Volume 13 | Issue 1 |

 Abstract

Lung cancer continues to be a major cause of death globally, and early diagnosis plays a critical role in improving survival rates. This study explores the potential of machine learning models to detect and classify lung cancer using a publicly available dataset. Five different algorithms--Logistic Regression, K-Nearest Neighbors (KNN), Support Vector Machine (SVM), Naive Bayes, and Random Forest--are examined to evaluate their effectiveness in lung cancer detection. Data preprocessing techniques are applied to address missing values, normalize features, and partition the dataset into training and testing subsets for model evaluation. To assess and compare the performance of the models, various metrics such as accuracy, precision, recall, F1-score, and Area Under the Curve (AUC) are employed. The results show that the Random Forest model yields the highest accuracy at 91.8%, followed by SVM and Logistic Regression. Although KNN and Naive Bayes demonstrate slightly lower performance, they still offer useful insights, particularly due to their simplicity and computational efficiency. This study underscores the advantages of Random Forest, especially in managing complex datasets, making it a promising tool for the early detection of lung cancer in clinical settings. The results suggest that machine learning techniques, especially ensemble methods like Random Forest, can aid healthcare professionals in delivering faster and more accurate diagnoses, leading to improved patient outcomes and optimized clinical processes.

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 Keywords

Lung Cancer, Machine Learning, Logistic Regression, KNN, SVM, Naive Bayes, Random Forest, Classification, Early Detection, Healthcare Applications

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

This study focuses on the taxonomic investigation of tapeworm species from the genus Senga (Cestoda: Pseudophyllidea) found in the freshwater fish Mastacembelus armatus from the Washim District of Maharashtra, India. The present communication describes a new species, Senga govindii, identified in Mastacembelus armatus from the Penganga River. This species differs from known species of the genus in several characteristics, including the shape and size of the scolex, the number of hooks, the arrangement of the rostellum, the shape of the segments, the number of testes, the position of the cirrus pouch, and the arrangement of the vitellaria.

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 Keywords

Mastacembelus Armatus, cestode parasites, Pseudophyllidean, Senga.

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Creative Commons Attribution 4.0 and The Open Definition

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Neither liquidity nor profitability pose a danger to the overall resilience and quality of the assets held by Indian banks. The sufficiency and quality of the financial infrastructure are largely determined by the standard of assets held by the banking sector. NPAs are a key factor in evaluating a bank's ability to manage its budget. A significant problem for the Indian banking industry is the rise in non-performing assets (NPAs). The rise of nonperforming assets (NPAs) is one of the biggest concerns facing India's banking industry. The study's objective is to assess and contrast SBI and HDFC Bank's GNPA and NNPA. The same relevant data have been gathered and examined for a five-year period, spanning from 2020 to 2024. The findings indicate that although the GNPA and NNPA of SBI Bank have declined, the HDFC Banks have climbed dramatically.

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 Keywords

Non-performing Assets (NPA), Gross non-performing assets, (GNPA), Net non-performing Assets (NNPA)

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Creative Commons Attribution 4.0 and The Open Definition

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This paper emphasis the investment problems and satisfaction level of university teachers in diverse investment avenues. The study attempts to understand the investment problems faced by investors while investing and analyze the satisfaction level of university teachers towards investment options. The primary data was collected from 50 Vijayanagara Sri Krishnadevaraya University Teachers through structured questionnaire and analysed through SPSS software with statistical tools such as descriptive statistics, Ranking Analysis and MANOVA. The investment problems faced by the investors is analysed by ranking analysis considering mean value of investment avenues and identified that low return, risk and liquidity are the major problems faced by the investors. The study reveals that there is a significant relationship between demographic factors and satisfaction level towards investment options by applying Multivariate test.

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Investment Problem, Satisfaction, Avenues, Multivariate

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Creative Commons Attribution 4.0 and The Open Definition

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Diabetes mellitus is a long-term metabolic condition by elevated blood sugar levels due to problems with insulin production, insulin function, or a combination of both. Effective Diabetes management strategy requires careful selection and monitoring of pharmacological therapy. This review focuses on prescription pattern analysis of anti-diabetic drugs in secondary care hospitals, emphasizing the trends, efficacy, and compliance observed in real-world settings. Understanding these patterns can guide clinicians in optimizing treatment strategies and improving patient outcomes.

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Creative Commons Attribution 4.0 and The Open Definition

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Diabetes, Patient, prescription, analysis

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Creative Commons Attribution 4.0 and The Open Definition

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Abstract: Globalization has been a transformative force in shaping the Indian economy, particularly since the economic reforms of 1991. This research paper examines the multidimensional impact of globalization on India's economic landscape, focusing on key sectors such as agriculture, manufacturing, and services. Using an analytical approach, the study evaluates economic indicators like GDP growth, foreign direct investment (FDI), trade dynamics, and employment trends to understand globalization's influence. The paper also explores the socio-cultural implications, including shifts in consumer behavior, education, and labor dynamics. While highlighting the opportunities brought about by globalization--such as increased market access, technological advancements, and integration into global supply chains--it also addresses the associated challenges, such as income inequality, environmental concerns, and vulnerability to global market fluctuations. This research provides policy recommendations to maximize globalization's benefits while mitigating its adverse effects, ensuring sustainable and inclusive economic growth. By combining historical analysis, empirical data, and case studies, the paper offers valuable insights into India's journey within the global economic framework and its potential path forward in a rapidly evolving globalized world.

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 Keywords

Globalization , Shaping, India's, Economic, Growth , Development

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Creative Commons Attribution 4.0 and The Open Definition

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The integration of technology in language instruction has significantly influenced the standardization of English, which is crucial in various global contexts. This study examines the role of technology in promoting Standard English, explores the challenges it introduces, and highlights its impact on teaching methods and learning outcomes. By analysing responses from educators and students of English learning as foreign language, the present research identifies the benefits and drawbacks of technology-driven language education, emphasizing the need for a balanced approach that combines technological tools with traditional pedagogy

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 Keywords

Technology, ELT, Digital Learning, CALL, Web, Internet

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Technology is rapidly spreading. one cannot imagine a day without the use of digital technologies. todays students are more dependent on internet as a supplement for achieving their academic goals. Even a layman is operating smart phones for communication and other services. The knowledge of digital literacy has become necessary for every individual to lead a successful life. Hence this paper.

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Creative Commons Attribution 4.0 and The Open Definition

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Digital literacy, education

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Creative Commons Attribution 4.0 and The Open Definition

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The amalgamation of artificial intelligence (AI) and data science in business services has the potential to bring about significant improvements in efficiency, cost reduction, and innovation across various industries. However, it also raises important ethical and privacy concerns that must be addressed. This paper aims to explore the opportunities and challenges of leveraging AI and data science in business services. The paper will first discuss the potential benefits of AI and data science, including improved efficiency, cost reduction, and innovation. It will then examine the ethical and privacy concerns that arise with the use of AI and data science in business services, including bias and discrimination, invasion of privacy, lack of transparency and accountability, and job loss. The paper will also discuss measures that businesses can take to address these concerns, including developing ethical guidelines and policies, responsible data management and governance, and transparency and accountability in AI systems. Finally, the paper will provide a future outlook for the amalgamation of AI and data science in business services, highlighting the need for responsible and fair use of these powerful technologies.

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 Keywords

AI (artificial intelligence), Data Science, Automation, Decision-making, Personalization, Customer service, Predictive maintenance, Expertise, Data quality, Privacy, Ethics, Integration, Cost

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Banking and financial services are fundamental to organizations across various sectors, including government, private, public, academic, and not-for-profit entities. The demand for digital transformation in these organizations has grown significantly, especially in response to challenges posed by the COVID-19 pandemic. During this period, many organizations were compelled to transition to online service delivery, even though the supporting infrastructure--such as reliable internet connectivity, widespread smartphone adoption, advanced technologies, and a digitally skilled workforce--was not fully developed.Robotics, a multidisciplinary field focused on designing machines capable of mimicking and replicating human actions, offers solutions that save time, reduce costs, and enhance service quality. Robotic Process Automation (RPA) in banking and financial services presents numerous advantages, including cost reduction, strengthened regulatory compliance, streamlined operations, minimized operational risks, and improved customer experiences. This study explores the evolution of robotics and examines its applications and impact within the banking and financial services industry.

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Fintech, Robot, RPA, Robotic Process Automation, Digital Finance, Artificial Intelligence, Banking, Financial Services

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Creative Commons Attribution 4.0 and The Open Definition