of poverty and the multidimensional approach. It also examines the determinants of household poverty status using both unidimensional and multidimensional measures using the logit model. The results show that the intensity, severity, and depth of poverty varies substantially across the 2 measures. The unidimensional measure of poverty shows that 36 percent of the households were poor as compared to 46 percent multidimensionally poor households. Moreover, demographic, regional, and household heads’ characteristics also affect households’ poverty status.

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Chen, Zhenmin, and Tieyong Hu. "Statistical Test for Bivariate Uniformity." Advances in Statistics 2014 (October 19, 2014): 1–6. http://dx.doi.org/10.1155/2014/740831.

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The purpose of the multidimension uniformity test is to check whether the underlying probability distribution of a multidimensional population differs from the multidimensional uniform distribution. The multidimensional uniformity test has applications in various fields such as biology, astronomy, and computer science. Such a test, however, has received less attention in the literature compared with the univariate case. A new test statistic for checking multidimensional uniformity is proposed in this paper. Some important properties of the proposed test statistic are discussed. As a special case, the bivariate statistic test is discussed in detail in this paper. The Monte Carlo simulation is used to compare the power of the newly proposed test with the distance-to-boundary test, which is a recently published statistical test for multidimensional uniformity. It has been shown that the test proposed in this paper is more powerful than the distance-to-boundary test in some cases.

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Wu, Bo, and Yu-Hui Zhang. "A Class of Multidimensional Q-Processes." Journal of Applied Probability 44, no. 01 (March 2007): 226–37. http://dx.doi.org/10.1017/s0021900200002825.

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In this paper we present some necessary conditions for the uniqueness, recurrence, and ergodicity of a class of multidimensionalQ-processes, using the dual Yan-Chen comparison method. Then the coupling method is used to study the multidimensional processes in a specific space. As applications, three models of particle systems are illustrated.

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Zhang, Zhidong, and Luis Garcia. "Examining Dimensionality and Validity of the Academic Integrity Survey Instrument." Journal of Education and Development 7, no. 1 (February 8, 2023): 46. http://dx.doi.org/10.20849/jed.v7i1.1326.

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Dimensional reduction is one of the methods to ensure the quality of a questionnaire. This study examined two methods to reduce the dimension of the questionnaire: multidimensional scaling (MDS) and exploratory factor analysis (EFA). The questionnaire, Awareness of Academic Dishonesty consists of 30 questions. Participants included 110 college students. Multidimensional scaling analysis reduced the multidimensions to essentially two dimensions. The exploratory factor analysis reduced the multidimensions to three dimensions. MDS allowed the researchers to evaluate the questionnaire items by looking at the similarities of these data points. EFA provided an alternative thought about the construct of the questionnaire.

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Prates, Elivania Magalhães, Andréa Da Silva Gomes, Ronaldo Lima Gomes, Fernanda Calasans Costa Lacerda Pessoti, Mônica De Moura Pires, and Monick Midlej do Espírito Santo. "ANÁLISE DA POBREZA SOB A PERSPECTIVA MULTIDIMENSIONAL NOS TERRITÓRIOS DE IDENTIDADE DA BAHIA." InterEspaço: Revista de Geografia e Interdisciplinaridade 7, no. 20 (March 26, 2021): 202102. http://dx.doi.org/10.18764/2446-6549.e202102.

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ANALYSIS OF POVERTY FROM A MULTIDIMENSIONAL PERSPECTIVE IN THE BAHIA'S IDENTITY TERRITORIESANÁLISIS DE LA POBREZA DESDE UNA PERSPECTIVA MULTIDIMENSIONAL EN LOS TERRITORIOS DE IDENTIDAD DE BAHIARESUMOSob a perspectiva multidimensional e com base no conceito de pobreza desenvolvido por Amartya Sen, cuja noção elaborada refere-se à ausência ou privação de capacidades básicas, este trabalho mensura e analisa a pobreza nos Territórios de Identidade da Bahia. Para tanto, utiliza-se o Índice de Pobreza Multidimensional - IPM criado pela Iniciativa de Pesquisas em Pobreza e Desenvolvimento Humano da Universidade de Oxford, em parceria com o Programa das Nações Unidas para o Desenvolvimento. Foram utilizados os microdados da amostra do censo demográfico do Instituto Brasileiro de Geografia e Estatística – IBGE referentes ao ano de 2010. Os resultados da pesquisa mostram que a proporção de pobres multidimensionais no estado da Bahia corresponde a 25,46%. Os indicadores que carecem de maior atenção são: anos de escolaridade, saneamento e coleta de lixo, os quais apresentaram maiores percentuais de privações para diversos territórios baianos. Com relação à intensidade, verificou-se que sua manifestação na Bahia é maior que sua incidência, resultando em 36,96% a média de privações compartilhadas pelos indivíduos multidimensionalmente pobres. O IPM se apresentou mais crítico para os Territórios de Identidade Bacia do Rio Corrente (0,143) e Baixo Sul (0,141); já para a Bahia, esse resultado foi de 0,094. A mensurabilidade torna-se importante para melhor embasar as políticas públicas de assistência social e de promoção do desenvolvimento dos territórios.Palavras-chave: Pobreza; Capacitações; Índice Multidimensional.ABSTRACTThis study aims at measuring and analyzing the state of poverty in Identity Territories of Bahia under multidimensional approach based on the concept of poverty of absence or deprivation of basic capabilities by Amartya Sen. The present research measured poverty using the Multidimensional Poverty Index - MPI created by Poverty and Human Development Initiative (OPHI) at the University of Oxford, in a partnership with the United Nations Development Programme (UNDP). Micro-data on the basis of demographic census of 2010 carried out by Brazilian Institute of Geography and Statistics (IBGE) was used. The survey results show that the proportion of multidimensional poorness is corresponding to 25.46%. The qualitative indicators that need further attention are: years of schooling, sanitation and garbage collection. They had higher percentages of deprivation among the Territories. Regarding to the intensity, Bahia has higher numbers if compared to the incidence rates, resulting 36.96% in the average of the deprivation of multidimensional poorness. The MPI was more critical to the Identity Territories of Bacia do Rio Corrente (0.143) and Baixo Sul (0.141) compared to Bahia which result was 0.094. The measurability of poverty becomes important to better endorse public policies on social assistance and to better promote the development of the Territories.Keywords: Poverty; Capability; Multidimensional Index.RESUMENEste documento mide y analiza la pobreza en los Territorios de Identidad de Bahía desde una perspectiva multidimensional y basada en el concepto de pobreza desarrollado por Amartya Sen como ausencia o privación de habilidades básicas. Se utiliza el Índice de Pobreza Multidimensional - IPM creado por la Iniciativa de Investigación sobre la Pobreza y Desarrollo Humano de la Universidad de Oxford, en asociación con el Programa de las Naciones Unidas para el Desarrollo. Utilizamos los microdatos de la muestra del censo del Instituto Brasileño de Geografía y Estadística para 2010. Los resultados de la encuesta muestran que la proporción de pobres multidimensionales en el estado de Bahía corresponde al 25,46%. Los indicadores que necesitan más atención son: años de escolaridad, saneamiento y recolección de basura que presentaron porcentajes más altos de privación para los diversos territorios de Bahía. Con respecto a la intensidad, se encontró que su manifestación en Bahía es mayor que su incidencia, lo que resulta en 36.96% de la privación promedio compartida por individuos pobres multidimensionales. El IPM fue más crítico para los Territorios de Identidad de la Cuenca del Río Corrente (0.143) y Low Sul (0.141), para Bahía, este resultado fue 0.094. La mensurabilidad se vuelve importante para apoyar mejor las políticas públicas de asistencia social y la promoción del desarrollo territorial.Palabras clave: Pobreza; Entrenamiento; Índice Multidimensional.

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6

Cheng, Lizhi, and Yonghong Zeng. "Multidimensional polynomial transform algorithm for multidimensional DFT." Electronics Letters 36, no. 11 (2000): 990. http://dx.doi.org/10.1049/el:20000698.

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7

Rodrigues, Danuzia Lima, Ricardo Bruno Nascimento dos Santos, Izete Pengo Bagolin, and Danilo Araujo Fernandes. "Pobreza multidimensional intraurbana na região metropolitana de Belém." Redes 25 (December 18, 2020): 2251–73. http://dx.doi.org/10.17058/redes.v25i0.14166.

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O objetivo deste artigo é analisar as múltiplas dimensões da pobreza intraurbana na Região Metropolitana de Belém, por meio dos microdados do Censo de 2010. Para isso, são utilizados os arcabouços teóricos da Abordagem das Capacitações e da pobreza multidimensional e aplica-se a metodologia de Alkire e Santos (2010). Os resultados evidenciam existência de diferenças entre a pobreza monetária e a pobreza multidimensional e mostram que áreas consideradas menos pobres em termos multidimensionais não são as mesmas quando avaliadas em termos monetários. Percebe-se que as áreas de ponderação, em que praticamente coincidem os indicadores de renda e o multidimensional, não estão na mesma posição na classificação geral dos indicadores sintéticos de avaliação sobre pobreza. Adicionalmente, a composição de privações domiciliares difere entre as áreas de ponderação e a incidência da pobreza multidimensional ainda é elevada, mesmo após os avanços sociais vastamente relatados na literatura nos últimos 15 anos.

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8

Patel, Alpa R., and Dr Jayesh M. Patel. "Multidimensional model and OLAP operations." Indian Journal of Applied Research 3, no. 3 (October 1, 2011): 57–58. http://dx.doi.org/10.15373/2249555x/mar2013/20.

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9

Vanžurová, Alena. "Tensor approach to multidimensional webs." Mathematica Bohemica 123, no. 3 (1998): 225–42. http://dx.doi.org/10.21136/mb.1998.126070.

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10

Najitama, Esha, Ghozali Maski, and Asfi Manzilati. "Analysis of multidimensional poverty dynamics in Indonesia: The effect of demographic and institutional factors." Journal of Innovation in Business and Economics 4, no. 02 (December 31, 2020): 87–96. http://dx.doi.org/10.22219/jibe.v4i02.15630.

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Measuring poverty only from a monetary perspective is lacking. Given the variety of human needs, poverty needs to be measured multidimensionally. Hence, this study analyzes multidimensional poverty dynamics and identifies its determinants from the demographic and institutional factors. Using the Multidimensional Poverty Index (MPI) and data from the two survey periods of the Indonesia Family Life Survey (IFLS), it is known that multidimensional poverty tends to be transient rather than chronic. The highest education level of the head of the household, the level of dependency, the island of residence, the village political system, and the village government's corruption affect both chronic and transient poverty categories. The marital status of household heads, household size, and customary norms only affected the chronic poor category

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11

John, Peter St, Martin Slann, and Bernard Schechterman. "Multidimensional Terrorism." International Journal 44, no. 3 (1989): 736. http://dx.doi.org/10.2307/40202630.

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12

SARDINHA, Tony Berber. "Análise multidimensional." DELTA: Documentação de Estudos em Lingüística Teórica e Aplicada 16, no. 1 (2000): 99–127. http://dx.doi.org/10.1590/s0102-44502000000100005.

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Este trabalho oferece uma retrospectiva da abordagem conhecida por 'Análise Multidimensional', iniciada por Douglas Biber. O trabalho apresenta os conceitos centrais relacionados a esta abordagem e resenha os estudos principais que a utilizaram. Trabalhos ainda inéditos, realizados no Brasil, também são resenhados. O artigo ainda inclui uma discussão acerca das principais críticas relacionadas à Análise Multidimensional.

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13

Gower, J. C., F. Cox, and M. A. A. Cox. "Multidimensional Scaling." Journal of the Royal Statistical Society. Series A (Statistics in Society) 159, no. 1 (1996): 184. http://dx.doi.org/10.2307/2983485.

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14

Jeffers, J. N. R., and Mark L. Davison. "Multidimensional Scaling." Statistician 34, no. 2 (1985): 257. http://dx.doi.org/10.2307/2988171.

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15

van Vught, Frans, and Don F. Westerheijden. "Multidimensional ranking." Higher Education Management and Policy 22, no. 3 (December 20, 2010): 1–26. http://dx.doi.org/10.1787/hemp-22-5km32wkjhf24.

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16

Delfino, Maria Claudia Nunes. "Análise multidimensional." Cadernos de Linguística 2, no. 4 (September 11, 2021): e474. http://dx.doi.org/10.25189/2675-4916.2021.v2.n4.id474.

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A Linguística de Corpus, um dos ramos da Linguística Aplicada, tem como um dos seus construtos metodológicos a análise multidimensional, uma metodologia que leva em consideração a parte quantitativa da linguística, onde grandes quantidades de textos que formam o corpus de análise passam por procedimentos estatísticos. As características linguísticas dos textos são agrupadas em fatores de acordo com sua coocorrência nos textos que, ao serem interpretados linguisticamente, são chamadas de dimensões. Essa abordagem metodológica teve início na década de 80 com o linguista Douglas Biber nos Estados Unidos implementando o que chamamos abordagem americana da Linguística de Corpus. No Brasil, esta abordagem é desenvolvida tanto em textos em língua inglesa, portuguesa, alemã e espanhola e o LAEL na PUC-SP é o polo de desenvolvimento desta metodologia. O presente trabalho é uma revisão de literatura dessa abordagem que a princípio foi desenvolvida para análise gramatical / funcional e, hoje em dia, já há trabalhos na área lexical, semântica e colocacional.

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17

Berry, Robert Q., and Mark W. Ellis. "Multidimensional Teaching." Mathematics Teaching in the Middle School 19, no. 3 (October 2013): 172–78. http://dx.doi.org/10.5951/mathteacmiddscho.19.3.0172.

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18

Reyment, R. A. "Multidimensional Palaeobiology." Biometrics 50, no. 3 (September 1994): 897. http://dx.doi.org/10.2307/2532824.

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Ahamad, Mustaque, Mostafa H. Ammar, and Shun Yan Cheung. "Multidimensional voting." ACM Transactions on Computer Systems 9, no. 4 (November 1991): 399–431. http://dx.doi.org/10.1145/118544.118552.

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20

Krzywinski, Martin, and Erica Savig. "Multidimensional data." Nature Methods 10, no. 7 (June 27, 2013): 595. http://dx.doi.org/10.1038/nmeth.2531.

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Kraack, Jan Philip. "Multidimensional scrambling." Nature Physics 14, no. 4 (April 2018): 328. http://dx.doi.org/10.1038/s41567-018-0121-0.

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House, Robert V., and Kenneth L. Hastings. "Multidimensional Immunomodulation." Journal of Immunotoxicology 1, no. 2 (January 2004): 123–29. http://dx.doi.org/10.1080/15476910490503646.

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23

Lloyd, G. E. R. "MULTIDIMENSIONAL REALITY." Common Knowledge 17, no. 1 (January 1, 2011): 27–30. http://dx.doi.org/10.1215/0961754x-2010-031.

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Wills, S. "Truly Multidimensional." Science 332, no. 6032 (May 19, 2011): 918. http://dx.doi.org/10.1126/science.1207841.

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Houghton, A., H. J. Kwon, and J. B. Marston. "Multidimensional bosonization." Advances in Physics 49, no. 2 (March 2000): 141–228. http://dx.doi.org/10.1080/000187300243363.

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Li, Yongyan. "Multidimensional enculturation." Multiple Perspectives on L1 and L2 Academic Literacy in Asia Pacific and Diaspora Contexts 15, no. 1 (June 30, 2005): 153–70. http://dx.doi.org/10.1075/japc.15.1.10li.

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The present paper examines the disciplinary enculturation experience of a Chinese doctoral student. I first refer to Lave and Wenger’s (1991) concept of legitimate peripheral participation (LPP) as the theoretical background of this study. I then present the case of Fei, a doctoral student of physics in a major university in East China, focusing on his interactions with specialist texts, the supervisor, and the research community. In the discussion of the findings, I cast Fei’s experience in the light of LPP. I conclude by emphasizing the value of naturalistic case studies in extending English educators’ scope of vision of academic enculturation.

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27

Jaffe, Nick. "Multidimensional Connectors." Teaching Artist Journal 6, no. 2 (April 9, 2008): 95–96. http://dx.doi.org/10.1080/15411790801910644.

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Henry, Tyson R., and Scott E. Hudson. "Multidimensional icons." ACM Transactions on Graphics 9, no. 1 (January 3, 1990): 133–37. http://dx.doi.org/10.1145/77635.77641.

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Avasarala, Sameer K., Michael S. Machuzak, and Thomas R. Gildea. "Multidimensional Precision." Journal of Bronchology & Interventional Pulmonology 27, no. 2 (April 2020): 153–55. http://dx.doi.org/10.1097/lbr.0000000000000650.

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Pfeiffer, Susan M., and Paul T. P. Wong. "Multidimensional Jealousy." Journal of Social and Personal Relationships 6, no. 2 (May 1989): 181–96. http://dx.doi.org/10.1177/026540758900600203.

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Eliaz, Kfir, and Pietro Ortoleva. "Multidimensional Ellsberg." Management Science 62, no. 8 (August 2016): 2179–97. http://dx.doi.org/10.1287/mnsc.2015.2240.

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Jolliffe, Ian. "Multidimensional Scaling." Technometrics 38, no. 4 (November 1996): 403–4. http://dx.doi.org/10.1080/00401706.1996.10484556.

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Armstrong, Daniel W., and Staci L. Massey Simonich. "Multidimensional Separations." Analytical Chemistry 86, no. 23 (November 3, 2014): 11473. http://dx.doi.org/10.1021/ac503953m.

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Trager, Robert F. "Multidimensional Diplomacy." International Organization 65, no. 3 (July 2011): 469–506. http://dx.doi.org/10.1017/s0020818311000178.

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AbstractStates often negotiate with each other over more than one issue at the same time. This article presents a model of multidimensional international crisis bargaining. Unlike unidimensional bargaining, with two issue dimensions states can send costless signals about their resolve that have dramatic effects on other states' beliefs and actions. One reason is that when states claim a willingness to fight over an issue they in fact are not willing to fight over, they may lose the opportunity to get what they really want without conflict. As a result, when there is a chance that adversaries may each be willing to fight over two issues, the states can even sometimes convey with certainty when they will fight for both issues. The model also leads to some surprising comparative statics, for example, decreases in the probability that the target is willing to fight can increase the probability of war.

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Quinzii, Martine, and Jean-Charles Rochet. "Multidimensional signalling." Journal of Mathematical Economics 14, no. 3 (January 1985): 261–84. http://dx.doi.org/10.1016/0304-4068(85)90003-5.

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Joos, Thomas, and Steven Bodovitz. "Multidimensional proteomics." Drug Discovery Today 8, no. 19 (October 2003): 879–80. http://dx.doi.org/10.1016/s1359-6446(03)02848-4.

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Hirsch, Thomas M. "Multidimensional Equating." Journal of Educational Measurement 26, no. 4 (December 1989): 337–49. http://dx.doi.org/10.1111/j.1745-3984.1989.tb00338.x.

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Koellner, Karen, Melissa Colsman, and Rachael Risley. "Multidimensional Assessment." TEACHING Exceptional Children 44, no. 2 (November 2011): 48–56. http://dx.doi.org/10.1177/004005991104400205.

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Koellner, Karen, Melissa Colsman, and Rachael Risley. "Multidimensional Assessment." TEACHING Exceptional Children 47, no. 2 (October 13, 2014): 103–11. http://dx.doi.org/10.1177/0040059914553206.

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Mellström, Ulf. "Multidimensional masculinities." NORMA 9, no. 2 (April 3, 2014): 81–83. http://dx.doi.org/10.1080/18902138.2014.910328.

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Mugavin, Marie E. "Multidimensional Scaling." Nursing Research 57, no. 1 (January 2008): 64–68. http://dx.doi.org/10.1097/01.nnr.0000280659.88760.7c.

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Walter, Bruce, Adam Arbree, Kavita Bala, and Donald P. Greenberg. "Multidimensional lightcuts." ACM Transactions on Graphics 25, no. 3 (July 2006): 1081–88. http://dx.doi.org/10.1145/1141911.1141997.

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Bremser, Wolfgang, and Winfried Fachinger. "Multidimensional spectroscopy." Magnetic Resonance in Chemistry 23, no. 12 (December 1985): 1056–71. http://dx.doi.org/10.1002/mrc.1260231208.

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Hout, Michael C., Megan H. Papesh, and Stephen D. Goldinger. "Multidimensional scaling." Wiley Interdisciplinary Reviews: Cognitive Science 4, no. 1 (October 8, 2012): 93–103. http://dx.doi.org/10.1002/wcs.1203.

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45

Venturi, G. "Multidimensional cosmology." Lettere Al Nuovo Cimento Series 2 44, no. 1 (September 1985): 43–47. http://dx.doi.org/10.1007/bf02746950.

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Greenleaf, J. "Multidimensional echocardiography." Ultrasonic Imaging 14, no. 2 (April 1992): 202. http://dx.doi.org/10.1016/0161-7346(92)90041-s.

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Schmidt, Torsten C., Oliver J. Schmitz, and Thorsten Teutenberg. "Multidimensional chromatography." Analytical and Bioanalytical Chemistry 407, no. 1 (October 24, 2014): 117–18. http://dx.doi.org/10.1007/s00216-014-8265-y.

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48

Thiel, Stuart E. "Multidimensional auctions." Economics Letters 28, no. 1 (January 1988): 37–40. http://dx.doi.org/10.1016/0165-1765(88)90068-7.

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Baldwin, William A., and George O. Strawn. "Multidimensional trees." Theoretical Computer Science 84, no. 2 (July 1991): 293–311. http://dx.doi.org/10.1016/0304-3975(91)90165-x.

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Rogozovskyi, Oleg A. "Multidimensional array signal processing with multidimensional matrix operations." Journal of the Acoustical Society of America 105, no. 2 (February 1999): 1253. http://dx.doi.org/10.1121/1.426010.

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