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158 results on '"Chaturvedi, Amrita"'

3. Machine Learning for Sensor-Based Handwritten Character Recognition: A Brief Survey

Author

Singh, Shashank Kumar, Chaturvedi, Amrita, Goos, Gerhard, Series Editor, Hartmanis, Juris, Founding Editor, van Leeuwen, Jan, Series Editor, Hutchison, David, Editorial Board Member, Kanade, Takeo, Editorial Board Member, Kittler, Josef, Editorial Board Member, Kleinberg, Jon M., Editorial Board Member, Kobsa, Alfred, Series Editor, Mattern, Friedemann, Editorial Board Member, Mitchell, John C., Editorial Board Member, Naor, Moni, Editorial Board Member, Nierstrasz, Oscar, Series Editor, Pandu Rangan, C., Editorial Board Member, Sudan, Madhu, Series Editor, Terzopoulos, Demetri, Editorial Board Member, Tygar, Doug, Editorial Board Member, Weikum, Gerhard, Series Editor, Vardi, Moshe Y, Series Editor, Bertino, Elisa, Editorial Board Member, Gao, Wen, Editorial Board Member, Steffen, Bernhard, Editorial Board Member, Yung, Moti, Editorial Board Member, Woeginger, Gerhard, Editorial Board Member, Bramas, Quentin, editor, Chatterjee, Bapi, editor, Devismes, Stéphane, editor, Egan, Malcolm, editor, Mandal, Partha Sarathi, editor, Mukhopadhyaya, Krishnendu, editor, and Saradhi, V. Vijaya, editor

Published
2025
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6. Integrating Flourishing within PDS Partnerships to Support Students' Mental Health and Wellbeing

Author

Larson, Kristine E., Savick, Stephanie, Segree, Tara, Buchanan, Mable, and Chaturvedi, Amrita

Abstract

Considering the critical need to support students' mental health and wellbeing, this article outlines a standards-based approach that integrates flourishing within a high school English/Language Arts classroom and supports clinical practice and professional development in a professional development school (PDS). Using the book, "The Bean Trees," the university liaison, mentor teacher, and intern worked together to co-teach a lesson that integrated flourishing, while also meeting curricular objectives. Moreover, the university liaison and mentor teacher used a gradual release model to support the student intern's clinical practice. Lastly, the three stakeholders reflected on their clinical and professional learning. Implications for integrating flourishing in content areas to support students' mental health and wellbeing through university-school partnerships are discussed.

Published
2022

7. Ensemble Models for Vulnerability Prediction Using Code Metrics

Author

Tiwari, Purushottam, Murlidhar, Zope Sumedh, Chaturvedi, Amrita, Singh, Shashank Kumar, Kacprzyk, Janusz, Series Editor, Gomide, Fernando, Advisory Editor, Kaynak, Okyay, Advisory Editor, Liu, Derong, Advisory Editor, Pedrycz, Witold, Advisory Editor, Polycarpou, Marios M., Advisory Editor, Rudas, Imre J., Advisory Editor, Wang, Jun, Advisory Editor, Kumar, Rajesh, editor, Verma, Ajit Kumar, editor, Verma, Om Prakash, editor, and Wadehra, Tanu, editor

Published
2024
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9. Applying Machine Learning for American Sign Language Recognition: A Brief Survey

Author

Singh, Shashank Kumar, Chaturvedi, Amrita, Kacprzyk, Janusz, Series Editor, Gomide, Fernando, Advisory Editor, Kaynak, Okyay, Advisory Editor, Liu, Derong, Advisory Editor, Pedrycz, Witold, Advisory Editor, Polycarpou, Marios M., Advisory Editor, Rudas, Imre J., Advisory Editor, Wang, Jun, Advisory Editor, Sharma, Harish, editor, Shrivastava, Vivek, editor, Bharti, Kusum Kumari, editor, and Wang, Lipo, editor

Published
2023
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11. A Multiclass EEG Signal Classification Model Using Channel Interaction Maximization and Multivariate Empirical Mode Decomposition

Author

Jha, Pankaj Kumar, Tiwari, Anurag, Chaturvedi, Amrita, Goos, Gerhard, Founding Editor, Hartmanis, Juris, Founding Editor, Bertino, Elisa, Editorial Board Member, Gao, Wen, Editorial Board Member, Steffen, Bernhard, Editorial Board Member, Yung, Moti, Editorial Board Member, Tanveer, Mohammad, editor, Agarwal, Sonali, editor, Ozawa, Seiichi, editor, Ekbal, Asif, editor, and Jatowt, Adam, editor

Published
2023
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13. Software Fault Prediction Using Data Mining Techniques on Software Metrics

Author

Kumar, Rakesh, Chaturvedi, Amrita, Kacprzyk, Janusz, Series Editor, Gomide, Fernando, Advisory Editor, Kaynak, Okyay, Advisory Editor, Liu, Derong, Advisory Editor, Pedrycz, Witold, Advisory Editor, Polycarpou, Marios M., Advisory Editor, Rudas, Imre J., Advisory Editor, Wang, Jun, Advisory Editor, Misra, Rajiv, editor, Shyamasundar, Rudrapatna K., editor, Chaturvedi, Amrita, editor, and Omer, Rana, editor

Published
2022
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14. Applying Extreme Gradient Boosting for Surface EMG Based Sign Language Recognition

Author

Singh, Shashank Kumar, Chaturvedi, Amrita, Prakash, Alok, Kacprzyk, Janusz, Series Editor, Gomide, Fernando, Advisory Editor, Kaynak, Okyay, Advisory Editor, Liu, Derong, Advisory Editor, Pedrycz, Witold, Advisory Editor, Polycarpou, Marios M., Advisory Editor, Rudas, Imre J., Advisory Editor, Wang, Jun, Advisory Editor, Misra, Rajiv, editor, Shyamasundar, Rudrapatna K., editor, Chaturvedi, Amrita, editor, and Omer, Rana, editor

Published
2022
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25. The Impact of In-Class Breathing Exercises on Student Mental Health in a General Chemistry 1 Lecture: A Mixed Method Analysis

Author

Korfiatis, Alex, Chaturvedi, Amrita, Tennison, Jen, and Alagic, Asmira

Abstract

This study investigates the implementation and outcomes of a mindfulness-based intervention, specifically focused on breathing exercises, within a chemistry classroom setting. Amidst the backdrop of widespread stress, anxiety, and depression among college students─intensified by the challenges of the COVID-19 pandemic─this study presents a targeted in-class approach to enhance mental health. The intervention, integrated into a General Chemistry 1 course, screened for baseline anxiety and mindfulness and aimed to address the high levels of stress particularly prevalent among first-time college students. Through a mixed-methods analysis, the study engaged students in a semester-long 5 min breathing intervention, evaluating its effects on their levels of anxiety and mindfulness via interviews and pre–post-intervention assessments using the GAD-7 (General Anxiety Disorder-7) scale and MAAS (Mindfulness Attention Awareness Scale). Quantitative findings revealed notable high baseline levels of anxiety in students, and qualitative analysis of semistructured interviews highlighted the intervention’s role in fostering a sense of calmness, focus, and reduction of anxiety, contributing to a more conducive learning environment. Data show that severe anxiety levels increased by 10% while mindfulness decreased by 3% at the end of the semester.

Published
2025
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27. Ontology-Driven Framework to Automatically Generate University Timetable

Author

Bajpai, Shruti, Chaturvedi, Amrita, Kacprzyk, Janusz, Series Editor, Gomide, Fernando, Advisory Editor, Kaynak, Okyay, Advisory Editor, Liu, Derong, Advisory Editor, Pedrycz, Witold, Advisory Editor, Polycarpou, Marios M., Advisory Editor, Rudas, Imre J., Advisory Editor, Wang, Jun, Advisory Editor, Bansal, Jagdish Chand, editor, Gupta, Mukesh Kumar, editor, Sharma, Harish, editor, and Agarwal, Basant, editor

Published
2020
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28. Applying Deep Learning for Discovery and Analysis of Software Vulnerabilities: A Brief Survey

Author

Singh, Shashank Kumar, Chaturvedi, Amrita, Kacprzyk, Janusz, Series Editor, Pal, Nikhil R., Advisory Editor, Bello Perez, Rafael, Advisory Editor, Corchado, Emilio S., Advisory Editor, Hagras, Hani, Advisory Editor, Kóczy, László T., Advisory Editor, Kreinovich, Vladik, Advisory Editor, Lin, Chin-Teng, Advisory Editor, Lu, Jie, Advisory Editor, Melin, Patricia, Advisory Editor, Nedjah, Nadia, Advisory Editor, Nguyen, Ngoc Thanh, Advisory Editor, Wang, Jun, Advisory Editor, Pant, Millie, editor, Kumar Sharma, Tarun, editor, Arya, Rajeev, editor, Sahana, B.C., editor, and Zolfagharinia, Hossein, editor

Published
2020
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29. Obsessive Compulsive Disorder: What an Educator Needs to Know

Author

Chaturvedi, Amrita, Murdick, Nikki L., and Gartin, Barbara C.

Abstract

The presence of obsessive compulsive disorder (OCD) impairs social, emotional and academic functioning. Individuals with OCD may have co-morbid disorders including attention deficit hyperactivity disorder, depression, oppositional defiant disorder, or Tourette syndrome. Challenges occur when students with OCD become a part of the general education classroom. This article provides an overview of OCD and presents information to assist teachers and school staff to successfully meet the needs of students with OCD.

Published
2014

30. Tourette Syndrome: Classroom Implications

Author

Chaturvedi, Amrita, Gartin, Barbara C., and Murdick, Nikki L.

Abstract

Tourette Syndrome (TS) is a neurobiological disorder characterized by various involuntary motor movements and vocal tics. Symptoms of TS emerge between the ages of 3 to 8 years old, are most severe when an individual reaches puberty, and decrease by the time a person is 20 years old. Additionally, persons with TS may have secondary disabilities of obsessive-compulsive disorder, attention deficit hyperactivity, and/or learning disabilities. Challenges occur when students with TS or with TS plus secondary disabilities become members of the general education classroom. This article provides information to assist teachers and staff in the general education setting to successfully include the child with TS. (Contains 3 tables.)

Published
2011

33. Large-Scale Meta-Analysis of Genes Encoding Pattern in Wilson’s Disease

Author

Misra, Diganta, Tiwari, Anurag, Chaturvedi, Amrita, Kacprzyk, Janusz, Series Editor, Pal, Nikhil R., Advisory Editor, Bello Perez, Rafael, Advisory Editor, Corchado, Emilio S., Advisory Editor, Hagras, Hani, Advisory Editor, Kóczy, László T., Advisory Editor, Kreinovich, Vladik, Advisory Editor, Lin, Chin-Teng, Advisory Editor, Lu, Jie, Advisory Editor, Melin, Patricia, Advisory Editor, Nedjah, Nadia, Advisory Editor, Nguyen, Ngoc Thanh, Advisory Editor, Wang, Jun, Advisory Editor, Bhatia, Sanjiv K., editor, Tiwari, Shailesh, editor, Mishra, Krishn K., editor, and Trivedi, Munesh C., editor

Published
2019
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35. Ontology-Driven Shopping Cart and Its Comparative Analysis

Author

Vardhan, Aditya, Chaturvedi, Amrita, Barbosa, Simone Diniz Junqueira, Series editor, Chen, Phoebe, Series editor, Filipe, Joaquim, Series editor, Kotenko, Igor, Series editor, Sivalingam, Krishna M., Series editor, Washio, Takashi, Series editor, Yuan, Junsong, Series editor, Zhou, Lizhu, Series editor, Kaushik, Saroj, editor, Gupta, Daya, editor, Kharb, Latika, editor, and Chahal, Deepak, editor

Published
2017
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37. Using a contemplative practice intervention in teacher education courses to neutralize implicit racial bias: a feasibility study.

Author

Larson, Kristine E., Chaturvedi, Amrita, Dunn, Molly, and Chavers, Nora

Subjects
RACISM, IMPLICIT bias, TEACHER education, FEASIBILITY studies, RUMINATION (Cognition), RACIAL differences, IMPLICIT learning
Abstract

This study examined the preliminary impact of a contemplative practice intervention on the implicit racial biases of 22 participants enrolled in teacher preparation courses using a mixed-methods, pre/post-test design. Quantitative analyses determined whether there were statistically significant differences in implicit racial bias before and after the intervention, and qualitative data from participants' written reflections were used to understand participant experiences with the intervention. Results suggested that the intervention was associated with decreases in implicit racial bias. Moreover, participant reflections suggested preliminary social validity of the intervention. Taken together, the contemplative practice intervention used in this feasibility study is a promising approach to neutralize prospective and current teachers' implicit racial bias. [ABSTRACT FROM AUTHOR]

Published
2024
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40. Deep Learning

Author

Sinha, Amit, primary, Gupta, Suneet Kumar, additional, Tiwari, Anurag, additional, and Chaturvedi, Amrita, additional

Published
2019
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41. Ontology - Driven Observer Pattern

Author

Chaturvedi, Amrita, T.V., Prabhakar, Kacprzyk, Janusz, Series editor, Catania, Barbara, editor, Cerquitelli, Tania, editor, Chiusano, Silvia, editor, Guerrini, Giovanna, editor, Kämpf, Mirko, editor, Kemper, Alfons, editor, Novikov, Boris, editor, Palpanas, Themis, editor, Pokorný, Jaroslav, editor, and Vakali, Athena, editor

Published
2014
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43. Universal Design for Instruction for Students with Disabilities at the Postsecondary Level

Author

Chaturvedi, Amrita

Abstract

In recent years there has been a considerable increase in the number of students with disabilities enrolling for postsecondary education. However, graduation rates for students with disabilities have not been commensurate with their enrollment rate at postsecondary institutions. Some factors for low graduation rate among students with disabilities are lack of proper educational support and services, lack of academic skills and readiness, inadequate transitional support, and lack of awareness and knowledge among faculty regarding students with disabilities and the accommodations they need. One way to address the factors leading to low graduation rate is to incorporate the concept and principles of Universal Design for Instruction (UDI) in teaching practices at the postsecondary level. UDI is an educational approach that is inclusive in nature and affords equal opportunities to all students, including students with disabilities. The purpose of this mixed methods study was (i) to uncover the extent to which students with disabilities perceived that faculty members at University of Arkansas, Fayetteville (UFA) were incorporating the principles and practices of UDI while teaching (ii) to investigate the perception of faculty members at UAF regarding the extent of usage of principles and practices of UDI and (iii) to investigate the perception of students with disabilities regarding the teaching practices of instructors that can help them succeed in their classes at UAF. Surveys and semi-structured interviews were used to achieve the purpose of this study. The findings of the study showed that according to student report and faculty self-report faculty members were more likely to use certain principles of UDI as compared to other principles. The discipline, year of college, rank, gender and experience teaching students with disabilities had an effect on how respondents responded to certain survey items compared to other items. Results from semi-structured interviews showed that students with disabilities can benefit if principles of UDI are incorporated in teaching practices at the postsecondary level. [The dissertation citations contained here are published with the permission of ProQuest LLC. Further reproduction is prohibited without permission. Copies of dissertations may be obtained by Telephone (800) 1-800-521-0600. Web page: http://www.proquest.com/en-US/products/dissertations/individuals.shtml.]

Published
2010

47. A reliable and efficient machine learning pipeline for american sign language gesture recognition using EMG sensors.

Author

Singh, Shashank Kumar and Chaturvedi, Amrita

Subjects
AMERICAN Sign Language, MACHINE learning, SIGN language, RECOGNITION (Psychology), HUMAN-computer interaction, FEATURE selection
Abstract

Sign languages has extensive applications among differently-abled to communicate with their surroundings. With the development of different sensing technologies, several new human-computer interaction techniques (HCI) have been established to recognize hand gestures. Computer vision-based methods have shown significant utility for such applications. However, these methods are strongly dependent on the lighting conditions. The surface electromyography (sEMG) technique is invariant to lighting conditions and can easily reflect human motion intention. In this work, sEMG based sign language recognition model was developed using an efficient machine learning pipeline. Two sEMG datasets were recorded for predefined hand gestures using wireless sensors. These signals were mainly acquired against 24 manual alphabets (ASL-24) and ten digits(ASL-10) of American Sign Language (ASL). The collected data sets were preprocessed, and around 450 well-established feature was extracted from each sEMG channel. We applied an ensemble feature selection approach combining four diverse filter-based feature selection methods (ANOVA, Chi-square, Mutual Info, ReliefF). A newly proposed feature combiner that exploits feature–feature and feature–class correlation thresholds is used to combine feature subsets formed across the ensemble. The resulting features comprise reduced & most representative feature subsets and are further used in the pipeline for classifying ASL gestures. Using the CatBoost algorithm, the pipeline presented excellent average classification accuracy(99.91% on ASL-24) and other performance parameters for recognizing ASL gestures. The pipeline was also applied and validated on a benchmark dataset (Ninapro database 5, exercise A) and achieved similar outcomes. The result highlights the feasibility of using sEMG based approach as better options to computer-vision-based techniques to build an accurate and robust Sign Language Recognition system (SLRS). Moreover, efforts were made to find the optimal number of sensors and features for recognition task on (ASL-10 dataset) without impacting the overall reliability and accuracy of the system. The experiments results can be used to enhance the performance of various wearable sEMG sensor based HCI applications. [ABSTRACT FROM AUTHOR]

Published
2023
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