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A Transdisciplinary Approach to Enhancing Online Engineering Education Through Learning Analytics Masikini Lugoma , Lethuxolo Yende , Pule Dikgwatlhe , Akhona Mkonde , Rorisang Thage , Lucky Maseko , Ngonidzashe Chimwani (pages: 1-6) AI Disruptions in Higher Education: Evolutionary Change, Not Revolutionary Overthrow Cristo Leon , James Lipuma , Maximus Rafla (pages: 7-18) Education, Research, and Methodology: A Transdisciplinary Cybernetic Whole Nagib Callaos , Cristo Leon (pages: 19-33) Enhancing Educational Effectiveness Through Transdisciplinary Practice: The ETCOP Model Birgit Oberer , Alptekin Erkollar , Andreas Kropfberger (pages: 34-40) From Instruction to Interaction: Reflexive Learning Design for Cross-Generational Engagement at the Workplace Gita Aulia Nurani , Ya-Hui Lee (pages: 41-44) GIS in Aquatic Animal Health Surveillance: A Transdisciplinary eLearning Initiative Integrating Education, Research, and Methodology (The Aquae Strength Project) Eleonora Franzago , Rodrigo Macario , Matteo Mazzucato , Federica Sbettega , Manuela Cassani , Guido Ricaldi , Francesco Bissoli , Anna Nadin , Fabrizio Personeni , Manuela Dalla Pozza , Grazia Manca , Nicola Ferré (pages: 45-50) Reflexivity as a Compass: The European AI Act and Its Implications for U.S. Higher Education Institutions Jasmin Cowin (pages: 51-56) Required General Education Program Evaluation: Bridging the Gap Between Educators and Administrators James Lipuma , Cristo Leon , Jeremy Reich (pages: 57-61) Researching Ourselves Jeremy Horne (pages: 62-72) The Self-Aware, Reflective Learner: Fostering Metacognitive Awareness and Reflexivity in Undergraduates Through Service-Learning Genejane Adarlo (pages: 73-81)
ABSTRACT
Selection of the Most Indicative Wavelets for the Multiresolution of the Vowels
The paper describes one approach of the selection of the most indicative wavelets for each of the vowels in the author’s native language. Analysis is performed on the correct and incorrect vowels. On each of the sample multiresolution decomposition is applied. For each of the detail and approximation the most indicative wavelet is selected using value of the variance as the criteria. Some interesting results are obtained and biorthogonal wavelets have been select as the most appropriate for the multiresolution of the vowels. Using this criterion, any further analysis of the samples can be done using only coefficients of the discrete wavelet transformation on the level of approximation or any level of the detail, with enough guarantees that they are most appropriate for each vowel.
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