July 2024

Enhancing Well-Being: Embracing Aging, Alleviating Anxiety, and Reflecting on Mortality

Author(s): Sri Varthini, Maya Rathnasabapthy*
Volume: 5 Issue: 3 Pages: 172-182
DOI: https://doi.org/10.47857/irjms.2024.v05i03.01239


Abstract The contemplation of mortality paradoxically fosters authentic living and diminishes apprehension as individuals approach death. Research indicates a shift in attitudes toward death reflection with aging. This study seeks to address the gap by comprehensively examining the relationship between age, death reflection, and general anxiety. This study also explores how healthy navigation through death […]

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The Shifting Terrains of Disability and Gender: Investigating the Delineation of Women with Disabilities in Hindi Films

Author(s): Shibu Gorai* , Shri Krishan Rai
Volume: 5 Issue: 3 Pages: 162-171
DOI: https://doi.org/10.47857/irjms.2024.v05i03.01210


Abstract The paper engages with the portrayal of women with disabilities in Hindi cinema, considering the diverse facets of representational strategies and structures of power. Addressed in the narratives as objects of derision, pity, and care, women with disabilities are drawn to the able-bodied gaze and patriarchal chauvinism. Films such as Black (2005), Barfi (2012),

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X-Gen Women Entrepreneur Competence Behavior with Tech

Author(s): Ramamurthy Bedaduri, Rajesh Mamilla*
Volume: 5 Issue: 3 Pages: 432-446
DOI: https://doi.org/10.47857/irjms.2024.v05i03.0774


Abstract Self-Help Groups (SHGs) are critical in empowering female entrepreneurs by promoting self-employment and economic prospects. These groups promote entrepreneur empowerment events and encourage members to adopt competitive behavioral norms. However, despite SHG aid, Generation X (Gen-X) women entrepreneurs have difficulties in adopting technology, reducing their competitiveness. This study investigates the influence of technology adoption

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Economic Indicators and Banking Practices: Predicting NonPerforming Assets in the Financial Sector

Author(s): Ratnavalli B*, Jitendra Gowrabhathini , Deepak Choudhary A, Karthik M, Manikya Sanjay MK, VikramSimha Varma K
Volume: 5 Issue: 3 Pages: 420-431
DOI: https://doi.org/10.47857/irjms.2024.v05i03.0772


Abstract This study examines how several economic and operational factors might forecast Non-Performing Assets (NPAs) in the banking sector. We proposed that macroeconomic indicators, interest rate changes, GDP growth rates, credit risk management strategies, loan monitoring efficiency, and industry-specific declines substantially impacted the occurrence and extent of Non-Performing Assets (NPAs). We used a one-sample t-test

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LuCoNet: A Convolutional Neural Network Model for Lung Cancer and Colon Cancer Prediction Using Histopathological Images

Author(s): Sankalp Hegde, Bhavadharini RM*
Volume: 5 Issue: 3 Pages: 407-419
DOI: https://doi.org/10.47857/irjms.2024.v05i03.0766


Abstract Histopathology is the study of cellular structures, tissues and their abnormalities to diagnose a wide range of diseases, with a primary focus on cancer. The recent innovations and advancements in image analysis techniques and machine learning enable the histopathologists to automate the process of detection and classification of diseases observed in histopathology images. Traditional

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Idiosyncratic Deals: Understanding Effect of Intrinsic and Extrinsic Motivation I-Deals on Innovative Work Behaviour

Author(s): Vani Menon, Aarthy Chellasamy*
Volume: 5 Issue: 3 Pages: 398-406
DOI: https://doi.org/10.47857/irjms.2024.v05i03.0759


Abstract ‘I-deals’ or Idiosyncratic deals are specialised, adaptable work patterns by mutual agreement between employees and their managers to meet demands of a dynamic work place. Innovative work behaviour also known as IWB is referred to as the employee behaviour that intends to create and introduce novel and valuable products, processes, innovations and ways of

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GROW(ing): An Exemplary Educational Approach in Irudhi Suttru

Author(s): Arya PJ, Bhuvaneswari R*
Volume: 5 Issue: 3 Pages: 390-397
DOI: https://doi.org/10.47857/irjms.2024.v05i03.0750


Abstract Education can transform a person’s life by aiding in the development of reason and the attainment of freedom of expression. It entails a process of learning and teaching that progresses through various phases of development for both the instructor and the student. Black (2005), Chak de India (2007), Iqbal (2005), Mary Com (2014), Taare

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Tomtit Flock Optimization with Deep Variational Autoencoder for Customer Churn Prediction in Telecommunication Industry

Author(s): Vani Haridasan*, Kavitha Muthukumaran, Hariharanath K
Volume: 5 Issue: 3 Pages: 376-389
DOI: https://doi.org/10.47857/irjms.2024.v05i03.0749


Abstract The telecommunication sector becomes popular in recent years and service companies suffer from a loss of valued customers to competitors. In the operational area, customer churn is a challenging issue, which makes companies, loses customers, and therefore is of bigger issue for the industry. Recent technologies and competitors were developing quickly and churn prediction

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Choroidal Morphological Changes: A Promising Avenue for Early Diagnosis of Neurocognitive Disorders

Author(s): Pranab Hazra*, Mainak Dey, Priyanka Bawaly, Ashis Kumar Dhara, Tushar Kanti Bera
Volume: 5 Issue: 3 Pages: 847-864
DOI: https://doi.org/10.47857/irjms.2024.v05i03.0970


Abstract Neurocognitive Disorders (NCDs) pose a substantial public health challenge, demanding timely detection and intervention to enhance patient outcomes. Recent strides in medical imaging have unveiled choroidal morphological alterations as a novel avenue for early NCD diagnosis. This study investigates the effectiveness of deep learning algorithms, particularly Residual neural networks (ResNet) and Visual Geometry Group

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Implementation of Deep Learning Application for Emergency Maintenance of Medical Linear Accelerator

Author(s): Damodharan Palaniappan, Thurai Pandian M, Sindhu AS, Premavathi T*, Rituraj Jain, Sanjay Singh
Volume: 5 Issue: 3 Pages: 834-846
DOI: https://doi.org/10.47857/irjms.2024.v05i03.0974


Abstract The purpose of this work is to improve the quality of medical services, to acquire financial benefits for hospitals, and to achieve beneficial social consequences. These are the goals and the motivations that are driving this work. Using the framework of deep learning, it studies the composition of medical linear accelerators, as well as

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