Volume 14 | Issue 4 |

 Abstract

This study explores how mental health professionals in India perceive the influence of gender on mental health concerns and therapeutic practice. Recognising gender as a significant social determinant of psychological experiences, the study examines how therapists interpret and engage with gender-related factors within clinical settings. A quantitative, cross-sectional design was employed using a structured online questionnaire administered to 28 mental health professionals, including psychologists, counsellors, and psychotherapists. The instrument assessed perceptions of gender differences in mental health, help-seeking behaviour, and therapeutic practice using Likert-scale items. Data were analysed using descriptive statistics. The findings indicate that mental health professionals widely recognise the role of gender in shaping psychological distress, coping styles, and help-seeking patterns. Participants also demonstrated strong awareness of the mental health challenges faced by gender-diverse individuals and broadly endorsed the importance of gender-sensitive approaches in therapeutic outcomes. However, variability was observed in the extent to which gender is consistently integrated into therapeutic practice, particularly in relation to professional training and preparedness. The study suggests that while awareness of gendered dimensions of mental health is evident, their systematic integration into therapeutic practice remains uneven, highlighting the need for more structured engagement with gender within professional training and clinical frameworks.

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Gender; Mental health; Help-seeking behaviour; Gender-sensitive practice; Mental health professionals; India; Gender diversity

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

The accelerating shift towards digital platforms for commerce and education has exposed significant limitations in user experience and engagement. While Augmented Reality (AR) presents a compelling solution, its adoption has historically been impeded by the need for standalone applications. This paper introduces the Phase 2 design and implementation of an AI-Powered WebAR Virtual Try-On & Learning Platform. Our advanced system leverages Supabase for real-time cloud data management and integrates OpenAI's capabilities for predictive product recommendations and generative 3D interactions. By utilizing WebGPU and Three.js, the platform delivers high-fidelity 60 FPS rendering directly within the browser, entirely bypassing app installations. Empirical evaluations demonstrate that our predictive recommendation model achieves an accuracy of 90.4%, while rendering optimizations maintain Motion-to-Photon (MTP) latency below the critical 16 millisecond threshold to prevent cybersickness. With a System Usability Scale (SUS) score averaging 76.6, the results validate that this cloud-native, AI-driven architecture is highly effective for solving practical challenges in both e-commerce and interactive education.

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

WebAR, Virtual Try-On, Artificial Intelligence, Supabase, OpenAI Integration, Cloud Computing, Three.js, WebGPU, Predictive Modeling, Interactive Education, Spatial Computing, System Usability Scale.

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Creative Commons Attribution 4.0 and The Open Definition

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The Freedom Fighters of Undivided Chitradurga District: 1800-1947 explores the remarkable yet often overlooked contributions of Chitradurga in India's struggle for independence. Situated in central Karnataka, the district was home to a diverse array of freedom fighters, ranging from the valiant Nayaka rulers who resisted early British annexation to local reformers, peasant leaders, and activists inspired by the Indian National Congress. Over nearly one and a half centuries, these individuals participated in armed uprisings, civil disobedience, and non-violent movements, reflecting the region's enduring spirit of resistance. Their efforts not only challenged colonial authority but also fostered political consciousness and social reform among the local populace. By documenting the lives, struggles, and achievements of these fighters, this study highlights Chitradurga's significant role in shaping Karnataka's and India's broader nationalist history, emphasizing the interplay between local leadership, grassroots mobilization, and the pan-Indian independence movement.

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Chitradurga, Freedom Fighters, Indian Independence Movement, Nayaka Rulers, Peasant Uprisings, Civil Disobedience, Quit India Movement, Non-Violent Resistance, Local Leadership, Colonial Resistance

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Abstract: The emotional stability of trainee teachers significantly impacts their teaching performance and personal well-being. This research explores how emotional adjustment varies among trainee teachers, focusing on gender differences and self-efficacy levels. Data was collected from 700 trainee teachers across multiple teacher training institutions. Data were collected from B.Ed Colleges by using standardized questionnaire. The tool used for 'Teachers adjustment inventory scale' was developed by Singh and Sinha 2018. Teacher's Self-Efficacy scale by Sood and Sen (2017). Key findings indicate female prospective teachers have superior 'Emotional Adjustment' as compared to male prospective teachers. Gender (A) and self-efficacy level (B) of prospective teachers has a significant joint effect on 'emotional adjustment'. The study underscores the need to foster emotional resilience and self-efficacy in trainee teachers to boost their teaching effectiveness.

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

: Emotional Adjustment, Self- efficacy, Prospective teachers, Gender

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Academic stress has been a major problem among college students, and it tends to result in psychological distress including depression and anxiety. This paper looks at the connection between academic stress, social support and mental health outcomes in college students, as well as whether social support is a buffering variable. It was based on the quantitative correlational research design, and 150 students of the college aged 18-25 took part in the study using standardized tools, such as the Academic Stress Scale, Multidimensional Scale of Perceived Social Support, Beck Depression Inventory, as well as Generalized Anxiety Disorder Scale.

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Academic stress, Social support, Depression, Anxiety, College students

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

This research presents the design and implementation of an AI-powered data analysis chatbot that enables users to interact with structured datasets using natural language queries.

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Artificial Intelligence, Data Analysis, Chatbot, Local LLM, Django, RAG, Pandas, Natural Language Processing

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Employee attrition is a big problem for companies around the world, causing issues with how they run and manage their money. Traditional machine learning methods work to some extent, but they usually don't offer enough accuracy or clarity to be useful in making real-world decisions about human resources. This paper introduces a framework that uses a neural network and includes SHAP analysis to predict and explain why employees leave, based on the IBM HR Analytics dataset. The model uses specially designed features, balances the classes with SMOTE, and applies dropout regularization. The system's results show it is correct about 82% of the time, has a ROC-AUC score of 0.73, finds 57% of the actual cases, and has an F1-score of 50%. SHAP analysis shows that working overtime, how much money someone makes each month, and how happy they are with their job are the top factors that predict if someone will leave their job, giving HR managers useful information to take action

Licence: creative commons attribution 4.0

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Employee Attrition Prediction, Neural Networks, SHAP Explainability, Human Resource Analytics, Imbalanced Classification

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Abstract: This study examines the effectiveness of digital learning platforms in IT companies with respect to employee training, skill development, and productivity. The research adopts a descriptive research design and collects primary data through a structured questionnaire from 120 IT employees. Statistical tools such as frequency and percentage analysis, reliability analysis, and crosstab analysis are used to interpret the data. The findings indicate that digital learning platforms significantly improve employee skills, enhance productivity, and provide flexible learning opportunities. However, challenges such as technical issues, lack of time, and limited interaction affect learning effectiveness. The study concludes with recommendations to improve usability, personalization, and engagement in digital learning systems.

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Digital Learning, Employee Training, Learning Management, E-learning, Skill Development.

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

The provision of care to patients that live far away or are old-age continues to be an immense challenge from a logistics perspective. For this study, we have developed a localized version of the HealthCare Lite system, which will monitor patient vitals through the use of the ESP32-WROOM-32. This includes the use of the DS18B20 to monitor body temperature, the MAX30105 to monitor blood oxygen levels and heartbeat, and the AD8232 to detect ECG signals. The MPU6050 will be used to detect falls. All this information will then be transmitted to Firebase and, in case of emergencies, the SIM800L will send text messages.

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

IoT, ESP32, Health Monitoring System, Wearable Sensors, Heart Rate Monitoring, SpO? Measurement, ECG Signal Processing, Temperature Sensing, GSM Communication, Wireless Sensor Network

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Communication Signal Intelligence(COMSIGINT) involves the interception, processing, and analysis of communication signals such as radio frequency (RF), wireless transmissions, radar signal s, and satellite communications. Traditional machine learning approaches in this domain rely heavily on labeled datasets, which are often scarce, expensive, and impractical to obtain due to the complexity and dynamic nature of communication environments. Self-Supervised Learning (SSL) has emerged as a powerful paradigm that enables models to learn meaningful representations from large volumes of unlabeled data. This paper presents a comprehensive study of SSL techniques applied to communication signal intelligence, including contrastive learning, autoencoders, and predictive modeling. Furthermore, the paper discusses system architectures, practical applications, advantages, challenges, and future directions. The results indicate that SSL significantly enhances scalability, adaptability, and performance in modern signal intelligence systems

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Self-Supervised Learning, COMSIGINT, RF Signals, Representation Learning, Contrastive Learning, Autoencoders, Signal Processing.

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Creative Commons Attribution 4.0 and The Open Definition