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Improved Collaborative Filtering using Evolutionary Algorithm based Feature Extraction
International Journal of Computer Applications Vol.64,No.20, pp.20-26 ISSN No. 0975-8887 -
Group Movie Recommendations via Content Based Feature Preferences
International Journal of Scientific & Engineering Research Vol. 4, Issue 2, pp.1-5 ISSN No. 2229-5518 -
Developing the assessment questions automatically to determine the cognitive level of the e-learner using NLP techniques
The key objective of the teaching-learning process (TLP) is to impart the knowledge to the learner. In the digital world, the computer-based system emphasis teaching through online mode known as e-learning. The expertise level of the learner in learned subjects can be measured through e-assessment in which multiple choice questions (MCQ) is considered to be an effective one. The assessment questions play the vital role which decides the ability level of a learner. In manual preparation, covering all the topics is difficult and time consumable. Hence, this article proposes a system which automatically generates two different types of question helps to identify the skill level of a learner. First, the MCQ questions with the distractor set are created using named entity recognizer (NER). Further, based on blooms taxonomy the Subjective questions are generated using natural language processing (NLP). The objective of the proposed system is to generate the questions dynamically which helps to reduce the occupation of memory concept. 2020, IGI Global. Copying or distributing in print or electronic forms without written permission of IGI Global is prohibited. -
Associations Between Religious Coping and Anxiety Symptoms Among Emerging Adults in India: Religious Centrality as a Potential Moderator
Anxiety disorders are globally prevalent, with the highest disease burden in low- and middle-income countries. However, most research on protective factors of anxiety is predominantly conducted in high-income countries. Focusing on India, the most populous middle-income country where religion is salient, this study examined the association between religious coping and generalised anxiety symptoms and whether aspects of social identity moderated this association. A religiously and ethnolinguistically diverse sample of emerging adults (N = 484, Mage = 20.48 years) completed measures of religious coping, religious centrality and anxiety. Results indicated that negative religious coping was positively associated with anxiety symptoms, whilst positive religious coping was unrelated to anxiety. Religious centrality did not moderate the relation between religious coping and anxiety. However, ethnolinguistic identity (Northeastern vs. other regions) moderated the association, such that negative religious coping predicted higher concurrent anxiety among Indians from other regions, but not among Northeasterners. Findings support the role of negative religious coping in anxiety and suggest investigations into the role of ethnolinguistic identity as a critical contributing factor to mental health. 2026 The Author(s). International Journal of Psychology published by John Wiley & Sons Ltd on behalf of International Union of Psychological Science. -
Coping with Burnout Across Cultures
The well-being of employees is impacted by numerous factors within their work realm. These factors consist of internal elements, such as the work environment, relationships with coworkers, and satisfaction with their jobs, as well as external factors like job security, working conditions, pay, and growth opportunities. Unfortunately, the COVID-19 pandemic has introduced significant changes that have greatly disrupted the factors that were crucial for employees to maintain a healthy and productive career. These changes include the global economic downturn, shifts in workplace culture, and a decline in worklife balance, all contributing to increased job insecurity among employees. The weight of unemployment and job insecurity often materialises as burnout and enduring fatigue among employees, consequently lessening their peak efficiency level. However, while exploring coping techniques for burnout, cultural practices are persistently overlooked. However, each culture possesses distinctive norms that shape an individuals way of handling workplace stress and pressure. This paper will predominantly look at secondary data published in online databases to explore previously existing literature on differences in culture while coping with burnout. Through the literature review, the authors compare the coping mechanisms employees adhere to between individualistic cultures and collectivist cultures. The paper highlights employees routines at a broader level, emphasising the need for organisations to be aware of diverse coping styles, especially on sites that act as a melting pot of cultures. It aims to promote safer work environments by articulating the differences in coping mechanisms of employees in different cultures. The paper explores sustainable practices for employees and workers to enhance their job satisfaction and well-being. The Author(s), under exclusive license to Springer Nature Switzerland AG 2026. -
Sentiment Analysis for Online Shopping Reviews Using Machine Learning
Everyday shoppers need reliable and insightful reviews of e-commerce websites to enhance their shopping experience. This research study explores sentiment analysis on Amazon reviews. It utilizes them as a diverse repository of customer opinions by unlocking their embedded sentiments, thereby recognizing their pivotal role in guiding potential buyers. Sentiment misinterpretations may result from many machine learning models that have trouble comprehending the context of Amazon reviews, particularly regarding subtle wordings, sarcasm, or irony. Additionally, these models can have biases that skew sentiment analysis results, mainly when working with a diverse set of Amazon review datasets. To overcome these, three machine learning models, namely, Bidirectional Encoder Representations from Transformers (BERT), Bidirectional and Auto-Regressive Transformers (BART), and Generative Pre-trained Transformers (GPT) are used in this study. During the experimental research, it was observed that BERT gave the highest accuracy of 90% when compared with BART (70%) and GPT (84%) models. BERTs bidirectional contextual comprehension at identifying subtleties in language provides a thorough and realistic representation of the sentiments of Amazon users, which is why the model gave the highest accuracy. The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024. -
Intersecting queer rights and legislative theatre in India: advocacy narrative of power, justice and expression
Queer activism and Legislative Theatre (LT) converge in myriad ways at their intersection, influencing and shaping each other. The present work investigates how LT can help to identify queer marginalisation in the fissured legal paradigm of India. It explores how LT can address the hegemonic silencing of the queer from an advocacy perspective. Our conviction is that the LT challenges the entrenched power structures against a queer-inclusive democratic space, offers a blueprint to advance queer dialogue, and coalition-building for legislation and policy discussions. It is the time when such a potent artistic activism must shape the public discourse. 2025 Informa UK Limited, trading as Taylor & Francis Group. -
Pandemic, theatre and performance: Democratizing the subalterns through the Theatre of the Oppressed
The presented work analyses Theatre of the Oppressed (TO) methods impacting the pandemic. It follows the WHO timeline, when the COVID-19 pandemic had cast a dark shadow, making sustenance difficult for the marginalized section of Indian society. TO methods, though reflected, adapted and accommodated exhaustively in Indian applied theatre over the last four decades, offered a fresh, collective, democratic space during the pandemic. Forum theatre (FT) and legislative theatre (LT) praxis rendered a platform for activism, awareness and emancipation of the subalterns during the pandemic. Thus, TO renewed psycho-social dialogue and critical, creative, experimental space during this time. The applicability of such methods facilitating social change is gauged using Boals spect-actorship and Freires conscientization. The article looks forward to the TO signposts to serve as nodal points for further scholarly discussion and study on democratizing the disenfranchised population through FT and LT during the pandemic. 2023 Intellect Ltd Article. English language. All Rights Reserved. -
Facial Expression Recognition with Transfer Learning: A Deep Dive
In the realm of affective computing, where the nuanced interpretation of facial expressions plays a pivotal role, this research presents a comprehensive methodology aimed at refining the precision of facial expression recognition on the CK+ (Cohn-Kanade Extended) dataset. Our method uses the robust DenseNet121 architecture that has been pretrained on the 'imagenet' dataset, and it leverages transfer learning on the foundational CK+ dataset. The model deftly handles issues with overfitting, normalization, and feature extraction that are present in facial expression detection on CK+. Our approach not only achieves an overall accuracy of 98%, with a 5.86% accuracy enhancement over the base paper on the CK+ dataset, but also shows remarkable precision, recall, and F1-score values for individual emotion classes. It is noteworthy that emotions such as anger, contempt, and disgust have precision rates that reach 100%. The study highlights the model's noteworthy input to affective computing and presents its possible real-world uses in emotion analysis on CK+ and human-computer interaction. 2024 IEEE. -
Advancements and challenges in deep learning for breast cancer screening: A review
Breast cancer continues to be the prevalent cancer on a global scale, playing a major role in the worldwide cancer statistics, the critical role of early detection in reducing death rates is underscored. In the context of breast cancer, screening, deep learning (DL) emerged as a game-changer, providing notable improvements over existing techniques. This review explores the use of DL in analysing images from various sources such as X-rays, ultrasound, magnetic resonance imaging, and biopsies. Additionally, it highlights DL's potential to pre-screen for cancer by integrating diverse data, including demographic information, biological markers, and meta-analytical risk assessments. The analysis reveals that deep learning frameworks, especially those optimized with feature selection techniques, attain the minimal false-negative rates, effectively distinguishing between patients with and without cancer. Notably, DL models demonstrate lower prediction uncertainty compared to traditional machine learning, as shown by reduced standard deviations in performance metrics. Additionally, the paper proposes a cascade network model that achieves 98.61% classification accuracy and a 98.41% F1 score by segmenting tumours with a UNet architecture and classifying them with a ResNet backbone. Despite these advancements, challenges such as limited annotated data and adaptability to new data domains persist. In response to these issues, the proposed Self AdaptNet leverages innovative self-supervised learning and adversarial techniques to improve the resilience as well as adaptability of BC detection models.AI technology, particularly DL-based systems, has the capacity to completely transform breast cancer screening by improving screening accuracy and reducing observer variability. However, clinical adoption requires standardized guidelines, trustworthy AI practices, and collaboration among researchers, clinicians, and regulatory bodies. 2026 Author(s). -
Non-Invasive Detection of Ovarian Cancer using Biosensors Framework with Machine Learning and Federated Learning Techniques
Ovarian cancer is a leading cause of death worldwide, frequently diagnosed at advanced stages due to the lack of effective early screening methods. This work proposes a non-invasive cancer diagnostics utilizing amperometric electrochemical biosensors in early cancer detection from biological fluids, such as urine-based by combination of specific biomarkers like HE4 and Ca125, which are closely associated with ovarian cancer. This study approach integrates machine learning models to work with biosensor data for cancer classification tasks, and federated learning methods to ensure patient data privacy. The proposed system achieves diagnostic results using a synthetic dataset with over 98% accuracy. This decentralized healthcare solution demonstrates early ovarian cancer detection and improved patient outcomes by combining predictive capability with privacy preservation. 2025 IEEE. -
Non-Invasive Detection of Ovarian Cancer using Biosensors Framework with Machine Learning and Federated Learning Techniques
Ovarian cancer is a leading cause of death worldwide, frequently diagnosed at advanced stages due to the lack of effective early screening methods. This work proposes a non-invasive cancer diagnostics utilizing amperometric electrochemical biosensors in early cancer detection from biological fluids, such as urine-based by combination of specific biomarkers like HE4 and Ca125, which are closely associated with ovarian cancer. This study approach integrates machine learning models to work with biosensor data for cancer classification tasks, and federated learning methods to ensure patient data privacy. The proposed system achieves diagnostic results using a synthetic dataset with over 98% accuracy. This decentralized healthcare solution demonstrates early ovarian cancer detection and improved patient outcomes by combining predictive capability with privacy preservation. 2025 IEEE. -
Kamla Chowdhry (19202006)
Kamla Chowdhry played a pivotal role in the development of management education and industry relations in India, beginning her career at the Ahmedabad Textile Industry Research Association (ATIRA). As head of the Psychology division, she transformed workplace dynamics in the textile mills of Ahmedabad through her research on workers lives, enhancing stakeholder relations and productivity. Chowdhry was the first faculty member at the Indian Institute of Management Ahmedabad (IIMA), where she designed the influential Programme for Management Development. She held prestigious positions, including the Hindustan Lever Professor of Management Practices and was among the first women appointed to Harvard Business School as visiting faculty. Following her tenure at IIMA, Chowdhry served as an advisor for the Ford Foundation and led the National Wastelands Development Board, contributing significantly to sustainable development initiatives and serving on key commissions related to forestry and the environment. 2025 selection and editorial matter, Braj Bhushan; individual chapters, the contributors. -
Level of green computing based management practices for digital revolution and New India /
International Journal of engineerig And Advanced Technology, Vol.8, Issue 3, pp.133-136, ISSN No: 2249-8958. -
Quality of Life of Indian Youth during 3rd Year of COVID-19 Pandemic
COVID-19 adversely impacted the overall well-being of the youth like others. Perceived Quality of Life (QoL) is one of the determinants of the effective involvement of youth in their studies and career success. No Indian study reported on the QoL of youth. Given this background, the present study attempted to examine the perceived QoL of Indian Youth during 3rd year of COVID-19 pandemic and its association with their background, perceived stress, worries, online teaching mode and physical activities. Seven hypotheses were formulated for verification. Data were collected using a specially designed Structured Questionnaire and WHO QoL Questionnaire after ascertaining the face validity. A group of 334 youth aged between 21-24 participated in the online study (Mean age: 22.51; SD: 2.154). Findings disclosed that the overall QoL of 19.16% (64/334) of youth was poor, while it was average for 19.16% (64/334) and high for 20.7% (69/334) youth. However, male and female youth differed significantly with respect to physical QoL only (p < 0.000). The youth who perceived stress from attending continuous online classes and staying at home had lower scores in all four domains of QoL (p < 0.001). The findings also confirmed an association between worries about future careers and catching COVID-19 and QoL. The effectiveness of the online teaching mode and clarification of queries were positively associated with QoL (p < 0.001). Interestingly, social support from family members and friends and physical exercise were found to be stress relieving and reflected in overall improved QoL (p < 0.001). The study's findings talk about promoting physical activities and introducing institution-based mental health support facilities for the youth who lack support facilities. The Author(s) 2025. -
Happiness, Meaning, and Satisfaction in Life as Perceived by Indian University Students and Their Association with Spirituality
The present study aims to examine the association between various dimensions of psychological well-being (subjective happiness, satisfaction, and meaning in life), spirituality, and demographic and socioeconomic background of university students. A total of 414 postgraduate students were selected from three different schools, viz. science, management, and social sciences/humanities of Pondicherry University (A Central University), Puducherry, India, following multistage cluster sampling method. One semi-structured questionnaire and four standardized psychological scales, viz. subjective happiness scale, satisfaction with life scale, meaning in life questionnaire, and spirituality attitude inventory, were used for data collection after checking psychometric properties of the scales. The results show that a positive significant correlation between spirituality and subjective happiness exists. Spirituality is also correlated with meaning in life and satisfaction with life scale. Statistically, no significant gender difference was observed with respect to subjective happiness, meaning, and satisfaction in life as well as spirituality although the mean score of female students was more in all the four psychological domains. Non-integrated students are found to be happier than integrated students, and statistically it was significant. Positive interpersonal relationship and congenial family environment were probed to be facilitating factors for positive mental health of university students. There is a severe need to address students mental health by every educational institution through multiple programs. 2019, Springer Science+Business Media, LLC, part of Springer Nature. -
Doctoral Research by Youth: Analyzing the Role of Socio-Demographic Variables on Flourishing and Grit
The study examines the importance of socio-demographic variables like age, gender, family environment, and relationship with parents and friends in deter-mining non-cognitive traits such as flourishing and grit, during the tenure of doctoral research. The cross-sectional correlational study comprises 400 Ph.D. scholars from a Central University in India, who were given a personal data sheet, the Flourishing Scale and the Grit Scale, for assessment. The results of the F-test showed that flourishing was significantly related to age, family environment and relationship with friends, and grit was significantly related to family environment and relationship with friends. Analysis using Pearson correlation found a weak correlation between flourishing and the three subscales of grit, namely ambition, consistency of interest, and perseverance of effort. Findings suggest that the socio-demographic variables are important contributors in the long-term goal-oriented behaviors and that flourishing and grit are two related but not correlated variables that influence completion and attrition of the doctoral research. The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2023. -
Youth of North East States of India: Issues, Concerns and Need for Mental Health Support as Perceived by NCC Officers
The youth of North-East India are in disadvantaged situations as compared to youth from the rest of the country in all respects. The objective of this article was to examine the views of the NCC Officers of North-East states about youth welfare in the region as they have first-hand experience in dealing with youth. Participants views were obtained on-line, by using a Semi-structured Questionnaire in the form of Google Form. A group of 142 NCC Officers provided feedback. Data collected were subjected to thematic analysis. Findings disclosed that youth of North-East states experience a range of challenges including poverty, lack of internet facilities, inability to attend NCC camps due to ongoing classes, substance dependence, lack of guidance and support leading to dropout and lack of values. The NCC Officers opined that a good number of North-East youths require mental health support and career guidance, in addition to mental health awareness. 2023 Taylor & Francis Group, LLC. -
School corporal punishment, family tension, and students internalizing problems: Evidence from India
There is considerable evidence that parental corporal punishment (CP) is positively associated with childrens behavioral and mental health problems. However, there is very little evidence addressing whether CP perpetrated by teachers or school staff is similarly associated with problematic student functioning. To address this gap in the research literature, data were collected from students in a locale where school CP continues to be widely practiced. Participants were 519 adolescents attending public or private schools in Puducherry, a city in eastern India. Students completed surveys assessing school CP, internalizing problems, social support, and resilience. The results indicated that 62% of the students reported experiencing school CP in the past 12 months, with males and those attending public schools being significantly more likely to report school CP than females and those in private schools. Youth who reported school CP reported more anxiety and depression. That relation was more pronounced in youth who reported family tension. Social support and resilience did not moderate the relations. The findings add to the substantial evidence about negative associations regarding the use of CP but in a new venuethe school, and provide some evidence for the need to change how students are disciplined in schools in India and elsewhere. 2016, The Author(s) 2016. -
Cloud computing security for public cloud using ciphers and queueing petri nets
Cloud computing is the most used word in the domain of Information Technology, which is making colossal differentiations in the IT business. Nowadays, a massive proportion of data is being made, and the masters are discovering better approaches for managing this data. In a general sense, the word cloud implies a virtual database that stores immense data from various clients. There are three sorts of cloud public, private and hybrid. A public cloud is fundamental for general customers where customers can use cloud benefits free or by paying. Private cloud is for explicit associations, and hybrid one is in a broad sense a mix of both. Cloud offers diverse kind of administrations, for instance, IAAS, PAAS, SAAS where administrations like a stage for running any application, getting to the enormous information extra room, can use any application running under the cloud are given. The cloud similarly has a shortcoming concerning the security for the data warehouse. In a general sense, public cloud is inclined to data modification, data hacking and therefore, the integrity and privacy of the data are being undermined. Here in our work our motive is to verify the information that will be taken care of in the public cloud by using the multi-stage encryption. The estimation that we have proposed is a mix of Rail Fence cipher and Play Fair cipher. 2020, IJSTR.