Facial recognition technology has gained immense popularity in recent years due to its applications in security, authentication, and personalized user experiences. Traditional facial recognition systems primarily rely on supervised learning techniques to classify and recognize faces based on labeled datasets. However, reinforcement learning (RL), a machine learning paradigm focused on training models through interactions and feedback from the environment, presents a new approach to enhance the adaptability and performance of facial recognition systems. This paper explores the implementation of facial recognition (...) using reinforcement learning, focusing on the advantages RL offers in terms of continuous learning and real-time adaptation. By utilizing an RL agent to improve the feature extraction and classification process, the proposed method dynamically adapts to changing environmental conditions and new facial data, providing more robust recognition capabilities. This paper provides a comprehensive discussion of the proposed model, its architecture, and experimental results. (shrink)

Customer retention is a significant issue and one of the most pressing issues for big businesses. Companies are working to create methods to anticipate future customer churn since it has such a direct impact on their revenues, particularly in the telecom industry. As a result, identifying factors that contribute to customer turnover is critical in order to take the required steps to minimise churn. Our work's primary contribution is the development of a churn prediction model that helps telecom carriers forecast (...) which customers are most likely to churn. The model created in this paper employs machine learning methods on a large data platform to provide a novel approach to feature engineering and selection. This study also established churn variables that are critical in identifying the underlying causes of churn in order to evaluate the model's success. CRM may increase productivity, suggest appropriate promotions to a group of probable churn customers based on similar behaviour patterns, and vastly improve the company's marketing efforts by understanding the major churn causes from customer data. The accuracy, precision, recall, f-measure, and receiving operating characteristics (ROC) area of the suggested churn prediction model are all assessed. Furthermore, via the rules produced by the attribute-selected classifier algorithm, it offers reasons behind the churning of churn consumers. (shrink)

Observational learning can enhance the acquisition and performance quality of complex motor skills. While an extensive body of research has focused on the benefits of synchronous (i.e., concurrent physical practice) and non-synchronous (i.e., delayed physical practice) observational learning strategies, the question remains as to whether these approaches differentially influence performance outcomes. Accordingly, we investigate the differential outcomes of synchronous and non-synchronous observational training contexts using a novel dance sequence. Using multidimensional cross-recurrence quantification analysis, movement time-series were recorded for novice dancers (...) who either synchronised with (n = 22) or observed and then imitated (n = 20) an expert dancer. Participants performed a 16-count choreographed dance sequence for 20 trials assisted by the expert, followed by one final, unassisted performance trial. Although end-state performance did not significantly differ between synchronous and non-synchronous learners, a significant decline in performance quality from imitation to independent replication was shown for synchronous learners. A non-significant positive trend in performance accuracy was shown for non-synchronous learners. For all participants, better imitative performance across training trials led to better end-state performance, but only for the accuracy (and not timing) of movement reproduction. Collectively, the results suggest that synchronous learners came to rely on a realtime mapping process between visual input from the expert and their own visual and proprioceptive intrinsic feedback, to the detriment of learning. Thus, the act of synchronising alone does not ensure an appropriate training context for advanced sequence learning. (shrink)

Dr. Amrit Kaur Raina, a renowned educationist, was a profound scholar of Sikhism. Having served as an educationist and administrator for over forty years at various prestigious educational institutions in India, she had also established herself as an eminent writer in the field of a comparative study of religions. Through her literary essays, as published in several reputed research journals, magazines, books, and newspapers, she had been able to create an indelible mark of scholarship on the minds of her readers. (...) Inspired by the writings of the Sikh Gurus and her father, Prof. Harnam Das, she devoted her life to disseminating the Sikh Gurus' educational philosophy and Gurmat among the masses. Being a prolific writer, with thirty-one books to her credit, in the diverse fields of education, religion, Punjabi, and Hindi literature, she had been honoured with the Shiromani Punjabi Sahityakar award (2006) and Haryana Gaurav Puraskar in Punjabi (2016) by Government of Haryana. A votary of honest living, Dr. Amrit Kaur Raina led a life dedicated to the love of God and selfless service to society. She was a true karam yogi who had devoted her whole life to spread the message of education, Gurmat, and service to all. She had been honored for her services to the Sikh cause, by several Sikh organizations, including SGPC, Amritsar; Guru Gobind Singh Foundation, Ludhiana; Sukhmani Society, Amritsar; Shaheed Memorial International Sewa Society, Ludhiana; S. D. College, Ambala Cantt; and Gurmat College, Patiala, etc. Dr. Amrit Kaur Raina often asserted that Sikh Gurus' educational philosophy, their Sikhi ethics, their compositions, and Sri Guru Granth Sahib as a whole are the substance that makes for spirituality befitting the 21st century. Her views on various aspects of Sikh Gurus' Educational Philosophy are presented here for the benefit of readers:. (shrink)