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    Item type:Item, Thesis Access status: Open Access ,
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    Item type:Item, Thesis Access status: Open Access ,
    Impact of employee wellness on employee performance in banking industry of West Bengal
    (University of North Bengal, 2024) Dutraj, Rajeev; Sengupta, Palash R.
    Organisations were beginning to make the correlation between the vitality of their staff and their progress as establishments. Happier workplaces emerged from healthier and more engaged staff members. Also, the more highly engaged teams showed an increase in profitability by double digits. A holistic perspective on an individual's health and well-being emerged in the wellness realm, inclusive of physical, mental, emotional, social and spiritual aspects. This development necessitated better and preventive strategies of maintaining health within the larger context of wellness. This realization brought about a massive paradigm shift in organisational strategies that focused on holistic approaches to employee treatment rather than the erstwhile satisfaction-based. Since the 1990s, the profound transformation of banks had led to work-related stress challenging both employees’ performance and mental health, especially in the banking sector where employee welfare were central to economic governance. Strategies implemented to aim to balance rapid changes like liberalization, globalization, and technological advancements with employee wellbeing. Stress and health issues from these changes emphasized the importance of workforce wellness, yet addressing mental health problems in the banking industry was slow. Stress and other health conditions caused by these significant changes had put a premium on the wellness of the workforce in an age where millions around the globe were challenged with mental health issues. There had been a widespread prevalence of mental health problems in the workplace, but head of the institute in the banking industry was slow to address them. The transformation had led to workrelated stress challenging both the employees’ performances and mental health. The understanding of the pervasiveness of mental disorders globally led to the rise in organisations adopting broad-based employee wellness anchored on motivation and happiness theories. This study primarily focused on the interplay between Maslow’s hierarchy of needs and Herzberg’s two-factor model and the exploration of various dimensions of employee wellness. However, the study also considered the mediating role of employee mental well-being as a key component of the broader theoretical framework in the present study. The interplay of financial, social, workplace and spiritual wellness explained the combined effects of these key contributors on employee performance through the perspective of the mental well-being of bank employees. Notably, the direct link between employee well-being was important, considering the detrimental impacts of poor mental health on productivity and overall performance. Employers had begun countering this phenomenon by introducing wellness programs and flexible working hours. Employee wellness was a must-do for banking's future success in diverse micro and macro environmental challenges that were constantly evolving. Whenever organisations chose to take care of employees first, a long-term triumph of those companies in this area was guaranteed because they created happier employees with lower turnover rates than expected. Design/Methodology The study sample consisted of 498 employees with a variety of branches of the bank in West Bengal, and the research consisted of three phases: to begin with, descriptive statistical analysis to describe the data in terms of the demographic data, and second, to identify the research variables/instruments. The third phase was represented by the testing of the hypotheses and determining the causal relationships. The study applied a sample based on probability theory to achieve impartiality. For Exploratory Factor Analysis, a language used for factor analysis, was performed using IBM SPSS to address the different factors for testing the hypothesis, while the Sobel test was used to determine the mediation effect. The researchers used structural equation modeling via SPSS AMOS 22. Hence, EFA and hypothesis testing as the mediator variable were tested by using the Sobel test. Findings The findings emphasised the role of employee mental well-being as a partial mediator in the connections between financial wellness, social wellness, workplace wellness, spiritual wellness, and employee performance. Moreover, the study disclosed that all dimensions of employee wellness demonstrated a causal relationship with the exogenous variable. These outcomes endorsed incorporating motivation theory with diverse wellness dimensions, accentuating the significance of positive mental wellbeing in elucidating the proposed model. Limitations Retrieving the truthfulness of the employees’ mental status was strenuous. It was only restricted to four dimensions of wellness. That was the financial, social, spiritual, and workplace. The overall understanding of employee wellness did not explicitly reveal relevant information that necessitates. Therefore, longitudinal research would be better to establish a more reliable method of measurement. The model could incorporate moderating factor, showing other factors such as the employee's family background and gender, which influence mental health. Although limited to a few districts in West Bengal, the survey also included the majority. Practical Implications The recent study contributed significantly to the understanding of employee wellness in the banking sector. As a result, the causal link between various wellness dimensions with employee performance and, subsequently, organisational success was established based on the examined relationship with employee mental well-being. Moreover, the study showed high significance of mental well-being in employee focus and performance. The results also proved the suitability of the four-factor wellness comprising financial, social, spiritual, and workplace directions. The prevalence of stress and the insufficient availability of immediate solutions for mental health problems were determined. At the same time, the awareness of the field supported by actual measures for the banking sector, such as counselling services and stress management, was indicated. Finally, the study revealed the potential of employee wellness as the change agent in the respective lifestyle, relying on the motivation theory to prevent burnout. Hence, the theory had the potential to shift of focus from reactive to proactive behaviour ensuring the always-motivated employees. Originality/Value The proposed model, uniquely integrating employee mental well-being as a mediator factor, represented an unexplored avenue in prior research. The results proposed a roadmap with which to tackle the challenge of mental health disorders and could create opportunities to better employee performance. As such, this model had the potential to become a key pillar in formulating future Human Resource Bank policies
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    Item type:Item, Thesis Access status: Open Access ,
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    Item type:Item, Thesis Access status: Open Access ,
    Design and development of a computer based automated system for brain tumar segmentation
    (University of North Bengal, 2024) Sarkar, Kanishka; Mondal, Ardhendu
    The research study focuses on diagnosing brain tumors from medical images using a combination of image processing and machine learning techniques. Early detection of brain tumors is crucial for improving the chances of patient survival. The study is organized into five chapters, each addressing a specific aspect of the research. Chapter 1 functions as an introductory section, offering a comprehensive view of the problem domain. It succinctly outlines the motivation driving this study, followed by an exploration of diverse information concerning the brain and brain tumors. Additionally, it elucidates the importance of early tumor detection and delineates the associated challenges. Finally, a proposed work plan is outlined in this chapter. In Chapter 2, the focus is on the preparatory procedures for MRI (Magnetic Resonance Imaging) and CT (Computed Tomography) images. These processes encompass various methods, such as eliminating background, refining images through enhancement, and removing the skull. The removal of the background serves to eliminate extraneous information, while enhancement techniques work to elevate the overall image quality. The objective of skull stripping is to isolate the brain region by separating it from the surrounding structures. An innovative method involving generating an ellipsebased mask for Head Masking has been proposed. Moreover, the use of the Distance-versus-Angle feature is implemented to distinguish CT images that lack a patient table structure in the CT slice. In the case of contrast enhancement, a straightforward geometric transformation is employed on the sectional Gamma-transformation mapping graphs. As for skull stripping, the approach involves applying adaptive intensity slicing and iterative morphology. In Chapter 3, the approaches employed for the identification and delineation of tumors are examined. These algorithms carefully analyze the pre-processed images to identify regions that potentially contain tumors. To enhance the accuracy of tumor detection and segmentation, a variety of techniques are employed, spanning conventional image processing methods and machine learning approaches. A novel method of feature extraction, specifically the ”Expanded Local Histogram,” is introduced for tumor detection. Additionally, two inventive thresholding approaches, namely ”Peak Difference” and "Least Center Distance," are proposed for tumor segmentation. Furthermore, an original super-pixel classification method is suggested for the segmentation of tumors in both CT and MRI images. Chapter 4 delves into the outcomes of the implemented algorithms. A comprehensive evaluation is conducted, comparing the proposed methods with cutting-edge techniques to demonstrate their efficacy. This section underscores the significant impact of the proposed algorithms, emphasizing their accuracy and poten'tial to enhance patient outcomes. The introduced head masking achieves an average Jaccard coefficient value of 94% for MRI images and 93.4% for CT images. The patient table detection algorithm exhibits a remarkable accuracy of 99.4%. The proposed contrast enhancement method not only outperforms comparable methods in contrast value but also maintains a high correlation of 98% and the maximum entropy value. The skull stripping method proposed attains an accuracy of 97% for MRI images and approximately 99% for CT images. In the realm of tumor detection, the proposed method achieves accuracy rates of up to 99°/o for MRI images and 100% for CT images. The tumor segmentation, employing the peak difference threshold, demonstrates an accuracy of 95.63%, while the Least Center Distance (LCD) method achieves 96.64% accuracy. The superpixel classification method attains over 99% accuracy for MRI images and 98.64% for CT images. Finally, the conclusive outcomes of the proposed methods, limitations, and future scope have been dis6us`sed in Chapter 5. Overall, the research study aims to contribute to the field of brain tumor diagnosis by introducing a set of algorithms for medical image enhancement, skull stripping, tumor detection, and tumor segmentation. The proposed methods utilize both traditional image processing strategies and machine learning approaches. The results and comparisons provided in the study help evaluate the effectiveness of these algorithms in enhancing early tumor detection and, consequently, increasing the possibility of patient surival.
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    Ethical philosophy of Srimad-Bhagavad-Gita
    (University of North Bengal, 2023) Ghosh, Sondipa; Roy, Nirmal Kumar