Volume 13 | Issue 8 |

 Abstract

The rapid growth of software systems has led to an increase in the volume and complexity of bug reports, necessitating efficient and accurate prediction models to manage and address these reports effectively. This paper presents a Nature-Based Prediction Model of Bug Reports (NBPMBR) leveraging ensemble machine learning techniques to enhance the prediction accuracy and reliability of bug report classifications. By integrating various nature-inspired algorithms such as Genetic Algorithms (GA), Particle Swarm Optimization (PSO), and Ant Colony Optimization (ACO) within an ensemble framework, NBPMBR combines the strengths of these algorithms to improve performance.The model undergoes rigorous training on historical bug report data, using feature extraction methods to capture relevant information such as bug severity, priority, and textual descriptions. The ensemble approach ensures robustness by mitigating the weaknesses of individual algorithms, leading to a more balanced and accurate prediction outcome. Experimental results on benchmark datasets demonstrate that NBPMBR outperforms traditional machine learning models in terms of precision, recall, and overall prediction accuracyThis nature-based ensemble model not only advances the state-of-the-art in bug report prediction but also provides a scalable and adaptable solution for real-world software maintenance and quality assurance processes. By automating the classification and prioritization of bug reports, NBPMBR aids in the efficient allocation of resources, thereby improving the software development lifecycle and enhancing the overall quality of software products.

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 Keywords

XG Boost classifier, Support Vector Machine (SVM), Logistic Regression, Random Forest, Propose Voting Classifier Confusion Matrix, Extension XGBoost Confusion Matrix

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This study investigates the financial literacy of MGNREGA workers in Karnataka, with a focus on savings, investment, and insurance practices. Adopting a descriptive research design, data were collected from 200 participants using a structured Likert-scale questionnaire. The responses were analysed using SPSS with t-tests to measure the literacy levels across domains. The results reveal moderate financial literacy in savings and investment, with mean scores significantly higher than neutral levels. However, insurance awareness remains low and statistically insignificant, indicating a critical gap in risk management knowledge among the workers. The study underscores the urgent need for targeted financial education programs, especially in the domain of insurance. It recommends collaborative efforts between local self-help groups, NGOs, and policymakers to design and implement financial literacy initiatives tailored to rural communities. Strengthening these capacities is vital for enhancing financial empowerment and ensuring sustainable livelihoods in rural Karnataka.

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Financial Literacy, MGNREGA workers, savings awareness

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Creative Commons Attribution 4.0 and The Open Definition

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(Abstract: Christian Missionaries set their foot on the soil of Assam for the first time in early 19th century and gradually spread to the rest of the other north eastern states. The British official encouraged missionary activities in these regions to improve the backwardness of indigenous population and to spread the gospel of Christianity. However, it was in the later part of 19th century when frontier tribes of Arunachal Pradesh got connected with missionary activities. The paper will enlighten the advent of Christianity in North Eastern region of India.)

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(Key Words: Abor, Christianity, Kampti, Khasi, Missionary, Sadiya, Singpho,)

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This review examines the influence of social media on tourism behaviour, synthesising recent studies to explore how platforms like Instagram, TikTok, and Facebook shape destination choices, tourist engagement, and marketing strategies. The literature is organised thematically, covering the impact of social media content, electronic word-of-mouth (e-WOM), influencers, destination image, psychological factors, and regional contexts. Findings highlight that visually engaging content, credible peer reviews, authentic influencer narratives, and culturally resonant strategies drive tourist decisions, with variations across demographics and regions. Gaps in research, particularly in regional and socio-economic contexts, are identified, suggesting directions for future studies. This review provides insights for destination marketing organisations (DMOs) to leverage social media effectively.

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Social media, tourism behaviour, destination choice, electronic word-of-mouth (e-WOM), influencers, destination image, psychological factors, regional contexts, destination marketing.

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The growth of self-financing colleges in Kerala has expanded educational opportunities but has also raised questions about the working conditions of teachers employed in these institutions. This study investigates the level of job satisfaction and economic well-being of self-financing college teachers, while also examining the professional challenges they encounter. Primary data were collected from 135 teachers across different self-financing colleges in the Malappuram district using a structured questionnaire. The finding reveals that job satisfaction among self-financing teachers is moderate, with significant differences between Arts and Science and Engineering faculty. Economic well-being scores indicate that while most teachers can meet household expenses, low and irregular salary payments, limited savings capacity, and dissatisfaction with income contribute to economic insecurity. Professional challenges such as lack of job security, heavy workload, and restricted career advancement opportunities further intensify these difficulties.

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Creative Commons Attribution 4.0 and The Open Definition

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Job satisfaction, Economic well-being, Professional challenges, Self-financing colleges

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this paper is about a unique printmaking technique called color Intaglio: reduction process which is only developed and practices in the college of Fine Arts in Andhra University, Visakhapatnam. This particular process evolved from the scarcity of materials, students started reusing the zinc plates said by Shree T.Sudhakar Reddy Rtd. Professor from printmaking, Fine Arts Department at Andhra University, Visakhapatnam.

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Printmaking, Intaglio, etching, color Intaglio, reduction process, zinc plate, burnishing, re use.

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Abstract Rheumatoid Arthritis (RA) is an autoimmune disorder, which can lead to joint deformation and which can lead to permanent disability that cannot be treated in a timely manner. Early diagnosis is thus imperative for effective treatment. In this paper, we present an end-to-end RA detection system with the help of Convolutional Neural Networks (CNN) for hand X-ray images. The model is trained on a balanced 200-image dataset (100 RA, 100 Normal) with extensive pre-processing and augmentation techniques which is used to enhance performance in the lack of large datasets. The CNN architecture was here we used is chosen for its ability to extract hierarchical features from medical images without manual feature engineering. The trained model was deployed using a Flask-based web application, with real-time prediction supported by confidence scores and easy-to-use interaction.This Experiment gives the results that show high reliability, with test cases reporting 96.24% confidence for Normal x-ray image and 92.27% for RA-positive cases.There is another approach where the numerical clinical dataset is used which contain details such as age, gender, ESR, CRP, RF, and Anti-CCP levels. Here the Deep Neural Network (DNN) was trained after preprocessing and scaling the data, demonstrating high predictive performance compared to traditional Machine Learning models. This model was implemented using a Flask-based web application, which will work with real-time prediction and confidence scores and simple interaction. The system can be potentially integrated into clinical workflows, especially in regions where specialist availability is scarce.

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 Keywords

CNN, DNN, Rheumatoid Arthritis, Medical Imaging, Flask, Deep Learning, X-ray Analysis CNN, Rheumatoid Arthritis, Medical Imaging, Flask, Deep Learning, X-ray Analysis.

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Creative Commons Attribution 4.0 and The Open Definition

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Heavy metal contamination in soil ecosystems poses a significant environmental and microbiological concern due to the persistent and toxic nature of metals such as Zinc and Cadmium. This study evaluated the microbial response to heavy metal-induced stress by isolating soil bacteria from industrially impacted areas in Bangalore, India. Using standard microbiological techniques, the isolates were cultured on various media and were exposed to various concentrations of Zn and Cd to evaluate their tolerance profiles. Disc diffusion assays were performed to determine zones of inhibition, revealing concentration-dependent sensitivity. Zinc showed moderate antimicrobial effects, with partial bacterial growth observed at lower concentrations, while cadmium exhibited strong toxicity and completely inhibited microbial growth in most cases. Subculturing in broth media further confirmed these observations, with visible growth in Zinc-supplemented Nutrient Broth but complete inhibition in Luria Broth, potentially due to me

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Heavy metal stress; Cadmium; Zinc; Disc diffusion assay; Bioremediation potential

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Creative Commons Attribution 4.0 and The Open Definition

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Body self-image refers to how one perceives their own bodies on the basis of different aspects like fitness, fatness, overall appearance, and some other aspects. The motivation to compare one's body through social media describes a person's inclination to evaluate their own physical appearance in relation to others they see online. The present study was done on 200 college students to study the relationship between social media use with the motivation of body comparison and dimensions of body self-image. The tools used were motivation to use social media for body comparison and subscales of body self-image questionnaire-short form (BSIQ-SF). Correlation design was used and the results showed a significant negative relationship between motivation to use social media for body comparison and investment in ideals (r = -0.145*), other correlations with BSIQ-SF subscales were not significant. Regarding BSIQ-SF subscale interrelations, positive significant correlations emerged between investment in ideals and health fitness influence (r = 0.179*), social dependence (r = 0.267***), and attention to grooming (r = 0.377***). Negative significant correlations were found between overall appearance evaluation and other variables like fatness evaluation (r = -0.516***) and negative affect (r = -0.496***). The study is significant because it provides the basis for developing psychological interventions, educational policies, empirical evidence that would help in the reformation of societal standards of beauty and perception of a 'perfect body', by forming an essential reference for further studies in this field of research.

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

College Students, Motivation to Use Social Media for Body Comparison, Dimensions of Body Self-image, Social Media

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Creative Commons Attribution 4.0 and The Open Definition

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Abstract- The relationship between violence and memory in Saadat Hasan Manto's Partition tales Thanda Gosht and Khol Do is examined in this essay. Both tales illustrate how the pain of Partition persists as an embodied memory and psychological scar long after the violence has ended. Ishwar Singh's discovery of the murdered girl and his subsequent impotence in Thanda Gosht reveal how cruelty leaves a lasting memory that undermines connection and identity. In contrast, Sakina's dehumanized state, where her robotic answer to the command "open it," attests to the erasure of agency under the weight of repeated assaults, is how Khol Do foregrounds the collective pain of displacement and sexual abuse. Together, these stories illustrate Manto's unflinching portrayal of Partition as not merely a historical rupture but a continuing site of memory, where survivors and victims' alike embody the afterlife of violence. Drawing on trauma theory, particularly Cathy Caruth's notion of trauma as a belated and intrusive experience, this paper argues that Manto situates Partition within a framework of unending remembrance, making visible the inescapable entanglement of violence, memory, and identity.

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 Keywords

Violence, trauma, memory, partition, Manto and Caruth

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Creative Commons Attribution 4.0 and The Open Definition