Volume 13 | Issue 11 | November 2025

 Abstract

Oral hygiene plays a vital role in general health, yet many users fail to maintain optimal routines due to time constraints, inconvenience, and fragmented product ecosystems. This paper presents the design and prototyping of a modular oral care cabinet that integrates brushing, water flossing, UV-C sterilization, and ozonated rinsing into a single compact system. A user-centered approach involving surveys, ergonomic studies, and prototyping was employed. The final design features a shared brush-flosser trunk, embedded UV chamber, integrated ozonated water tank, and modular compartments. The concept enhances hygiene, convenience, and sustainability in daily routines. The system's intelligent integration ensures better hygiene while supporting eco-friendly practices. The article presents concept development, technical considerations, and testing outcomes, offering insights into its potential for market viability and user acceptance.

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 Keywords

Oral health, modular design, UV sterilization, ozone therapy, sustainability, product integration, water flosser, overall oral care.

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

In today's digital era, a smartphone has become highly essential in communication, finance management, and even entertainment. This very fact of growing dependency on them has also increased their vulnerability in terms of cyber threats. Among these, Android devices are much susceptible to malware, phishing, spyware, ransomware, and unauthorized data access that threatens user privacy, data integrity, and system reliability. The following paper proposes a Mobile Threat Detection and Resolution App that will offer intelligent proactive protection against mobile-based threats. The system will incorporate both static and dynamic analysis techniques to efficiently detect known and unknown malware. In performing a static analysis, the system will check application permissions, certificates, and manifest files; whereas dynamic analysis will include monitoring network traffic, active running processes in the background, and access requests. Upon detection of any potential threat, its automated resolution module isolates or removes the malicious entity from within without requiring user interference. It also comprises a phishing link verification module and a report generation system to give the user an informative view about detected threats and safety recommendations. Real-time monitoring, by means of a lightweight design and user-friendly dashboard, empowers the app to enhance mobile security without affecting system performance. Experimental evaluation reveals its effectiveness in terms of high detection accuracy with low resource consumption and rapid response time compared with traditional antivirus tools.

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 Keywords

Mobile security, threat detection, phishing link analysis, suspicious APK detection, Android application, static and dynamic analysis, cybersecurity, malware prevention, secure mobile computing.

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Object recognition in underwater environment is extremely difficult because of problems like color distortion, light scattering, and decreased visibility. A hybrid approach that combines Multicolor Space Residual Networks (MCRNet) with Swin-YOLO fusion to increase object recognition accuracy and underwater image quality. Swin Transformer uses self-attention techniques to extract multi-scale hierarchical features, whereas MCRNet uses residual learning and different color spaces (RGB, HSV, and Lab) to restore texture details and correct color distor- tions. By efficiently improving feature representations, the Swin- YOLO fusion improves YOLOv8's real-time object identification capabilities. According to experimental findings, the suggested strategy works noticeably better than stand-alone techniques, which makes it a viable option for marine applications and underwater research.

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 Keywords

Underwater Image Enhancement, Object Detec- tion, MCRNet, Swin Transformer, YOLOv8, Multi-Color Space Processing, Feature Fusion, Deep Learning, Computer Vision, Marine Applications

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Adolescence is a critical developmental stage characterized by rapid physical, cognitive, and emotional changes that often expose individuals to stress and emotional instability. Parental and family influences play a central role in shaping adolescents' capacity to manage stress and develop emotional intelligence (EI). This study explores the dynamic interaction between family environment, parenting styles, emotional support, and the stress management competencies of adolescents. Drawing on psychological and sociological frameworks, the paper highlights how positive family functioning and emotional communication contribute to enhanced resilience, emotional awareness, and regulation among youth. The findings underscore the necessity of strengthening family-based interventions and parent-adolescent communication to promote mental health and emotional well-being.

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 Keywords

Adolescents, Emotional Intelligence, Stress Management, Parenting, Family Environment, Emotional Regulation

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

analytics based on machine learning (ML) is transforming data-driven decision making in a variety of sectors by helping businesses anticipate trends, streamline processes, and improve strategic planning. The main elements of predictive analytics--data collection, preprocessing, feature engineering, model selection, and performance optimization--are examined in this essay. Applications in manufacturing (predictive maintenance and quality control), supply chain management (route Predictive optimization and inventory planning), retail and e-commerce (customer behavior analysis and demand forecasting), healthcare (disease prediction and personalized treatment), and finance (fraud detection and risk assessment) are highlighted. Notwithstanding its disruptive promise, issues including model interpretability, data quality, and ethical considerations need to be resolved. Future developments in explainable AI (XAI), big data integration, and AI-powered automation will spur innovation in business world.

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HEALTH DATA ANALYTICS: PREDICT DISEASE AND IMPROVE PATIENT CARE USING MACHINE LEARNING

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 Abstract

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Flexible work, Organizational support, Employee well-being, Hybrid work, Mental health.

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The postmodern feminism revolves around the ideas of inclusivity and individual experiences; breaking the gender norms, rejecting the conventional roles, and redefining social standards set for women. The novel, Mrs. Draupadi Kuru portrays the similar themes by bringing in the female characters from Mahabharata to the present day world. Their journey and exploration in the modern world make them to redefine their identity by self reflecting their trauma and experiences of their past life in the present day life. This paper explores the postmodern feminist ideals in the novel by identifying the progress and change in the characters and how they redefined their identity and their life's based on their choice. Foucault's perception about power, role of media, discourse and the social construction helps to analyse the text to highlight how power is operated by the means of discourse and how femininity is socially constructed. Luce Irigary, Judith Butler and Helen Cixous focuses on the identity, patriarchy, discourse and culture and this paper reflects their key concepts by analysing the text.

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 Keywords

Feminism, Identity, Redefine, Inclusivity, Gender.

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Creative Commons Attribution 4.0 and The Open Definition

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This article endeavors to study the image of New Woman in Indian Scenario. The new woman was a feminist ideal that emerged in the late 19th century and had a profound influence well into the 20th century. In 1984, Irish writer Sarah Grand in her article.'The New Aspect of the Woman Question.' It was a Henry James who developed the phrase 'New Woman' when he used it to describe American emigrant living in Europe.

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Emergence of New Woman in Indian Scenario

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Introduction: Smartphones bring many benefits when used for the basic intended purposes, but excessive use of smartphones might turn problematic and consequently, impairs well-being, negatively impacts academic performance, and leads to various psychological and physical complications among adolescents. 1 To create awareness about smart phone addiction among nursing students the researcher conducted the study "Prevalence of smartphone addiction and its relation with sleep of nursing students of a selected nursing institution in Kolkata, West Bengal." The objectives were to identify the prevalence rate of smart phone addiction, to assess the sleep status and to find out the relationship between smart phone addiction and insomnia among nursing students. Methodology: The research approach adopted was a non-experimental descriptive survey design. The study was conducted in a selected nursing Institution of Kolkata with sample size 110. Non probability consecutive sampling technique was used. The tools used were personal information, Smart phone addiction scale- SV, and Bergen insomnia scale (BIS) for data collection. The techniques used for data collection were questionnaire through online. Result: The findings showed 30.90% participants addicted to smart phone; 90% participants were found to spend 0-5 hours daily on screens. 55.46% students admitted to using their smartphone for at least 30 minutes after the lights were turned off, and 56.63% kept their smartphone near their pillow while sleeping. The insomnia among nursing students revealed 60.91%. Smartphone addiction had significant positive correlation with insomnia (r= 0.32). Conclusion: Future research can be built upon these findings and further investigation and intervention can be done. Addressing the problems proactively and awareness and precaution can enhance academic outcomes and student's health and balance in their life.

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 Keywords

Smart phone addiction, sleep

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

This research presents a fully implemented, end-to-end smart energy monitoring system integrating machine learning, a real-time backend service, and a Flutter-based mobile application. The system utilizes the publicly available COMBED dataset to simulate real-time smart meter readings at 30-second intervals via WebSocket streaming. Four machine learning models--KMeans clustering, Isolation Forest anomaly detection, LSTM short-term forecasting, and ARIMA long-term forecasting--enable comprehensive energy analysis including pattern recognition, anomaly alerts, and multi-horizon predictions. A FastAPI backend provides REST endpoints and WebSocket support with model inference latency below 100 ms. The Flutter application delivers a mobile-first dashboard with real-time charts, anomaly lists, bill estimation in INR, and forecast visualizations. Twilio SMS integration provides automated alerts for critical anomalies. This work distinguishes itself from prior literature through complete implementation, real-time simulation using open datasets, mobile-first architecture, and deployable multi-model integration. The system is reproducible, scalable, and extendable to real IoT smart meter hardware.

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Smart Meters, Energy Monitoring, Machine Learning, Anomaly Detection, Time-Series Forecasting, Flutter, FastAPI, COMBED Dataset, IoT Analytics, Sustainable Computing

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Creative Commons Attribution 4.0 and The Open Definition