Volume 13 | Issue 2 |

 Abstract

This study evaluates the effectiveness of Human Resource Development (HRD) interventions in addressing critical challenges in large-scale enterprises, including skill gaps, disengagement, high turnover, and resistance to change. Using a mixed-method approach, data were collected from 500 employees across 10 enterprises and 20 HR managers. Statistical tools, including regression analysis, ANOVA, and correlation analysis, revealed that targeted HRD strategies significantly improve employee outcomes. Training and development programs showed the strongest positive correlation with job satisfaction and skill enhancement (r = 0.75, p < 0.01), while performance management systems and engagement initiatives reduced disengagement and turnover rates. The findings highlight the importance of customized HRD practices aligned with organizational goals, recommending ongoing training, robust performance systems, career progression paths, and regular engagement monitoring. These interventions foster a motivated and skilled workforce, driving organizational success. Future research should explore sector-specific HRD practices and their long-term impacts.

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 Keywords

HRD Interventions, Employee Challenges, Large-Scale Enterprises, Employee Retention, Skill Enhancement

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Software development has gotten increasingly sophisticated and demanding, necessitating attention to even minor details. Problems in software development include quality degradation, cost, and schedule overruns. Software organizations rely on measurement programs to control quality, evaluate errors, and manage costs during development. To measure effectively, software metrics must be continuously evaluated and integrated into the development process. Object-oriented design metrics quantify the quality of a class and its attributes. This paper recommends using a combination of methods to improve coding efficiency and accuracy when evaluating projects using object-oriented approaches, including MOOD Metrics, CK metrics, and COCOMO-III. Using object-oriented ways to evaluate code helps identify certain factors. This directly addresses the software's quality. These findings can help enhance software estimation, quality training, and research, leading to more accurate project milestone estimates and fault-free software systems.

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 Keywords

Object-oriented, mood, CK, COCOMO, Defects, measurement, code, etc.

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Premenstrual Syndrome (PMS) is a most common condition affecting young aged women, characterized by physical, emotional, and behavioral symptoms. This study aims to investigate the factors associated with PMS among young adults aged 15-23 years, focusing on sleep patterns, physical activity, stress levels, and symptom severity.A cross-sectional study was conducted among 100 young females in Mumbai using a purposive convenience sampling method. Participants completed validated questionnaires assessing sleep (Athens Insomnia Scale), physical activity (Rapid Assessment of Physical Activity), stress (Perceived Stress Scale), and PMS severity (Premenstrual Symptoms Screening Tool). Anthropometric measurements were also recorded. Data analysis was performed using social science statistics software, employing descriptive statistics and chi-square tests to examine associations. The study found significant associations between PMS severity and various factors. Strength and Flexibility exercises showed strong correlation with PMS(p=0.043). Perceived stress showed a strong correlation with PMS (p = 0.027), indicating that higher stress levels increase PMS severity. Sleep disturbances were significantly linked to PMS(p=0.001) with moderate and severe insomnia strongly associated with severe PMS. Flexibility and strength exercises were significantly associated with PMS (p=0.043). This study highlights the strong association between PMS and modifiable lifestyle factors such as sleep and stress.

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Premenstrual Syndrome, physical activity, stress, sleep, young adults

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Artificial Intelligence (AI) has revolutionized the healthcare industry by enhancing disease detection, drug discovery, surgical precision, and predictive analytics. Integrating Artificial Intelligence (AI) with cutting-edge technologies such as quantum computing and nanotechnology has further improved medical treatments. Artificial Intelligence (AI) -based systems provide clinicians with decision-support tools, reducing diagnostic errors and optimizing treatment plans. Furthermore, Artificial Intelligence (AI) driven predictive models facilitate early disease prevention strategies. While addressing ethical and regulatory considerations, this study addresses the applications of Artificial Intelligence (AI) in medical diagnostics, medication development, surgery, and future forecasts. One of the most important technologies in modern human life is Artificial Intelligence (AI). The use of artificial intelligence (AI) is rapidly spreading across several sectors, ranging from general-purpose ones like perception and learning to more specialized ones such as diagnosing illnesses, digital assistants, search engines, proving mathematical theorems, social media, text editing, and autocorrect. Philosophy, mathematics, economics, psychology, computer engineering, cybernetics, linguistics, and sociology are some of the important fields that have contributed to the development of artificial intelligence (AI). Artificial Intelligence (AI) has transformed the landscape of medical science by enabling faster diagnoses, personalized treatments, and efficient healthcare management. This paper explores recent advancements in Artificial Intelligence (AI) -driven medical treatments, highlighting disease detection, drug discovery, robotic surgeries, and predictive analytics breakthroughs. Furthermore, the study investigates the future trajectory of Artificial Intelligence (AI) in medicine, emphasizing the potential of deep learning, quantum computing, and nanotechnology in revolutionizing patient care. The paper concludes with ethical considerations and challenges related to Artificial Intelligence (AI) implementation in healthcare.

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 Keywords

Artificial Intelligence (AI), Machine Learning, Deep Learning, Healthcare Innovations, Medical Imaging, Predictive Analytics, Disease Detection, Drug Discovery, Robotic Surgery, Quantum Computing, Nanotechnology, Medicine, Big Data, Cancer.

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Creative Commons Attribution 4.0 and The Open Definition

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The integration of Artificial Intelligence (AI) into healthcare has the potential to revolutionize the industry, enhancing patient outcomes, optimizing workflows, and reducing costs. AI technologies, including machine learning, natural language processing, and computer vision, are transforming diagnostics, treatment planning, drug discovery, and patient care management. By enabling more accurate diagnoses, personalized therapies, and efficient administrative processes, AI is improving the overall quality of healthcare services. However, challenges such as data privacy, ethical concerns, and the need for robust infrastructure remain as the healthcare sector adapts to these advancements. This abstract explores the current applications of AI in healthcare, its potential to streamline operations and enhance clinical decision-making, and the future prospects and challenges in creating a more efficient, accessible, and patient-centered healthcare system. Artificial Intelligence is the theory and development of computer systems that are able to perform tasks that would require human intelligence. AI in healthcare is the use of algorithms and software to approximate human cognition in the analysis of complex medical data. It mainly refers to doctors and hospitals accessing vast data sets of potentially life- saving information This includes treatment methods and their outcomes, survival rates, and speed of care gathered across millions of patients, geographical locations and innumerable and sometimes interconnected health conditions. Algorithms are already outperforming radiologists at spotting malignant tumours, and guiding researchers in how to construct cohorts for costly clinical trials. Imaging, on the other hand has become an essential component of many fields in medicine, biomedical applications, biotechnology and laboratory research by which images are processed and analysed. Putting together AI and imaging, the tools and techniques of artificial intelligence are useful for solving many biomedical problems and using a computer based equipped hardware software application for understanding images, researchers and clinicians can enhance their ability to study, diagnose, monitor, understand and treat medical disorders. AI is used in medical imaging to analyze breast cancer(Sonar ,MRI,CT), liver fibrosis and tumour etc.

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Artificial Intelligence (AI) Healthcare Machine Learning Natural Language Processing (NLP) Computer Vision Diagnostics Treatment Planning Drug Discovery Patient Care Management Medical Imaging Radiology Clinical Decision-Making Personalized Medicine Ethical Concerns Data Privacy Healthcare Optimization Biomedical Applications Tumor Detection MRI, CT, Sonar Liver Fibrosis Survival Rates Medical Algorithms

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Periungual warts, caused by the human papillomavirus (HPV), are common benign lesions that occur around the fingernails or toenails, often leading to pain, discomfort, and interference with nail growth. It is most commonly seen in children and young adults , affecting approximately 10- 20% of the case with. Although this condition is not life-threatening, it is challenge to treat with the traditional treatments such as cryotherapy, salicylic acid, and electrodesiccation have varying degrees of success, but recurrence remains common. Case summary - This case report explores the homeopathic treatment of a 27-year-old female with periungual warts using individualized remedies, specifically Thuja and Causticum. The patient had a history of stress and mild discomfort due to cauliflower-like growths around her fingernails. After homeopathic treatment, the warts significantly reduced in size, shrank, and eventually resolved without recurrence. Emotional stress and viral predisposition were considered significant factors in the patient's susceptibility to warts. The outcome was positive, with no new lesions and improved general well-being. This case highlights the potential of homeopathy as a holistic and individualized treatment approach for periungual warts, emphasizing the importance of addressing both physical symptoms and underlying emotional factors. Further research with larger sample sizes is required to establish the efficacy of homeopathic remedies for wart management.

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Warts, Periungal, Homoeopathy, Causticum, Holistic approach.

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Abstract: Almost all of the tourism countries are suffering from seasonality. Like any other destinations Rajasthan Tourism industry has traditionally been characterized by strong seasonality with large differences between winter and summer season. The study proposes to measure seasonality in Rajasthan's tourism industry. The study based on the secondary data acquired from Department of Tourism, Rajasthan. The paper provides methodological approach to analyze seasonality by Seasonal Indices, Seasonal Ratio, Seasonal Indicator and Gini-Coefficient. The findings reveal that a combination of different methods is the best way for analyzing seasonality. Key Words: Seasonality, Seasonal Indices, Seasonal Ratio, Seasonal Indicator and Gini-Coefficient.

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Key Words: Seasonality, Seasonal Indices, Seasonal Ratio, Seasonal Indicator and Gini-Coefficient.

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 Abstract

Cracks affect the strength and appearance of the structure and can demonstrate potential shortcomings or disappointments in materials. There are different types of cracks arrive in structural or non-structural structure due to weather changes, temperature conditions, improper curing, setting, loading conditions and etc., Understanding crack behaviour is crucial for developing effective repair methods such as Epoxy injection, Additional reinforcement, column jacketing, crack stitching, etc., In this paper, the cracks are analysed using a Microscope and rectify these problem. The study of cracks not only identifies the immediate issues but also provides insights into the structure's overall health, guiding long-term durability strategies delaying costly reconstruction. Timely detection and repair of cracks reduce maintenance costs and prevent expensive large-scale repairs or replacements. Cracks in structural elements significantly impact the durability, safety, and functionality of buildings and infrastructure. This study investigates the detection, characterization, and prevention of cracks using a combination of advanced non-destructive testing (NDT) techniques and preventive methodologies. Microscopic analysis provides a detailed understanding of crack morphology and propagation at a microstructural level. Ultrasonic Pulse Velocity (UPV) evaluates the material integrity by identifying internal flaws through variations in wave velocity. The Rebound Hammer test assesses surface hardness and potential crack susceptibility, while Ground Penetrating Radar (GPR) offers subsurface imaging to detect hidden cracks and voids. The integration of these techniques enables a comprehensive evaluation of crack formation, size, orientation, and depth. Additionally, strategies for the prevention of cracks are explored, including material selection, structural design improvements, and environmental control measures. The study aims to establish a multi-disciplinary approach to crack assessment and prevention, providing a robust framework for maintaining structural health and ensuring long-term performance.

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Cracks, Prevention

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The aim of the paper is to examine the transition of artistic practice from miniature painting to European naturalism under the Nizams of Hyderabad from the late 18th to early 20th Century due to the emergence of photography and academic naturalism. Influenced by the colonial modernity, the Nawabs and the nobles encouraged the European style of portraiture. During this period, artists such as Raja Ravi Varma, Shripad Damodar Satwalekar, and R.W. Deuskar sought patronage in Hyderabad, competing with established court photographers like Lala Deen Dayal. Raja Ravi Varma's attempts to secure commissions from Nizam Mahbub Ali Khan highlight the shifting power dynamics in the art world, as photography gained prominence over painted portraiture. Despite professional rivalries and challenges in gaining aristocratic favor, artists like Deuskar contributed to the modernization of Hyderabad's artistic traditions, blending European naturalism with Indian themes. By the early 20th century, Hyderabad's art scene reflected a complex interplay of tradition, colonial influence, and emerging nationalist sentiments.

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Keywords: Hyderabad School, Colonial Modernity, Academic Naturalism, Portraiture, R.W. Deuskar, Nizam Mahbub Ali Khan

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Creative Commons Attribution 4.0 and The Open Definition

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This research investigates how education fosters democracy in India by analyzing key educational policy documents. The study aims to understand how these policies promote democratic values, civic awareness, and political participation. It examines major frameworks such as the Indian Constitution, National Policies on Education (1968, 1986, and 2020), the Right to Education Act (2009), the Kothari Commission Report (1964-66), and other relevant reports. By employing thematic analysis, the study identifies recurring themes such as democratic citizenship, civic education, inclusivity and equity. It focuses on how this policy encourages an active citizenship for political engagement through informed participation of democracy. Additional attention is afforded to inclusiveness, equity and issues that are emerging such as digital literacy and even global citizenship due to NEP 2020. The study reveals the strengths and weaknesses of the policies currently in place in promoting democratic values. The paper concludes with recommendations on how education can be used to create a more inclusive and politically engaged society in India.

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 Keywords

Education and Democracy, Civic Awareness, Political Participation, National Education Policy, Democratic Citizenship, Social Justice

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Creative Commons Attribution 4.0 and The Open Definition