Current Issue

Volume: 12 Issue: 3 March 2026

A STUDY ON CONSUMER LOYALTY: WHY CONSUMERS STICK TO THE APPLE BRAND

Area of research: MARKETING

This Study Focuses On Understanding The Strategic Objectives Aimed At Building A Strong And Sustainable Business Model. The Primary Objective Is To Deliver A Seamless Ecosystem Experience That Integrates Products, Services, And Customer Interactions Into A Unified And Convenient Platform. The Study Also Emphasizes Maintaining High Product Quality And Continuous Innovation To Meet Evolving Consumer Expectations And Remain Competitive In The Market. Furthermore, It Highlights The Importance Of Creating A Strong Brand Identity And Building Customer Trust, Which Are Essential For Long-term Loyalty And Business Growth. By Analyzing These Objectives, The Study Aims To Explore How An Organization Can Enhance Customer Satisfaction, Strengthen Market Positioning, And Achieve Sustainable Development Through Quality, Innovation, And Trust-based Relationships.

Author: Dr.Vadivel M | Thiruselvam M

Volume: 12 Issue: 3 March 2026

NYKAA’S MARKETING MIX AND ITS EFFECT ON CONSUMER CHOICES

Area of research: MARKETING

This Study Examines Nykaa’s Marketing Mix And Its Effect On Consumer Choices In The Competitive Beauty And Personal Care Industry. Nykaa Has Emerged As One Of India’s Leading Online And Offline Beauty Retailers By Effectively Implementing The 4Ps Of Marketing—Product, Price, Place, And Promotion. The Research Analyzes How Nykaa’s Wide Product Range, Competitive Pricing Strategies, Strong Online Presence, And Influencer-driven Promotional Campaigns Influence Consumer Purchasing Decisions. The Study Also Explores Factors Such As Brand Trust, Product Authenticity, Convenience, Discounts, And Personalized Recommendations. Data Collected Through Surveys And Secondary Sources Interpretation Primary Data Indicate That Digital Marketing, Social Media Engagement, And Customer-centric Strategies Significantly Impact Consumer Preferences And Brand Loyalty. The Findings Suggest That Nykaa’s Well-integrated Marketing Mix Plays A Crucial Role In Shaping Consumer Perceptions And Driving Repeat Purchases. This Study Provides Insights Into How Strategic Marketing Decisions Influence Buying Behavior In The Growing Online Skincare And Cosmetics Market.

Author: Dr.Vadivel M | S.Sowmiya

Volume: 12 Issue: 3 March 2026

Curiosity To Comfort: Cultural Adaptation And Consumer Trust In KFC

Area of research: MARKETING

This Research Investigates How Cultural Adaptation Influences Consumer Trust Toward KFC In India. While Initial Interactions With The Brand Are Largely Driven By Curiosity And Global Appeal, Sustained Acceptance Depends On Cultural Comfort And Perceived Reliability. The Study Analyses How Localized Menus, Culturally Sensitive Practices, And Consistent Service Quality Contribute To Trust-building Among Consumers. Primary Data Were Collected From 120 Respondents Through A Structured Questionnaire And Analysed Using Percentage Analysis, Ranking Analysis, And Likert Scale–based Weighted Averages. The Results Demonstrate That Cultural Familiarity And Hygiene Perception Significantly Enhance Consumer Confidence And Repeat Patronage. The Study Concludes That KFC’s Success Lies In Its Ability To Integrate Global Branding With Local Cultural Expectations, Transforming Curiosity-driven Trials Into Long-term Consumer Comfort.

Author: Harish V | Dr D Sharon

Volume: 12 Issue: 3 March 2026

A Study On The Impact Of Lifestyle And Awareness On Food Choices Of College Students

Area of research: MARKETING

Food Habits Among College Students Are Undergoing A Rapid Transformation, Shaped By Academic Pressure, Urban Lifestyles, Technological Influence, And Increasing Independence In Food Choices. This Transitional Phase Of Life Marks A Critical Period Where Young Adults Move Away From Home-cooked Meals Toward Convenience-based And Commercially Prepared Foods. The Present Study Explores The Evolving Dietary Patterns Of College Students, Focusing On Meal Regularity, Food Preferences, Nutritional Awareness, And The Impact Of Social And Environmental Factors. It Highlights How Factors Such As Time Constraints, Peer Influence, Digital Food Delivery Platforms, And Stress Contribute To Irregular Eating Habits And Nutritional Imbalance. While Students Increasingly Prioritize Taste, Affordability, And Convenience, Health Considerations Often Take A Secondary Role. The Study Emphasizes The Long-term Implications Of These Habits On Physical Health, Mental Well-being, And Academic Performance. By Examining The Changing Relationship Between Young Minds And Their Food Choices, This Research Aims To Draw Attention To The Need For Nutritional Awareness And Institutional Support To Encourage Healthier Eating Practices Among College Students.

Author: Dr W Saranya | Ms R Arbutha

Volume: 12 Issue: 3 March 2026

Zonevo: Low-Cost Collaborative Smartphone-Based Urban Vehicle Collision Detection And Navigation System

Area of research: Intelligent Transportation Systems

Urbanization Has Led To A Rapid Increase In Vehicle Density, Resulting In Frequent Road Congestion And Accidents. According To Global Traffic Studies, A Significant Percentage Of Urban Accidents Occur Due To Delayed Reaction Time, Blind Spots, And Lack Of Situational Awareness. Advanced Driver Assistance Systems (ADAS) Have Been Introduced To Reduce Accident Rates. These Systems Use Hardware Sensors Such As LiDAR And Radar To Detect Obstacles And Nearby Vehicles. Although Effective, These Systems Are Costly And Mostly Limited To High-end Vehicles. In Contrast, Smartphones Have Become Ubiquitous And Contain Advanced Sensing And Communication Capabilities. These Devices Can Continuously Monitor Location, Velocity, Orientation, And Motion Patterns. Leveraging These Built-in Sensors For Collaborative Vehicle Safety Presents An Affordable Alternative To Traditional Hardware-dependent Systems. The Primary Objective Of This Research Is To Design And Implement A Low-cost Smartphone-based Collaborative System That Enhances Urban Vehicle Safety Without Requiring Additional Hardware Installations.

Author: Srikumaran S | Sam Stephen S | Sanjai G | Ranjith Kumar S | PRADEEP K (Mentor)

Volume: 12 Issue: 3 March 2026

Smart Healthcare Appointment And Disease Prediction System

Area of research: Artificial Intelligence And Machine Learning In Healthcare

The Rapid Advancement Of Artificial Intelligence (AI) And Machine Learning (ML) Technologies Has Significantly Transformed Various Domains, Particularly The Healthcare Sector. Early Disease Detection And Timely Medical Consultation Play A Crucial Role In Reducing Mortality Rates, Treatment Costs, And Healthcare Burden. However, Many Individuals Delay Hospital Visits Due To Lack Of Awareness, Limited Accessibility, Long Waiting Times, Or Uncertainty Regarding The Severity Of Symptoms. This Gap Highlights The Need For Intelligent, Accessible, And Integrated Healthcare Assistance Systems. This Paper Presents A Smart Healthcare Disease Prediction And Appointment System Using Machine Learning, A Web-based Application Designed To Provide Preliminary Medical Diagnosis Support And Seamless Doctor Appointment Scheduling Within A Unified Platform. The Proposed System Leverages Supervised Machine Learning Algorithms Trained On Structured Symptom-disease Datasets To Predict Possible Diseases Based On User-input Symptoms And Demographic Attributes Such As Age And Gender. The Prediction Engine Computes Probability Scores For Multiple Disease Classes And Identifies The Most Probable Condition Along With A Confidence Percentage. Additionally, The System Displays The Top Three Predicted Diseases To Enhance User Awareness And Informed Decision-making. To Further Enhance Reliability, The System Incorporates A Risk Classification Mechanism That Categorizes Predicted Diseases Into Low, Medium, And High Risk Levels Based On Model Confidence And Disease Severity. Unlike Traditional Symptom Checker Applications That Provide Only Textual Suggestions, The Proposed Platform Integrates A Complete Appointment Management Module. Users Can View Available Doctors Categorized By Specialization, Book Appointments Directly After Prediction, And Maintain Structured Appointment History Records. The System Is Implemented Using Python, Flask Framework, And A Relational Database For Secure Data Storage And Session Management. The Modular Architecture Ensures Scalability And Extensibility For Future Integration With Hospital Management Systems, Chatbot Assistance, And Mobile Applications. Experimental Evaluation Demonstrates Reliable Prediction Performance And Smooth System Functionality. The Proposed Solution Contributes Toward Enhancing Digital Healthcare Accessibility, Reducing Unnecessary Hospital Visits, And Supporting Early-stage Medical Decision-making Through Intelligent Automation.

Author: JanarthananV | JananiPriyaV | ShamlinThisha J | Abirami R

Volume: 12 Issue: 3 March 2026

Agri-Guard: An AI-Based Smart Agricultural Surveillance System Using YOLOv8 For Real-Time Object Detection

Area of research: Artificial Intelligence And Smart Agriculture

Crop Damage Caused By Wild Animals, Birds, And Unauthorized Human Intrusion Remains A Major Challenge In Modern Agriculture. Traditional Monitoring Approaches Such As Manual Supervision, Fencing, And Static Alarm Systems Are Often Inefficient, Labor-intensive, And Unable To Provide Continuous Protection. This Paper Presents Agri-Guard, An AI-powered Smart Agricultural Surveillance System That Leverages Real-time Computer Vision And Deep Learning For Automated Detection And Deterrence Of Threats In Farmland Environments. The Proposed System Utilizes The YOLOv8 Object Detection Model For Identifying Humans, Animals, And Birds From Live Camera Feeds. Video Streams Are Processed Using OpenCV, And Detections Are Handled Through A FastAPI-based Backend Architecture. Upon Detecting A Threat, The System Triggers Intelligent Alert Mechanisms, Records Evidence, And Logs Detection Data Into A Structured Database For Monitoring And Analysis. Experimental Evaluation Demonstrates That The System Achieves High Detection Accuracy With Low Latency, Making It Suitable For Real-time Agricultural Deployment. The Modular Architecture Ensures Scalability, Hardware Extensibility, And Integration With IoT-based Deterrent Mechanisms Such As Lights, Alarms, And Laser Systems.

Author: DHARUN A | AKASH SARAVANA SINGH R | REDONE RAJ S | AKASH G | Dr P Shenbagavalli (GUIDE)

Volume: 12 Issue: 3 March 2026

LUNG TUMOR SEGMENTATION USING VISUAL GEOMETRY GROUP NETWORKS IN MRI IMAGES

Area of research: Electronics And Communication Engineering

Lung Cancer Is One Of The Most Life-threatening Diseases Worldwide, And Early Diagnosis Significantly Increases The Chances Of Survival. Accurate Detection And Classification Of Lung Tumors Remain Challenging Due To Variations In Tumor Size, Shape, And Texture In MRI Images. This Study Proposes An Automated Lung Tumor Segmentation And Classification Framework Using Convolutional Neural Networks (CNN) And The Visual Geometry Group (VGG) Network Architecture. The Proposed System Utilizes MRI Images To Analyze Textural And Spatial Features Of Lung Tissues For Distinguishing Between Normal And Malignant Cases. A Multi-scale Feature Extraction Approach Is Incorporated To Improve Detection Performance And Enhance Classification Accuracy. The VGG Network Serves As The Base Model For Deep Feature Learning, While CNN Layers Refine Segmentation And Classification Tasks. The Developed Database Includes Multiple MRI Views To Ensure Robust Training And Validation. Experimental Results Demonstrate That The Proposed Model Achieves High Precision And Overall Classification Accuracy Of Up To 98%, As Evaluated Using Confusion Matrix Metrics. The System Reduces Manual Interpretation Errors And Provides An Efficient Computer-aided Diagnostic Tool For Early Lung Tumor Prediction.

Author: Mrs.M.Geethalakshmi, Nithish S | Nithish S | Gokul K

Volume: 12 Issue: 3 March 2026

A Study On Effects Of Television Advertisement On Consumer Buying Behaviour

Area of research: Marketing

Television Advertising Plays A Significant Role In Shaping Consumer Buying Behavior By Influencing Awareness, Attitudes, And Purchase Decisions. This Study Examines The Effect Of Television Advertisements On Consumers By Analyzing How Visual Appeal, Message Content, Repetition, Celebrity Endorsements, And Emotional Elements Impact Buying Intentions. Television Advertisements Act As A Powerful Communication Tool That Not Only Informs Consumers About Products And Services But Also Persuades Them By Creating Brand Recall And Positive Perceptions. The Study Highlights That Frequent Exposure To Television Advertisements Increases Product Familiarity And Trust, Which In Turn Affects Consumers’ Preferences And Choice Of Brands. Moreover, Advertisements Targeting Emotions And Lifestyles Are Found To Be More Effective In Motivating Impulse Buying And Brand Loyalty. The Findings Suggest That Television Advertising Continues To Be An Influential Factor In Consumer Decision-making, Despite The Growth Of Digital Media, And Remains A Crucial Strategy For Marketers To Attract, Influence, And Retain Consumers In Competitive Markets.

Author: Dr W Saranya | Mr. B L Santosh

Volume: 12 Issue: 3 March 2026

Opaline Attachment Defense System For Proactive Detection And Sanitization Of Malicious Email Files

Area of research: Information Technology

Email Attachments Remain A Primary Vector For Phishing And Malware Attacks, With Traditional Signature-based Defences Struggling Against Zero-day Threats. This Paper Introduces Opaline, A Proactive Defence System That Leverages Deep Learning Models Like RoBERTa To Analyse Textual Semantics And Structural Features In Attachments Such As PDFs And Documents, Achieving Early Detection Before User Interaction. By Integrating Sandbox Isolation And Automated Sanitization—converting Suspicious Files Into Safe Static Previews—Opaline Minimizes Risks While Preserving Workflow Usability, Offering A Practical Advancement Over Resource-heavy Existing Solutions.

Author: Mrs. M.Radhika | G.Ashika | Shreya Agrawal | T.Sruthik