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Journal articles on the topic 'Multidimensional process'

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Published: 8 February 2025

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1

Tomko, Mary Kay. "Recovery: A Multidimensional Process." Issues in Mental Health Nursing 9, no. 2 (January 1988): 139–49. http://dx.doi.org/10.3109/01612848809140919.

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2

MIZUTANI, Daijiro, Kengo OBAMA, Kiyoyuki KAITO, and Kiyoshi KOBAYASHI. "MULTIDIMENSIONAL INFRASTRUCTURE DETERIORATION PROCESS MODEL." Journal of Japan Society of Civil Engineers, Ser. D3 (Infrastructure Planning and Management) 72, no. 1 (2016): 34–51. http://dx.doi.org/10.2208/jscejipm.72.34.

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3

Huang, Jih-Jeng, Gwo-Hshiung Tzeng, and Chorng-Shyong Ong. "Multidimensional data in multidimensional scaling using the analytic network process." Pattern Recognition Letters 26, no. 6 (May 2005): 755–67. http://dx.doi.org/10.1016/j.patrec.2004.09.027.

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4

Syuzev, V. V., E. V. Smirnova, and A. V. Proletarsky. "Algorithms of multidimensional random process simulation." Computer Optics 45, no. 4 (July 2021): 627–37. http://dx.doi.org/10.18287/2412-6179-co-770.

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The article discusses two approaches to modeling signals and processes: the method of filter construction and the trigonometric method. It is shown that the later approach is more promising, since an increase in the signal/process representation dimension mathematically means adding a term to the basis function formula, which gives access to fast simulation algorithms. Examples of algorithms for multidimensional simulation of random processes using two methods are given and a software system that implements these algorithms is described. The results provided by the software system will allow you to predict characteristics of engineering projects (accuracy and speed of modeling algorithms). Due to the high relevance of and need for fundamental research of methods and algorithms for digital transformation of the component base, the digitalization of all aspects of activity, including the synthesis of new materials, the development of new methods for designing micro- and nano-systems, the article aims to expand the scope of the spectral method of simulating multidimensional processes using original algorithmic complexes.
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5

Pishchukhin, Aleksandr. "Multidimensional monitoring of a streaming process." IOP Conference Series: Materials Science and Engineering 709 (January 3, 2020): 033024. http://dx.doi.org/10.1088/1757-899x/709/3/033024.

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6

Ibarrola, P., and R. Vélez. "Hypothesis Testing for Multidimensional Gaussian Process." Theory of Probability & Its Applications 37, no. 1 (January 1993): 142–45. http://dx.doi.org/10.1137/1137032.

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7

Sznitman, A. S., and S. R. S. Varadhan. "A multidimensional process involving local time." Probability Theory and Related Fields 71, no. 4 (1986): 553–79. http://dx.doi.org/10.1007/bf00699041.

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8

Kurpius, DeWayne J., Dale R. Fuqua, and Thaddeus Rozecki. "The Consulting Process: A Multidimensional Approach." Journal of Counseling & Development 71, no. 6 (July 8, 1993): 601–6. http://dx.doi.org/10.1002/j.1556-6676.1993.tb02249.x.

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9

Deslauriers, Gilles, Jacques Dubois, and Serge Dubuc. "Multidimensional Iterative Interpolation." Canadian Journal of Mathematics 43, no. 2 (April 1, 1991): 297–312. http://dx.doi.org/10.4153/cjm-1991-016-4.

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AbstractWe define an iterative interpolation process for data spread over a closed discrete subgroup of the Euclidean space. We describe the main algebraic properties of this process. This interpolation process, under very weak assumptions, is always convergent in the sense of Schwartz distributions. We find also a convenient necessary and sufficient condition for continuity of each interpolation function of a given iterative interpolation process.
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10

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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11

Mambo, Lewis N. K. "From Multidimensional Ornstein - Uhlenbeck Process to Bayesian Vector Autoregressive Process." Journal of Mathematics Research 15, no. 1 (February 1, 2023): 32. http://dx.doi.org/10.5539/jmr.v15n1p32.

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The main purpose of  this paper is to make the connexion between stochastic analysis, the Bayesian Statistics, and time series analysis for policy analysis. This approach solves the problem of mathematical modelling - the presence of uncertainties in the models and parameters -  that reduces the  policy analysis and forecasting   effectiveness. By using the multiple It\^o  integral, the multidimensional Ornstein - Uhlenbeck process can be written as a Vector Autoregressive with lag 1 (VAR(1)) that is the generalization of Vector Autoregressive process. The  limit of this approach is in fact it requires  the strong foundations of stochastic analysis, the Bayesian Statistics, and time series analysis.
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12

Sucharittham, Nanthawadee, Choochart Haruechaiyasak, Hieu Chi Dam, and Thanaruk Theeramunkong. "Multidimensional Sentiment Cube Mining for Process Monitoring." Trends in Sciences 19, no. 9 (April 9, 2022): 3682. http://dx.doi.org/10.48048/tis.2022.3682.

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Process monitoring is essential for quality improvement because it is necessary to find the answers to which business issues need to be understood. In the era of social media, many critiques concern the business domain, including life insurance, which is one of the significant business sectors in Thailand. To utilize this useful cloud corpus for the business improvement process, we propose a novel methodology for process monitoring using the concept of multidimensional sentiment cube (MDSC) mining to raise usefulness with the business process model notation (BPMN). As the ability of MDC raise unlimited analysis perspectives merge with sentiment analysis (MDSC), this method can provide more sets of data for association rules mining and meet the needs to be analyzed. The cube analysis scenario, which uses association rules mining results, can reveal a significant hidden issue among aspects and sub-aspects associated under our design with their measurements. The results can be used for monitoring, which presents the customer's sentiment from social media in the real business case and identifying in the real process model. HIGHLIGHTS A methodology for process monitoring using the concept of multidimensional sentiment cube (MDSC) mining raise the usefulness of the business process model notation (BPMN) by utilizing the corpus for the business improvement process This method can provide more sets of data for association rules mining as the ability of MDC raise unlimited analysis perspectives to merge with sentiment analysis (MDSC) The results can monitor the customer’s sentiment from social media in the real business case and identify in the real process model GRAPHICAL ABSTRACT
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13

Dhifaoui, Zouhaier, and Jean-Marc Bardet. "Local correlation dimension of multidimensional stochastic process." Statistics & Probability Letters 181 (February 2022): 109262. http://dx.doi.org/10.1016/j.spl.2021.109262.

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14

Dies, Robert R. "A Multidimensional Model for Group Process Research." Small Group Behavior 16, no. 4 (November 1985): 427–46. http://dx.doi.org/10.1177/104649648501600401.

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15

Morris, Jessica F. "Lesbian Coming Out as a Multidimensional Process." Journal of Homosexuality 33, no. 2 (June 5, 1997): 1–22. http://dx.doi.org/10.1300/j082v33n02_01.

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16

Pichlak, Magdalena. "The innovation adoption process: A multidimensional approach." Journal of Management & Organization 22, no. 4 (December 1, 2015): 476–94. http://dx.doi.org/10.1017/jmo.2015.52.

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AbstractThe study analyses the broad sets of factors that influence the innovation adoption process in the environmental, organizational, top managers,’ innovation and user acceptance context. The innovation adoption process is presented as a sequence of stages, progressing from initiation through adoption decision to implementation of an innovation and it is considered at the organizational level. The Delphi survey conducted among 264 experts of a diverse professional and academic experience allowed examining the perceived significance of each factor for the various stages of the innovation adoption process. The results of the analysis show that the considered factors do not affect the innovation adoption process with the same strength but exert varying levels of influence on the subsequent stages. The study discusses the implications of these findings and suggests ideas for future research.
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17

Li, Song. "Multidimensional Aggregation Process in Cloud Computing System." International Journal of Grid and Distributed Computing 7, no. 5 (October 31, 2014): 1–14. http://dx.doi.org/10.14257/ijgdc.2014.7.5.01.

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18

Pohl, Christian, Julie Thompson Klein, Sabine Hoffmann, Cynthia Mitchell, and Dena Fam. "Conceptualising transdisciplinary integration as a multidimensional interactive process." Environmental Science & Policy 118 (April 2021): 18–26. http://dx.doi.org/10.1016/j.envsci.2020.12.005.

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19

NAKAKITA, Kiyomi, Makoto NAGAOKA, and Katsuyuki OHSAWA. "Multidimensional simulation of the diesel soot formation process." Transactions of the Japan Society of Mechanical Engineers Series B 56, no. 521 (1990): 221–26. http://dx.doi.org/10.1299/kikaib.56.221.

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20

Matysiak, Wojciech, and Marcin Świeca. "Zonal polynomials and a multidimensional quantum Bessel process." Stochastic Processes and their Applications 125, no. 9 (September 2015): 3430–57. http://dx.doi.org/10.1016/j.spa.2015.05.004.

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21

Ouali, Sonya, Mohamed Mhiri, and Lotfi Bouzguenda. "A Multidimensional Knowledge Model for Business Process Modeling." Procedia Computer Science 96 (2016): 654–63. http://dx.doi.org/10.1016/j.procs.2016.08.247.

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22

Thornhill, Nina F., Hallgeir Melbø, and Jan Wiik. "Multidimensional Visualization and Clustering of Historical Process Data." Industrial & Engineering Chemistry Research 45, no. 17 (August 2006): 5971–85. http://dx.doi.org/10.1021/ie051054q.

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23

Cox, Trevor F. "Multidimensional scaling used in multivariate statistical process control." Journal of Applied Statistics 28, no. 3-4 (March 2001): 365–78. http://dx.doi.org/10.1080/02664760120034108.

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24

Andjel, Enrique D. "Survival of multidimensional contact process in random environments." Boletim da Sociedade Brasileira de Matemática 23, no. 1-2 (March 1992): 109–19. http://dx.doi.org/10.1007/bf02584814.

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25

Hayes, Steven C., and Brandon T. Sanford. "Modern psychotherapy as a multidimensional multilevel evolutionary process." Current Opinion in Psychology 2 (April 2015): 16–20. http://dx.doi.org/10.1016/j.copsyc.2015.01.009.

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26

Kwon, Kibum, Jae Young Lee, Jong Gyu Park, and Aileen Guerrero Zaballero. "Process Consultation Within and Across Cultures." Journal of Applied Behavioral Science 56, no. 3 (January 10, 2020): 322–46. http://dx.doi.org/10.1177/0021886319896359.

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The purpose of this study is to consider how process consultants can effectively manage challenges both within and across cultures. This study investigates the multidimensional aspects of process consultation for workgroups that consist of diverse individuals in postmodern organizations. A proposed conceptual framework is developed to include factors that are useful for process consultants to consider when working in multicultural contexts. The micro-multicultural framework integrates the cultural mosaic with Schein’s ORJI (Observation, Reaction, Judgment, and Intervention) cycle. The framework represents the multidimensional aspects of cultural identities and explores verbal and nonverbal communication patterns during process consultation. A checklist for micro-multicultural process consultation is also proposed to demonstrate how a process consultant can perform his or her primary role comprehensively while considering process consultation as group-level phenomena.
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27

Lupenko, Serhii, and Roman Butsiy. "Isomorphic Multidimensional Structures of the Cyclic Random Process in Problems of Modeling Cyclic Signals with Regular and Irregular Rhythms." Fractal and Fractional 8, no. 4 (March 30, 2024): 203. http://dx.doi.org/10.3390/fractalfract8040203.

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This paper is devoted to the research of the isomorphic multidimensional cyclic structure and multidimensional phase structure of the cyclic random process (CRP) and to its formation method, which enables a rigorous formalization of intuitive ideas concerning cyclic stochastic motion. The fundamental properties of the cyclic random process and analytical dependencies between the multidimensional cyclic structure, multidimensional phase structure and rhythm structure of the CRP have been established. This work shows that the CRP is able to take into account the cyclicity of multidimensional distribution functions of cyclic signals as well as the variability in the rhythm of the investigated signals. A subclass of the CRP is the periodic random process, which allows for the use of classical processing methods of cyclic signals with a regular rhythm. Based on a series of experiments, significant advantages of the CRP as a mathematical model of electrocardiographic signals (ECG) compared to the periodic random process are shown.
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28

Mountford, T. S. "A Metastable Result for the Finite Multidimensional Contact Process." Canadian Mathematical Bulletin 36, no. 2 (June 1, 1993): 216–26. http://dx.doi.org/10.4153/cmb-1993-031-3.

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AbstractWe prove that for a contact process restricted to the cube [1,n]d and initially fully occupied, the time to die out, when it is suitably normalized, converges to an exponential random variable as n tends to infinity.
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29

Ali, Mohammad. "Stakeholder Recognition and Prioritization: A Dynamic and Multidimensional Process." Academy of Management Proceedings 2018, no. 1 (August 2018): 12264. http://dx.doi.org/10.5465/ambpp.2018.12264abstract.

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30

Lutov, A. G., and A. R. Ishkulova. "Automated System the Extreme Multidimensional Management of Process Plating." MEHATRONIKA, AVTOMATIZACIA, UPRAVLENIE 18, no. 3 (March 13, 2017): 185–91. http://dx.doi.org/10.17587/mau.18.185-191.

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31

Schmisser, Emeline. "Penalized nonparametric drift estimation for a multidimensional diffusion process." Statistics 47, no. 1 (February 2013): 61–84. http://dx.doi.org/10.1080/02331888.2011.591931.

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32

Simonton, Dean Keith. "Talent Development as a Multidimensional, Multiplicative, and Dynamic Process." Current Directions in Psychological Science 10, no. 2 (April 2001): 39–43. http://dx.doi.org/10.1111/1467-8721.00110.

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33

Judson, Marc A. "Determining the cause of pulmonary granulomas: A multidimensional process." Respirology 20, no. 1 (November 17, 2014): 5–6. http://dx.doi.org/10.1111/resp.12433.

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34

McConnell, J. Russell, Kathy P. Barton, Mark A. LaPack, and Mike A. DesJardin. "Streamlining Process R&D Using Multidimensional Analytical Technology." Organic Process Research & Development 6, no. 5 (September 2002): 700–705. http://dx.doi.org/10.1021/op0255332.

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35

Chan, K. K., and T. A. Spedding. "An integrated multidimensional process improvement methodology for manufacturing systems." Computers & Industrial Engineering 44, no. 4 (April 2003): 673–93. http://dx.doi.org/10.1016/s0360-8352(03)00002-0.

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36

Polaski, Arlene Lacey, Susan kalkhof Vitron, Brenda J. Carrier, and Dorothy Stano Carlson. "A MULTIDIMENSIONAL TEACHING-LEARNING STRATEGY FOR THE NURSING PROCESS." Nurse Educator 13, no. 4 (July 1988): 19–23. http://dx.doi.org/10.1097/00006223-198807000-00011.

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37

Kyriakidis, E. G., and A. Pavitsos. "Optimal intervention policies for a multidimensional simple epidemic process." Mathematical and Computer Modelling 50, no. 9-10 (November 2009): 1318–24. http://dx.doi.org/10.1016/j.mcm.2009.06.012.

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38

Bloznelis, M. "Distribution of the norm of a multidimensional Wiener process." Lithuanian Mathematical Journal 30, no. 4 (1991): 296–302. http://dx.doi.org/10.1007/bf00970825.

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39

Dharmadhikari, Shailaja. "Maximum likelihood estimation for birth and multidimensional Brownian process." Journal of Multivariate Analysis 23, no. 2 (December 1987): 220–32. http://dx.doi.org/10.1016/0047-259x(87)90154-0.

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40

Dannefer, Dale, and Marion Perlmutter. "Development as a Multidimensional Process: Individual and Social Constituents." Human Development 33, no. 2-3 (1990): 108–37. http://dx.doi.org/10.1159/000276506.

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41

Tang, Xueying, Zhi Wang, Qiwei He, Jingchen Liu, and Zhiliang Ying. "Latent Feature Extraction for Process Data via Multidimensional Scaling." Psychometrika 85, no. 2 (June 2020): 378–97. http://dx.doi.org/10.1007/s11336-020-09708-3.

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42

Elistratova, Ksenia. "Innovative Educational Process at School as a Multidimensional Phenomenon." Man and Education, no. 4 (73) (2022): 53. http://dx.doi.org/10.54884/s181570410023686-9.

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Questions are raised about the connection and interdependence of the phenomena of multidimensionality, cross-dimensionality and multi-mediumship in the innovative educational process of a modern school. The relevance and directions of application of the principle of multidimensionality in the management of the school and the educational process, the mechanisms of evaluation and management of the quality of the educational process, the quality of teacher activity, the quality of educational results are discussed. The possibilities and potential of the implementation of this principle are revealed in relation to the management of professional and personal development of a teacher, the formation and use of a model of education of a student, a school graduate. Particular importance in the article is given to the issues of multidimensional representation of educational results and effects of the educational process, the representation of the education of the student and the graduate of the school from the standpoint of not only the normatively established system of subject, meta-subject and personal results, three key components of functional literacy (mathematical, reading, natural science), but also the so-called skills of the XXI century, soft skills, cross-cutting competencies. A separate place is given to the disclosure of the concept of "cross-cutting competencies", the presentation of the author's classification of cross-cutting competencies.
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43

Mayr, Thomas, Marco F. Huber, Ralph Hensel, and Mathias Keil. "Process Optimization in Process Planning using a Multidimensional Approach in the Automotive Assembly." Procedia CIRP 126 (2024): 751–56. http://dx.doi.org/10.1016/j.procir.2024.08.303.

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44

Liddle, Howard A. "Multidimensional Family Therapy." SUCHT 56, no. 1 (February 2010): 43–50. http://dx.doi.org/10.1024/0939-5911/a000011.

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Background: Multidimensional family therapy is the most researched family based intervention for adolescent substance abuse. Research and coverage: Funded continuously since 1985 in a series of controlled trials, process studies, economic analyses, and implementation studies, MDFT has achieved positive outcomes at post treatment and at various follow-up periods at one year and beyond when compared to a variety of active treatments, including cognitive behavior therapy, group counseling, multifamily groups, as well as in comparisons against services as usual. MDFT is a treatment system rather than a one size fits all model, having been adapted for testing and implementation in a variety of U.S. locations and in a multinational controlled trial in Europe over the past 5 years (Berlin, Paris, Brussels, The Hague, and Geneva). Studies have tested MDFT in juvenile justice settings such as drug courts, detention centers, residential treatment, as well as in outpatient treatment offered in drug and juvenile justice outpatient settings.
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45

Guswanto, Bambang Hendriya. "A MULTIDIMENSIONAL SUBDIFFUSION MODEL WITH CHEMOTAXIS." Jurnal Ilmiah Matematika dan Pendidikan Matematika 11, no. 2 (December 27, 2019): 1. http://dx.doi.org/10.20884/1.jmp.2019.11.2.2259.

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The mathematical model for subdiffusion process with chemotaxis proposed by Langlands and Henry [1] for the one-dimensional case is extended to the multi-dimensional case. The model is derived from random walks process using a probability measure on a n-multidimensional unit ball $S^{n-1}$.
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46

Aldashev, Serik. "The Tricomi Problem for a Class of Multidimensional Mixed Hyperbolic-Parabolic Equations." Mathematical Physics and Computer Simulation, no. 2 (August 2022): 5–16. http://dx.doi.org/10.15688/mpcm.jvolsu.2022.2.1.

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It is known that in the mathematical modeling of electromagnetic fields in space, the nature of the electromagnetic process is determined by the properties of the medium. If the medium is non-conducting, we obtain degenerate multidimensional hyperbolic equations. If the medium has a high conductivity, then we come to degenerate multidimensional parabolic equations. Consequently, the analysis of electromagnetic fields in complex media (for example, if the conductivity of the medium changes) is reduced to degenerate multidimensional hyperbolic-parabolic equations. It is also known that the oscillations of elastic membranes in space can be modeled according to the Hamilton principle by degenerate multidimensional hyperbolic equations. The study of the process of heat propagation in a medium filled with mass leads to degenerate multidimensional parabolic equations. Therefore, by studying the mathematical modeling of the heat propagation process in oscillating elastic membranes, we also arrive at degenerate multidimensional hyperbolic-parabolic equations. When studying these applications, it becomes necessary to obtain an explicit representation of the solutions to the problems under study. Boundary value problems for hyperbolicparabolic equations on the plane are well studied, and their multidimensional analogues are little studied. The Tricomi problem for these equations was previously investigated. As far as we know, this problem has not been studied in space. In this paper, the Tricomi problem is shown to be ambiguously solvable for a class of multidimensional mixed hyperbolic-parabolic equations.
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47

Aldashev, C. A., and E. Kazez. "CORRECTNESS OF THE MIXED PROBLEM FOR ONE CLASS OF DEGENERATE MULTIDIMENSIONAL HYPERBOLO-PARABOLIC EQUATIONS." SERIES PHYSICO-MATHEMATICAL 6, no. 334 (December 15, 2020): 27–35. http://dx.doi.org/10.32014/2020.2518-1726.94.

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It is known that in mathematical modeling of electromagnetic fields in space, the nature of the electromagnetic process is determined by the properties of the medium. If the medium is non-conductive, we get degenerate multi-dimensional hyperbolic equations. If the medium has a high conductivity, then we go to degenerate multidimensional parabolic equations. Consequently, the analysis of electromagnetic fields in complex media (for example, if the conductivity of the medium changes) reduces to degenerate multidimensional hyperbolic-parabolic equations. Also, it is known that the oscillations of elastic membranes in space according to the Hamilton principle can be modeled by degenerating multidimensional hyperbolic equations. Studying the process of heat propagation in a medium filled with mass leads to degenerate multidimensional parabolic equations. Consequently, by studying the mathematical modeling of the process of heat propagation in oscillating elastic membranes, we also come to degenerate multidimensional hyperbolic-parabolic equations. When studying these applications, it is necessary to obtain an explicit representation of the solutions of the studied problems. The mixed problem for degenerate multidimensional hyperbolic equations was previously considered. As far as is known, these questions for degenerate multidimensional hyperbolic-parabolic equations have not been studied. In this paper, unique solvability is shown and an explicit form of the classical solution of the mixed problem for one class of degenerate multidimensional hyperbolic-parabolic equations is obtained.
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48

Elistratova, K. "Ecosystem of School Education Quality." Profession-Oriented School 11, no. 3 (July 22, 2023): 44–49. http://dx.doi.org/10.12737/1998-0744-2023-11-3-44-49.

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The article analyzes the concepts of «ecosystem» and «ecosystem approach», their evolution in the field of business, economics, education, the possibility of using the potential of the ecosystem approach in relation to the design and organization of the educational process at school as a cross-multidimensional phenomenon. A detailed interpretation of the methodology of the cross-multidimensional educational process in a secondary school as a result of interaction and intersection of various spaces and environments is given. The article also presents and discusses the results of a survey of teaching staff of secondary schools in St. Petersburg and the Leningrad region on the formation and development of the ecosystem of a cross-multidimensional educational process at school. On the basis of theoretical and experimental studies, generalizing conclusions are formulated, prospects for further study of the phenomenon of «ecosystem of the cross-multidimensional educational process in school» are determined.
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49

Tambouris, Efthimios. "Multidimensional Open Government Data." JeDEM - eJournal of eDemocracy and Open Government 8, no. 3 (December 19, 2016): 1–11. http://dx.doi.org/10.29379/jedem.v8i3.444.

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A large number of open government data concerns official and unofficial statistics. These data can be represented as multidimensional data. In this paper, we commence by presenting data fragmentation, an important challenge when exploiting open data. We thereafter introduce multidimensional data as a possible solution to overcome data fragmentation. More specifically, we outline the data cube model and linked open data technologies. In addition, we present a process for multidimensional linked open data publication and reuse. We also present a number of software tools that have been developed to manage multidimensional linked open data. We finally summarize the benefits and some of the main barriers.
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50

Helal, Diogo Henrique, Cleverson Vasconcelos da Nóbrega, and Tatiana Aguiar Porfírio de Lima. "Retirement and organizations: perspectives and challenges for both workers and human resource management." Working with Older People 25, no. 2 (March 4, 2021): 141–52. http://dx.doi.org/10.1108/wwop-04-2020-0014.

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Purpose This paper aims to reflect on retirement, showing its different viewpoints, advocating the need to understand the issue from a procedural and multidimensional perspective, and especially, defending a more active role of human resource management in the process. Design/methodology/approach This paper presents a theoretical framework of retirement, based on a procedural and multidimensional perspective. Findings To study how individuals adapt to retirement permits the discovery, for example, of how they obtain the quality of life after the transition and how they manage the internal and external aspects of the process. Human resource management must treat retirement as a complex and multidimensional phenomenon. This means it should consider retirement not only as a decision but also as a process. Originality/value This essay seeks to reflect on retirement, advocating the need to understand the issue from a procedural and multidimensional perspective, and especially, defending a more active role of human resource management in the process.
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