Volume - 11 Issue - 6

Area of research: Civil Engineering

The Increasing Demand For Clean Water And The Rising Pollution Levels In Aquatic Systems Have Intensified The Need For Effective Wastewater Treatment Methods. This Research Focuses On The Application Of Sugarcane Bagasse-derived Biochar As A Cost-effective And Eco-friendly Adsorbent. Biochar Was Synthesized At 400°C, 500°C, And 600°C Via Pyrolysis And Characterized Using Advanced Techniques Such As BET For Surface Area, SEM For Surface Morphology, FTIR For Functional Group Analysis, And TGA For Thermal Stability. Batch Experiments Revealed That Biochar Produced At 600°C Demonstrated Optimal Removal Efficiency For Ammonia And Methylene Blue From Synthetic Wastewater. Adsorption Kinetics Followed The Pseudo-second-order Model, And Isotherm Studies Confirmed Both Monolayer And Heterogeneous Adsorption Mechanisms. The Findings Support The Potential Of Sugarcane Bagasse Biochar As An Effective Material For Water Remediation Applications.

Author: Lisa Anto L

Area of research: Mechanical Engineering

Radio Frequency Identification (RFID) Technology Already Plays A Major Role In Many Areas. One Of The Applications Is For Object Detection. RFID Is Used For Effective Object’s Identification. A Good Example Is Object Detection At Storage Management System. It Is Applicable To The Environment Where People Easily Forget The Places Of The Stored Object. In The Other Hand, The Automatic Object Detection Will Be Useful For People Like Store Maintenance Person And Consumer Such That They Need Information Before Pick Up And Store Object While Doing Their Daily Life Activities. The Proposed Confined Space Trolley With A Digital Safety Notification System, Leveraging RFID Technology, Focuses On Its Innovative Features Related To Tool Monitoring, Tool Tracking, And Emergency Response Capabilities. The System Employs RFID Tags To Monitor Tools, Providing Real-time Data On Their Presence Or Absence On The Trolley. Additionally, RFID Facilitates Precise Tracking Of The Tools' Entry And Exit Times, Ensuring A Comprehensive Record Of Their Usage. The Integration Of An Emergency Button Further Enhances Safety By Allowing Immediate Alerts To Be Triggered In Critical Situations. This Abstract Highlights The System's Capacity To Streamline Tool Management, Minimize The Risk Of Missing Tools, And Precisely Record Tool-related Activities. Overall, The Proposed Solution Not Only Prioritizes Personnel Safety Within Confined Spaces But Also Introduces Efficiency In Tool Monitoring And Emergency Responsiveness, Making It A Holistic And Valuable Addition To Confined Space Operations.

Author: G.Narayanasamy | R.Boopathi

Area of research: CSE

Every Country Has Seen An Increase In Motorcycle Accidents Over The Years Due To Social And Economic Differences As Well As Regional Variations In Transportation Circumstances. One Common Mode Of Transportation For Those In The Middle Class Is A Motorbike. One Of The Leading Causes Of Road Accidents That Result In Fatalities Nowadays. Among Them, Motorcycling Accidents Are Common And Can Cause Severe Injuries. A Motorcycle Rider's Helmet Is One Of The Most Important Components Of Safety. But Many People Choose To Ignore The Recommendation To Wear A Helmet. In Current Situation, We Come Across Various Problems In Traffic Regulations In India Which Can Be Solved With Different Ideas. Riding Motorcycle/mopeds Without Wearing Helmet Is A Traffic Violation Which Has Resulted In Increase In Number Of Accidents And Deaths In India. Existing System Monitors The Traffic Violations Primarily Through CCTV Recordings, Where The Traffic Police Have To Look Into The Frame Where The Traffic Violation Is Happening, Zoom Into The License Plate In Case Rider Is Not Wearing Helmet. But This Requires Lot Of Manpower And Time As The Traffic Violations Frequently And The Number Of People Using Motorcycles Is Increasing Day-by-day. What If There Is A System, Which Would Automatically Look For Traffic Violation Of Not Wearing Helmet While Riding Motorcycle/moped And If So, Would Automatically Extract The Vehicle’s License Plate Number. Recent Research Have Successfully Done This Work Based On CNN, R-CNN, LBP, HoG, HaaR Features, Etc. But These Works Are Limited With Respect To Efficiency, Accuracy Or The Speed With Which Object Detection And Classification Is Done. In This Research Work, A Non-Helmet Rider Detection System Is Built Which Attempts To Satisfy The Automation Of Detecting The Traffic Violation Of Not Wearing Helmet And Extracting The Vehicles' License Plate Number. The Main Principle Involved Is Object Detection Using Deep Learning At Three Levels. The Objects Detected Are Person, Motorcycle/moped At First Level Using YOLOv2, Helmet At Second Level Using YOLOv3, License Plate At The Last Level UsingYOLOv2. Then The License Plate Registration Number Is Extracted Using OCR (Optical Character Recognition). All These Techniques Are Subjected To Predefined Conditions And Constraints, Especially The License Plate Number Extraction Part. Since, This Work Takes Video As Its Input, The Speed Of Execution Is Crucial. We Have Used Above Said Methodologies To Build A Holistic System For Both Helmet Detection And License Plate Number.

Author: ANGOTH LAKSHMAN | M. Madhu Vinay | P. Kalyani | V. Deepthi | M.Upendra

Area of research: CSE

Distributed Network Disruptions, Often Termed Distributed Denial Of Service (DDoS) Attacks, Exploit Vulnerabilities In System Infrastructures, Such As Web Servers Of Legitimate Organizations. Traditional Research Has Predominantly Utilized Outdated Datasets Like The KDD Dataset, Which May No Longer Represent The Evolving Nature Of Modern Threats. To Address This Gap, The Present Study Employs A Contemporary Dataset And Machine Learning Techniques To Identify And Forecast Various Forms Of DDoS Attacks.This Research Implements A Comprehensive Detection Framework Using Two Advanced Classification Algorithms: Random Forest And XGBoost. The UNSW-NB15 Dataset, Obtained From A GitHub Repository, Served As The Foundation For Training And Testing, While Python Was Used For Simulation And Model Deployment.Performance Evaluation Was Conducted Using A Confusion Matrix. In The First Experiment, The Random Forest Model Achieved A Precision And Recall Of 89%, With An Overall Accuracy Of 89%, Indicating Robust Performance. In The Second Test, The XGBoost Classifier Slightly Outperformed, Attaining Approximately 90% In Both Precision And Recall, With An Accuracy Of 90%.Compared To Previous Studies, Which Reported Lower Accuracy Rates Of 85% And 79%, The Proposed Methodology Demonstrates A Significant Enhancement In Identifying And Classifying DDoS Attacks, Offering A More Effective And Modern Solution To A Growing Cybersecurity Concern.

Author: Vooradi Sandya | B. Kinshu | D.Vithin Sai | M. Nanda Varma

Area of research: Child Health

Weaning Is The Process Of Introducing Supplementary Foods To The Babies From 6 Month In Addition To Breast Milk. Weaning Starts With Introduction Of Supplementary Food And Continues Until The Child Is Taken Off From Mother’s Milk. Mother’s Milk Alone Is Not Suitable To Give Needed Quantum Of The Essential Nutrients Demanded To Maintain Growth After The 6 Months. Weaning Food Should Be Wisely Chosen To Meet The Nutritive Need Of Baby And Maintain Growth. Effective Weaning Requires Maternal Knowledge And Practice. This Study Employed A Quantitative Approach With Descriptive Survey Design, Data Collection Done Through Interview Method To Assess The Weaning Practice And Structured Questionnaires Were Also Used To Find The Knowledge Level From 105 Samples. Results Showed That The Overall Maternal Knowledge Mean Score Is 18.11+3.37, Also Explored High Correlation Between Knowledge And Practice Score (p = 0.9457). Result Of The Study Handed Information That Maximum Number Of Mothers Had Good Knowledge About Weaning. The Findings Flash Lights To The Need For Educational Intervention Program In Empowering Maternal Knowledge And Skill In Weaning.

Author: Dayana Fernandez | Dr. J. Jayabharathi | N. Yogamangalam

Area of research: Mechanical Engineering

This Project Involves Designing And Making A Pneumatic-operated Automatic Machine Vice. It Is Used To Automatically Hold A Work-piece During Machining And Release It Once The Process Is Done. The System Is Controlled By A Programmed Microcontroller. An IR Sensor Detects The Presence Of A Work-piece And Sends A Signal To The Microcontroller. The Microcontroller Then Activates The Pneumatic System, Causing The Jaws To Hold The Work-piece. This Setup Reduces The Need For Manual Labor, Improves Accuracy, And Saves Time.

Author: Venkatesh Mutthada | R. Surya Kiran

Area of research: Artificial Intelligence

In Healthcare Sector ,specially In The Field Of Medical Imaging ,Artifical Intelligence (AI) Is Bringing Significant Changes. Imaging Methods Like CT Scans, X-rays, And MRIs Produce Large Volumes Of Visual Information That Require Accurate Interpretation For Proper Diagnosis. Traditionally, Radiologists Manually Analyze These Images, Which Can Be Time-intensive And Susceptible To Errors. AI Technologies—especially Deep Learning And Convolutional Neural Networks (CNNs)—are Now Being Used To Automate This Process, Improving Diagnostic Precision And Reducing The Time Needed For Analysis. This Study Explores The Growing Role Of AI In Interpreting Medical Images, With A Focus On Its Impact On CT Scans, X-rays, And MRI Evaluations. It Highlights Major Technological Developments, Clinical Case Studies, And AI's Effectiveness In Identifying Issues Such As Tumors, Bone Fractures, Lung Infections, And Brain-related Disorders. The Paper Also Discusses Challenges Such As Data Reliability, Algorithmic Transparency, And Regulatory Limitations In Clinical Practice. Ultimately, The Research Emphasizes That AI Serves As A Supportive Tool For Radiologists, Enhancing Decision-making And Patient Care, Rather Than Replacing Human Judgment. The Paper Outlines Present-day Applications, Existing Obstacles, And Potential Future Directions For AI In This Domain.

Author: Shweta Mandavkar

Area of research: Library Automation Software

This Article Compares SOUL 2.0 And SOUL 3.0 Library Automation Software Module By Module, Looking At Their Main Features, Upgrades, And New Functionalities. Major Modifications Have Been Made To The Information And Library Network (INFLIBNET) Centre Software For University Libraries (SOUL) Between Versions 2.0 And 3.0. Every New Version Is Assessed Using Critical Modules Like Acquisition, Catalogue, Circulation, Serial Control, Administration, And OPAC/Web OPAC. The Study Finds That SOUL 3.0 Is More In Line With Worldwide Standards, Better For Users, And Works With Modern Library Technologies Such As RFID And Mobile Access. The Main Objective Of The Study Is To Assist Research And Educational Institutions Decide If SOUL 3.0 Is The Appropriate Upgrade For Them In Terms Of Operational Efficiency And The Distribution Of Digital Services.

Author: Mr. Ganesh Sagare | Dr. Vaishali S. Khaparde

Area of research: Civil Engineering

Author: Mr. Jadhavar Harshvardhan | Mr. Sukale Suurabh | Mr. Jadhav Shreyash | Ms. SayyedA.H. | Dr. R.N.Shiral

Area of research: CSE

A Modern-day Self-sustaining Car Determines Its Driving Method By Means Of Thinking About Solely Exterior Factors (Pedestrians, Street Conditions, Etc.) Barring Thinking About The Interior Circumstance Of The Vehicle. To Overcome Above Problems,in This Paper Author Proposed A New Strategy Ie A Driving Decision Strategy(DDS) Based On Machine Learning For An Autonomous Vehicle” Analysis Of Both External And Internal Factors Determines The Optimal Strategy For An Autonomous Vehicle (consumable Conditions, RPM Levels Etc.). To Implement This, The Project Author Has Introduced And Algorithm Called DDS (Driving Decision Strategy) Algorithm Which Is Based On Genetic Algorithm To Choose Optimal Gene Values Which Helps In Taking Better Decision Or Prediction. DDS Algorithm Obtained Input From Sensor And Then Passes To Genetic Algorithm To Choose Optimal Value Which Helps In Faster And Efficient Prediction. Propose DDS With Genetic Algorithm Performance Is Comparing With Existing Machine Learning Algorithm Such As Random Forest And MLP (multilayer Perceptron Algorithm.). Propose DDS Shows Better Prediction Accuracy Compareto Random Forest And MLP. (multilayer Perceptron Algorithm.)

Author: Bukya Mohanbabu | P. Stephen Kamal | B.Sruthi | B. Koushik

Area of research: CSE

The Rapid Evolution Of Artificial Intelligence (AI) Has Introduced New Threats And Expanded Existing Vulnerabilities. This Article Reviews The Malicious Use And Abuse Of AI, Constructing A Typology Of Threats. Four Types Of Malicious Abuse Of AI Are Identified: Integrity Attacks, Unintended AI Outcomes, Algorithmic Trading, And Membership Inference Attacks. Additionally, Four Types Of Malicious Use Of AI Are Highlighted, Social Engineering, Misinformation, Hacking, And Autonomous Weapon Systems. Enhanced Collaboration Is Vital To Minimize Risks And Avoid Harmful Consequences.

Author: Veerender Aerranagula | R.satish | A.yogi manikanta | K.deveena

Area of research: CSE

Adverse Effects In Clinical Trials Pose Serious Health Risks And Financial Burdens. Predictive Algorithms For Side Effects Can Mitigate These Issues By Informing Early Drug Development. The LINCS L1000 Dataset, With Its Extensive Drug-perturbed Gene Expression Data, Is A Valuable Resource For Such Predictions. However, Many Current Methods Only Use A Limited Subset Of High-quality Experiments, Overlooking Much Of The Data. This Study Leverages The Full LINCS L1000 Dataset And Evaluates Five Deep Learning Architectures. A Multi-modal Model Combining Drug Chemical Structure (CS) And Gene Expression (GEX) Shows Superior Performance Among MLP-based Methods, With CS Features Proving More Informative. Additionally, A CNN Using Only SMILES Representations Achieves The Best Overall Results, Improving Macro-AUC By 13.0% And Micro-AUC By 3.1% Over Existing Approaches. The Model Also Identifies Previously Unreported Drug-side Effect Associations Found In The Literature.

Author: Murali Kanthi | V. Gunali | V. Sainath | B. Shankar Naik

Area of research: Transportation Engineering

As Per IRC Recommendation, California Bearing Ratio (CBR) Value Of Subgrade Is Used Of Flexible Pavements. California Bearing Ratio(CBR)value Is An Important Soil Parameter For Design Of Flexible Pavements And Runway Of Air Fields. It Can Also Be Used For Determination Of Sub Grade Reaction Of Soil By Using Correlation. It Is One Of The Most Important Engineering Properties Of Soil For Design Of Sub Grade Of Roads. CBR Value Of Soil May Depends On Many Factors Like Maximum Dry Density (MDD), Optimum Moisture Content (OMC), Liquid Limit (LL), Plastic Limit (PL), Plasticity Index (PI), Type Of Soil, Permeability Of Soil Etc. Besides, Soaked Or Unsoaked Condition Of Soil Also Affects The Value. These Tests Can Easily Be Performed In The Laboratory. The Estimation Of The CBR Could Be Done On The Basis Of These Tests Which Are Quick To Perform, Less Time Consuming And Cheap, Then It Will Be Easy To Get The Information About The Strength Of Sub Grade Over The Length Of Roads, By Considering This Aspect, A Number Of Investigators In The Past Made Their Investigation In This Field And Designed Different Pavements By Determining The CBR Value Of The Basis Of Results Of Low Cost, Less Time Consuming And Easy To Perform Tests. In This Study, Attempts Have Been Made To Seek The Values Of CBR Of Different Soil Samples And Correlate Their CBR Values For The Design Purpose Of Flexible Pavement As Per Guidelines Of IRC: 37-2012.

Author: V. Venkatesh | Vadapalli Hemanth Kumar

Area of research: Finance

This Study Analyzes The Financial Performance Of Elevator Industry Over A Five-year Period Using Ratio Analysis And Comparative Financial Statements. The Analysis Covers Profitability, Liquidity, Solvency, And Efficiency, Offering A Comprehensive Evaluation Of The Company's Financial Health. The Research Is Based On Secondary Data Collected From The Company’s Annual Reports And Financial Statements. The Findings Reveal Fluctuating But Generally Improving Financial Performance, Supported By Strong Liquidity And Moderate Profitability Growth In The Final Year. The Study Provides Valuable Insights For Stakeholders, Including Management, Investors, And Creditors.

Author: Anjitha KB | Mr. A Balasubramanian

Area of research: Computer Science And Engineering

The Study Aims To Harness The Capabilities Of Existing CCTV Networks To Improve The Crowd Management, Enhance The Crime Prevention, Andoptimize The Workplace Monitoring Using Artificial Intelligence (AI) And Machine Learning (ML) Techniques. By Integrating Intelligent Analytics With Current Surveillance Systems, We Seek To Create A Comprehensive Solution That Will Address An Urban Safety Challenges And Operational Inefficiencies Without The Need For Substantial New Infrastructure Investments. In The Realm Of Crowd Management, The Study Will Employ Real-time Video Analytics To Monitor Public Spaces During Events, Ensuring Effective Crowd Flow And Reducing The Risk Of Overcrowding. Machine Learning Algorithms Will Analyse Foot Traffic Patterns And Predict Potential Congestion Points, Enabling Authorities To Intervene Proactively And Manage Crowds More Effectively. This Not Only Enhances Public Safety But Also Improves The Overall Experience For Attendees At Large Gatherings. For Crime Prevention, The Study Will Focus On Developing AI-driven Surveillance Capabilities That Can Detect Suspicious Behaviours And Identify Potential Threats. Utilizing Advanced Techniques Such As Facial Recognition And Anomaly Detection, The System Will Learn From Historical Crime Data To Pinpoint High-risk Areas And Predict Criminal Activities. By Providing Law Enforcement With Actionable Insights, The Studyaims To Facilitate Timely Responses And Foster A Safer Community. In The Context Of Workplace Monitoring, The Integration Of AI With CCTV Footage Will Allow Organizations To Gain Valuable Insights Into Employee Productivity And Compliance With Safety Protocols. By Analysing Workplace Dynamics And Movement Patterns, Businesses Can Identify Operational Bottlenecks, Enhance Resource Allocation, And Ensure Adherence To Safety Measures. This Data-driven Approach Not Only Promotes A Culture Of Accountability But Also Drives Operational Efficiency. Overall, This Studyenvisions A Smarter, Safer Urban Environment And More Efficient Workplace Dynamics Through The Strategic Use Of Existing CCTV Networks Powered By AI And ML. The Anticipated Outcomes Include Improved Public Safety, Reduced Crime Rates, And Enhanced Organizational Productivity, Ultimately Benefiting Communities And Businesses Alike.

Author: Mr. B. Ramji | Makam Sahithi | Puchakayala Bharath | Lagishetti Shiva Krishna

Area of research: Transportation Engineering

Fillers Play An Important Role On Engineering Properties Of The Bituminous Paving Mixes. Conventionally, Cement, Lime And Stone Dust Are Used As Fillers. In This Study, An Attempt Has Been Made To Assess The Effects Of Different Types Of Fillers (e.g. Non-conventional And Conventional) On The Marshall Properties Of Bituminous Paving Mixes. For This Purpose, Non-conventional Fillers Such As Groundnut Shells And Silica Fume And Conventional Fillers Such As Cement And Stone Dust Were Used. All Of These Materials Were Tested According To The Standard Test Procedure Of AASHTO. Test Specimens Were Prepared By Using Different Types Of Filler Having Different Amount In The Mix Of 5% To 7.5%. The Marshall Properties Obtained For Both Types Of Fillers Reveal That, Nut Shells And Silica Fume Specimens Have Been Found To Exhibit Higher Stability Value Compared To Cement And Stone Dust Filler Specimens. In Addition, Mixers Containing Nut Shells And Silica Fume As Filler Showed Maximum Stability At 6.5 % Bitumen Content And The Percentage Of Air Voids Were Found To Be Decreased With The Increase Of Bitumen Content. This Do Research Has Influence Of Conventional And Inexpensive Fillers Such As Walnut Shells And Silica Fumes In Bituminous Concrete Flooring. As A Result Of This Project It Has Been Found That Bituminous Mixtures Containing These Unconventional Loads Produce Satisfactory Properties

Author: Kona Venkata Appa Rao | M.Gowri

Area of research: Community Health Nursing

Author: M. Prabu | Dr. Kanchana

Area of research: LIFE SCIENCE

Millets Are A Group Of Small, Nutritious Grains That Have Been A Staple Food For Thousands Of Years, Particularly In Asia And Africa.Kodo Millet (Paspalum Scrobiculatum) Is An Incredibly Nutritious Grain That Offers A Wide Range Of Health Benefits. Rich In Essential Nutrients, It Is An Excellent Source Of Complex Carbohydrates, Dietary Fibre, And High-quality Protein .They Belong To The Grass Family And Are Grown In Various Forms, Including Pearl Millet, Finger Millet, And Foxtail Millet. The Growing Interest In Functional Foods Has Fueled The Demand For Chocolate That Incorporates Healthy Ingredients Like Millet. Chocolate And Millet, Two Foods With Rich Histories And Unique Benefits, Are Now Being Combined To Create Innovative And Healthy Snack Options. When Combined With Chocolate, A Universally Loved Treat, Millet Offers A Unique Opportunity To Make A More Health-conscious And Sustainable Chocolate Product . Combining These Two Ingredients Creates A Product That Not Only Satisfies Sweet Cravings But Also Offers Functional Health Benefits. In Recent Chocolate-millet Bars And Snacks Are Becoming Popular For Their Ability To Provide A Steady Energy Release And Also Offers Environmental Benefits.Hence, The Current Research Aimed In The Formulation And Standardization Of Kodo Millet Chocolate With The Numerous Health Benefits Of Millet, Creating A Snack That Not Only Satisfies The Taste Buds But Also Contributes To A Healthier, More Sustainable Lifestyle.

Author: Mrs.D.Thenmozhi | A.Swetha

Area of research: NANOMATERIALS

Barium Titanate (BTO) Is An Inorganic Compound.The Solid Exists In One Of Four Polymorphs Depending On Temperature.Production And Handling Properties.Uses Of Barium Titanate.Oxides, Sulfides, And Alkoxides

Author: R. Rajalakshmi

Area of research: Artificial Intelligence And Recommender Systems In Smart Tourism.

Tourism Has Evolved Significantly With The Integration Of Artificial Intelligence (AI),enabling Smarter And More Efficient Travel Planning. This Research Presents An AI-powered Web-based Tourist Planning Application Designed To Enhance Personalized Travel Experiences Through Intelligent Recommendations. The System Employs Machine Learning Algorithms, Natural Language Processing (NLP), And Real-time Data Analytics To Analyze User Preferences, Historical Data, And Emerging Trends. By Leveraging These Technologies, The Application Provides Customized Suggestions For Destinations, Accommodations, Activities, And Itineraries, Optimizing The Travel Experience Based On Individual Needs. Additionally, The Platform Incorporates User Feedback To Continuously Refine Its Recommendations, Ensuring Improved Accuracy And Relevance Over Time. This Paper Explores The Architectural Design, Methodologies, Benefits, And Challenges Associated With Implementing Such A System In The Tourism Industry, Highlighting Its Potential To Revolutionize Digital Travel Planning.

Author: Saurabh Shukla | Darshana Patil

Area of research: Fraud Detection In Insurance

One Major Issue Facing The Banking Industry Is Insurance Fraud., Leading To Substantial Monetary Losses And Increased Premiums For Honest Policyholders. Traditional Rule-based Fraud Detection Systems Struggle To Adapt To Evolving Fraudulent Tactics, Necessitating The Adoption Of Machine Learning (ML) Techniques For More Effective Fraud Detection. This Research Explores An ML-powered Fraud Detection Framework That Leverages Supervised And Unsupervised Learning Models To Identify Fraudulent Claims With High Accuracy. To Enhance Trust And Transparency, Explainability Strategies Like LIME (Local Interpretable Model-agnostic Explanations) And SHAP (Shapley Additive Explanations) Are Combined., Allowing Investigators To Interpret Model Predictions. The Study Examines Various ML Algorithms, Evaluates Their Performance Using Real- World Insurance Datasets, And Demonstrates How Explainability Improves Decision-making By Offering Information On Fraud Patterns. Our Findings Suggest That An Explainable ML Approach Not Only Enhances Fraud Detection Rates But Also Reduces False Positives, Ensuring Fair Claim Processing. This Research Contributes To The Field Of Financial Fraud Detection By Presenting An Interpretable And Adaptive ML-driven Solution That Balances Accuracy, Efficiency, And Transparency.

Author: Nilesh Gupta | Shalini Gupta

Area of research: Management Studies

This Study Investigates The Prevailing Health And Welfare Measures Adopted For Employees Within The Retail Sector. With The Retail Industry Being One Of The Largest Employment Generators, Ensuring The Well-being Of Its Workforce Is Vital For Sustainable Growth. This Paper Examines Key Components Of Employee Welfare—both Statutory And Non-statutory—including Health Benefits, Safety Protocols, Employee Assistance Programs, And Workplace Ergonomics. The Research Highlights Challenges, Gaps In Policy Implementation, And The Perception Of Employees Regarding Current Welfare Measures. The Findings Suggest That While Some Initiatives Exist, A Comprehensive And Inclusive Approach To Health And Welfare Is Still Lacking In Many Retail Enterprises.

Author: Sravya R | Dr.M.Govinda Solai

Area of research: FINANCE

The Digital Marketing Industry, Has Shown Rapid Evolution In Recent Years, Driven By Technological Advancements And Increased, Internet Penetration. This Paper Aims To Study The Growth Trajectory And Financial Sustainability Of Digital Marketing Agencies, Especially In The Post-pandemic Era. The Study Analyzes Key Financial Indicators, Revenue Models, Operational Efficiency, And Client Acquisition Strategies. The Research Is Based On Primary Data Collected From Selected Agencies And Secondary Data From Industry Reports. The Results Highlight That Sustainable Growth Depends On Strategic Investments In Technology, Talent, And Analytics-driven Marketing.

Author: MANJIMA M | BALASUBRAMANIAN A

Area of research: Civil Engineering

Concrete Buildings Are Facing Some Serious Issues Around The World. There Are A Few Reasons For This, Natural Disasters Such As Earthquakes, Lack Of Knowledge About Important Building Codes, And Poor Supervision During Construction. Because Of These Problems, Many Buildings Are Weaker Than They Should Be. If These Structures Are Under Too Much Weight, They Can Bend And Corrode, Which Means Immediate Repairs Are Needed. To Tackle These Problems With Reinforced Concrete, Repair And Strengthening Methods Have Become Really Important In Construction Today. Even New Buildings Sometimes End Up Needing Fixes Because Of Design Mistakes Or Problems During Building. Structures That Have Been Damaged By Unexpected Events Like Fires Or Earthquakes Need Special Techniques To Make Them Strong Again. Fixing Up Buildings Helps Protect Them From Earthquakes And Reduces The Risk Of Damage. It’s All About Boosting A Building’s Strength To Meet Safety Standards. Many Studies Have Looked Into Effective Ways To Reinforce Them. This Paper Will Take A Brief Look At Some New And Cost-effective Methods For Repairing Damaged Buildings.

Author: Prof. Pawar Akshay S | Prof. Ghadage Nilesh R

Area of research: Environmental Engineering

Recent RO Water Purification Is Common Method Used For Drinking Water. This Method Is Very Simple And Gives Us Clean And Pure Water By Blocking All Contaminants. Then The RO Systems Are Very Compact And It Require Very Little Space And The Maintenance Of The System Is Very Simple. Some Of The Advantages Of RO Systems Are It Does Not Any Harmful Or Costly Chemicals For The Treatment, Energy Requirement For This Process Is Very Low Compare With The Other Water Treatment Methods And This System Is Fully Automated No Need For Manual Operations. But It Removes All The Essential Minerals Content Form The Water. Major Source For Minerals Are Drinking Water If We Drink The RO Water For Continuous Period Of Time Leads To The Deficiency Of The Minerals That’s Essential For Our Bones. To Overcome This Problem Cissus Quadrangularis (veld Grape) Is Used In The RO Membrane To Get The Mineral Ions That Present In It. Which Is Used To Heal The Bones As Well As Strengthen Our Bones. In This Report, Test Reports Shows That The Increase In Mineral Content As Well As Medicinal Properties Like Flavonoids While The RO Water Is Treated With Our Cissus Quadrangularis Membrane. Amount Of Calcium Is Increased From 22mg/l To 151.3mg/l Sodium Content Is Increased To 2.12 Mg/l And The Total Flavonoids Content Is 10mg/ml. From This Study Cissus Quadrangularis Is Used As A Low Cost Membrane And Used As A Good Source For Minerals And Medicinal Properties. Based On The Study, Cissus Quadrangularis Can Be Considered As Low Cost, Locally And Freely Abundantly Available, Eco-friendly For Drinking Water Purposes.

Author: K .Boopathi | S. Sakthivel | V. Indhumathi

Area of research: SAFETY ENGINEERING

Today We Use Highly Durable Materials In Our Day To Day Life. Some Material Used For Manufacturing Of Mechanical Components And Infrastructure Projects Require High Strength And Durability. To Make A Component Highly Durable Heat Treatment Is Done To Fulfil The Requirement Of Particular Needs Of A Component. The Heat Treatment Process Increases The Strength Of The Material By Modifying Their Metallurgical Properties. In Heat Treatment Facility, The Fire Hazards Are Comparatively High And Even A Single Fire Accident May Be Catastrophic Due To The Congested And Complex Layout Of The Facility. This Study Proposes A Novel Methodology For Modelling The Impact Of A Fire Event In A Heat Treatment Facility. Hazard Identification And Accident Credibility Assessment Have Been Used To Discover The Most Credible Fire Accident Scenarios. These Scenarios Have Been Simulated Using Computational Fluid Dynamics (CFD) Code, Fire Dynamics Simulator (FDS). The Results Have Then Been Compared To Identify The Most Severe Impact Of The Fire On Personnel And Assets Using Thermal Radiation And Risk Levels. It Has Been Found That The Fire Event In Scenarios Has A High Potential To Cause Damage To Adjacent Assets. From This Comparison, It Is Evident That The Scenario In The Fuel Storage And Transmission Pipe Lines In The Combustion Process Have The Highest Risk Of Fire To Both Personnel And Assets. The Proposed Methodology May Be Adapted Further For Safety Measure Design To Mitigate Or Avoid The Impacts Of A Fire Event In Any Complex Processing Facility.

Author: S. Varunbhirabhu

Area of research: Farmer Producer Organisation

Farmer Producer Organizations (FPOs) Are Evolving As A Changing Power India’s Agricultural Economy, Predominantly In The Backbone State-Punjab. The Main Aim To FPOs Is To Empower The Small And Marginal Farmers By Enhancing Their Socio-economic Status Through Nurturing Collective Farming, Easy Access To Markets, And Allowing Better Price Realization. The Present Study Is Based On Content Analysis Of Secondary Data Sources And Reports. The Significant Efforts Are Made By Central And State Government For Establishing FPOs With The Support Of NABARD And Other Agencies. The Evolution Of FPOs In Punjab Faces Several Challenges, Including Limited Infrastructure, Poor Market Linkages And Group Leadership, Low Farmer Awareness, And Dependence On Outdated Farming Techniques. This Study Critically Scrutinizes The Current Status, Policy Interventions From 2014-2024, Challenges, And Opportunities For FPOs In Punjab, Contribution Of Group Leaders’ Insights On Working Of FPOs. Recommendations Are Suggested For Bracing The FPO Network In Punjab, Guaranteeing Long-term Progress And Socio-economic Upliftment For Growers.

Author: Dr. Manveer Singh

Area of research: Civil Engineering

Highway Construction Projects Are Capital-intensive, With Equipment Management Playing A Pivotal Role In Determining Project Efficiency, Cost-effectiveness, And Timely Completion. This Thesis Investigates The Enhancement Of Operational Efficiency In Highway Construction Through Strategic Equipment Management Practices. By Analyzing Current Industry Approaches, The Study Identifies Inefficiencies Such As Equipment Downtime, Underutilization, And Suboptimal Maintenance Schedules, Which Contribute To Delays And Cost Overruns. The Research Proposes A Comprehensive Framework Integrating Advanced Technologies, Data-driven Decision-making, And Optimized Resource Allocation To Address These Challenges.

Author: Vaibhav Sonone | Pranav Lende

Area of research: Computer Application

Kidney Cancer Remains A Serious Health Threat Worldwide, With Many Cases Undetected Until Reaching Advanced Stages, Leading To Reduced Survival Rates. Factors Like Limited Awareness And Insufficient Diagnostic Resources Contribute To High Mortality, Especially In Regions With Restricted Healthcare Access. This Project Presents A Predictive System Designed To Support Early Detection Of Kidney Cancer By Analyzing Clinical And Demographic Data Through Machine Learning. Models Such As Logistic Regression And Neural Networks Were Utilized To Estimate Cancer Risk, Yielding High Accuracy In Detection. By Leveraging Data From Diverse Patient Groups, The System Aims To Provide Healthcare Professionals With A Reliable Tool For Identifying Kidney Cancer At Earlier Stages, Facilitating Timely Intervention And Improving Patient Outcomes. Evaluation Of The Models Was Based On Standard Accuracy Metrics, Ensuring Robustness And Broad Applicability. Future Work Will Focus On Enhancing Model Stability And Integrating It Into Clinical Settings, Positioning This System As A Vital Resource In Early Kidney Cancer Diagnosis And Management.

Author: Abhijeet Tiwari | Tushar Umbarkar

Area of research: Nursing

Gestational Diabetes Mellitus (GDM), Defined As Glucose Intolerance First Identified During Pregnancy, Significantly Increases Risks Of Maternal And Neonatal Complications, Including Preeclampsia, Macrosomia, And Future Type 2 Diabetes. Despite Its Growing Prevalence—especially In India, Which Accounts For Nearly Five Million Cases Annually—awareness Among Pregnant Women Remains Alarmingly Low, Particularly In Socioeconomically Disadvantaged Populations.Objective:This Study Aimed To Assess The Awareness Levels Of GDM Among Pregnant Women In Urban And Semi-urban Regions Of Karaikal, India, And To Examine The Relationship Between Awareness And Key Sociodemographic Factors.Methods:A Cross-sectional Study Was Conducted Over Six Months At An Urban Hospital In Karaikal. A Pre-validated 25-item Questionnaire Covering GDM Risk Factors, Symptoms, Screening, Treatment, And Complications Was Administered To 400 Pregnant Women Attending Antenatal Clinics. Statistical Analyses, Including Chi-square Tests And Logistic Regression, Were Used To Evaluate Associations Between Awareness Levels And Demographic Variables.Results:Only 14% Of Participants Demonstrated Good Awareness Of GDM, While 33% Had Poor Awareness. Significant Associations Were Found Between Higher Awareness And Tertiary Education (OR 2.67, P=0.002) As Well As Urban Residence (OR 1.94, P=0.018). Knowledge Deficits Were Particularly Evident Regarding GDM Complications And Treatment.Conclusion:There Is A Critical Need For Targeted, Culturally Appropriate Antenatal Education Programs Focusing On GDM Awareness, Especially For Women With Limited Education And Those In Rural Or Semi-urban Settings. Improving Maternal Health Literacy Could Enhance Early Detection And Management Of GDM, Thereby Reducing Both Immediate Obstetric Risks And Long-term Diabetes Burden In Mothers And Offspring.

Author: Dr.J.Jayabharathi | A.Priyadharshini | M.Anitha | T.Hemalatha

Area of research: Nursing

Pain In Labor Is Nearly A Universal Experience. Pregnant Women Commonly Worry About The Pain They Will Experience During Labor And Child Birth. During The First Stage Of Labor Uterine Contractions Cause Cervical Dilatation, Effacement And Uterine Ischemia (decreased Blood Flow And Therefore The Local Oxygen Deficit) Resulting From Contraction Of The Arteries To The Myometrium. During The First Stage Of Labor, Women Usually Perceive The Visceral Pain Of Diffuse Abdominal Cramping And Uterine Contractions. OBJECTIVES: To Assess The Pre-test Level Of Pain Perception Among Primigravida Mothers In Both Experimental Group I And Experimental Group -II ,To Assess The Effectiveness Of Lower Back Massage On Pain Perception Among Primi Gravida Mothers In Experimental Group –I ,To Assess The Effectiveness Of Deep Breathing Exercise On Pain Perception Among Primi Gravida Mothers In Experimental Group –II ,To Compare The Effectiveness Between Lower Back Massage And Deep Breathing Exercise Among Primi Gravida Mothers ,To Find Out The Association Between Pretest Score Of Pain Perception Among Primi Gravida Mothers With Selected Demographic Variables.MATERIALS &METHODS : Quantitative Approach With Pre Experimental Design (two Group Pre- Test And Post- Test) Was Adopted In This Study. Sixty (60) Primi Gravida Mothers Who Were In First Stage Of Labor With 4-7cm Cervical Dilatation Admitted At Government Maternity Hospital,Karaikal Were Selected As A Sample For The Study By Using Non-probability Purposive Sampling Technique. Sample Size Was 60 (30 In Experimental Group –I And 30 In Experimental Group –II).pre Test Was Conducted By Using Mc Caffery Numerical Pain Scale To Assess The Pain Perception .The Intervention For The Study In Experimental Group-I Lower Back Massage Was Given For 20 Mints Every One Hour Interval For Three Times And In Experimental Group –II Deep Breathing Exercise Was Given About 20 Mints For Every One Hour Interval For Three Times .Post Test Was Conducted Using The Same Tool As Used In Pre Test. Descriptive Statistical Methods Like Percentage, Mean, Standard Deviation Inferential Statistics Like Paired’ Test And Un-paired ‘t’ Test Was Used To Analyze The Collected Data.Results And Conclusion : Study Results Shows That, In Experimental Group –I The Calculated ‘t’ Value On Pain Perception Was 29.427 Which Is Highly Significant At P<0.05 Level And Calculated ‘and In Experimental Group –II ‘t’ Value On Pain Perception Was 16.000 Which Is Highly Significant At P<0.05 Level .The Present Study Revealed That Regarding Effectiveness Of Lower Back Massage And Deep Breathing Exercise On Pain Perception Calculated ‘t’ Value Is 5.616.Hence, This Study Concluded That Both Lower Back Massage And Deep Breathing Exercise On Pain Perception Was Effective On Reducing Labor Pain Perception First Stage Of Labor .But, Deep Breathing Exercise Was More Effective Than Lower Back Massage Based On The Calculated “t’ Value.

Author: Anitha M | Dr.J.Jayabharathi | Priyadharshini .A

Area of research: Computing In Science & Engineering

In Recent Years, Companies Have Been Overwhelmed By The Sheer Number Of Resumes They Receive For Every Job Posting. Many Of These Resumes Never Even Get Seen. The Truth? Recruiters Just Don’t Have Time To Read Through All Of Them. This Means That Even Qualified Candidates Sometimes Get Filtered Out, Just Because They Didn’t Use The Right Format To Fix This Problem, Our Project Introduces An AI-based Resume Screening And Enhancement Platform. It’s A Smart Tool That Can Read Resumes, Understand Job Descriptions, And Automatically Decide How Well The Two Match. It Uses Powerful Natural Language Processing (NLP) Algorithms And Machine Learning Models To Do This Comparison. But That’s Not Allit Also Suggests Improvements To The Resume, So The Candidate Has A Better Chance Of Getting Noticed. The System Assigns A Compatibility Score And Offers Real-time, Friendly Help Through An AI Chatbot. It’s Like Having A Virtual HR Assistant 24/7. With This Platform, Hiring Becomes Smarter, Quicker, And Fairerfor Everyone Involved.

Author: Mr. G. KARTHIK | Mrs. V. MAGESHWARI

Area of research: Computer Application

The Usage Of Passwordless Authentication Is Changing Digital Identification By Doing Away With Traditional Passwords, Which Have Long Been Susceptible To Phishing, Reuse, And Breaches. The Development Of It Is Documented In This Paper, Which Also Highlights Significant Technology Advancements And Adoption Drivers Including The Need For Flawless User Experiences And The Increase In Data Breaches. In Addition To Evaluating The Security Advantages And Implementation Difficulties, It Examines Enabling Technologies Such As Biometrics, Cryptographic Keys, And Device-based Authentication. In Addition To Examining New Trends Like AI-driven Behaviour Analytics And Decentralized Identification, The Study Draws On Academic Literature, Industry Whitepapers, And International Standards. The Results Are Intended To Serve As A Reference For Researchers, Cybersecurity Experts, And Legislators As They Develop Safe And User-friendly Authentication Methods.

Author: Yash Agrawal | Ashutosh Choudhary

Area of research: Electronics And Communication Engineering

Water Pollution Caused By Floating Debris And Inefficient Fish Feeding Methods Poses Significant Environment Challenges. This Project Proposes An Autonomous Boat Equipped With Machine Learning (ML),IoT,and Servo Motor To Address These Issues. The System Uses A Heigh-resolution Camera And ML- Based Object Detection To Identify And Collect Floating Debris.This Servo-controlled Debris Collection Mechanism And Automatic Feeded Work In Real Time , Adjusting Based On Environment Feedback.The ML Model Continuously Improves It's Accuracy Through Learning, Ensuring Efficient Debris Removal And Precise Feeding. This System Is Designed For Low- Cost,low Maintenance Operation, Offering And Ontegrated And Integrated Solutions To Improve Water Quality And Aquatic Ecosystem Health.

Author: B.Priyadharsini | M. Naveena | K. Madhasri | S. Revathi

Area of research: Computer Engineering And Information Technology

The Increasing Cases Of Counterfeit Products, Fake Sellers, And Misleading Pricing On E-commerce Platforms Have Made Online Shopping Risky For Consumers. This Paper Presents An AI-based System That Detects Fake Products, Verifies Authenticity, Compares Prices Across Platforms, And Assists Users Via A Chatbot. The System Ensures Transparency, Enhances Trust, And Promotes Informed Decision-making In Digital Commerce.

Author: K.Chandru | Mrs. S.Shirley | Mrs. V.Mageswari

Area of research: Water Pollution

Because The Ground Water In The Industrial Area From Lote M.I.D.C. Is Used For Drinking And Household Purposes, It Is Necessary To Undertake An Assessment Of Its Quality. The Local River Receives The Liquid Waste From The Several Factories. At One-month Intervals Throughout The Year, Water Samples Were Taken From Wells Located Throughout The Industrial Area. To Evaluate The Effect Of Industrial Wastes On Ground Water, The Following Parameters Were Estimated: PH, EC, Na+, Cl-, Ca2+, Mg2+, HCO, SAR, And RSC. The Findings Indicate That The Majority Of The Water Samples In This Investigation Fall Below The Acceptable Drinking Water Quality Guideline

Author: Dr. Shrikant Kekane | DR. SHRIKANT KEKANE

Area of research: Digital Wellness

A Non-experimental Descriptive Study To Assess The Level Of Internet Dependency And Effectiveness Of Structured Teaching Programme On Knowledge On Internet Dependency Among The Students In Aringar Anna Government Arts And Science College, Karaikal. The Demographical Data And The Clinical Data Were Collected By Using Young`s Internet Addiction Test (IAT) To Assess The Level Of Internet Dependency Among College Students. Assessment Of Level Of The Internet Dependency Among The College Students Show That 52% Of College Students Had Moderate Level Of Internet Dependency And 48% Of College Students Had Mild Level Of Internet Dependency. Structured Teaching Programme Was Effective In Pretest 66% Of Them Have Inadequate Knowledge,34% Have Moderate Adequate And None Of Them Had Adequate Knowledge Where As In Posttest 74% Adequate Knowledge And 24% Having Moderately Adequate Knowledge. This Shows The Effectiveness Of Teaching Programme Was Increased The Awareness About Ill Effects Of Internet Dependency. It Can State That Of College Students Had More Moderate Level Of Internet Dependency.

Author: R.Karthiga | T.Hemalatha | Dr.J.Jayabharathi

Area of research: Water Pollution

Because The Ground Water In The Industrial Area From Mahad M.I.D.C. Is Used For Drinking And Household Purposes, It Is Necessary To Undertake An Assessment Of Its Quality. The Area's Groundwater Is Under A Lot Of Stress, Which Is Being Caused By Heavy Industrialisation And Growing Urbanisation. Thus, The Current Study Evaluates The Groundwater Contamination Caused By Heavy Metals While Taking This Important Factor Into Account. At One-month Intervals Throughout The Year, Water Samples Were Taken From Wells Located Throughout The Industrial Area. The Atomic Absorption Spectrophotometer (Perkin Elmer Model No. Analyst 200) Was Used To Identify The Heavy Metals, Which Are Iron, Copper, Zinc, Manganese, Nickel, Chromium, Cobalt, And Lead. The Majority Of Groundwater Samples Have Heavy Metal Concentrations Below The Maximum Allowable Limit, According To A Comparison Of The Results With WHO (1993) And BIS (1991) Recommendations.

Author: Shrikant Kekane

Area of research: Civil Engineering

The Engineering Characteristics Of Broad Soils, Particularly Black Textiles Soil (BCS), Present Substantial Challenges In Construction For Civil Engineering As A Result Of Their High Plasticity, Low Shear Strength, And Substantial Volume Changes Due To Moisture Fluctuations. Researchers Have Increasingly Concentrated On Environmentally Conscious And Cost-effective Stabilisation Techniques That Utilise Agricultural And Industrial Refuse In Order To Address These Constraints And Advance Sustainable Development. This Review Investigates The Potential Of Ash From Sugarcane Bagasse (SBA) And Low-density Polyethylene, Or LDPE, Waste Plastic As Partial Substitutes And Additives To Enhance The Geotechnical Features Of BCS At The Subgrade Level. Sugarcane Bagasse, A Plentiful Byproduct Of The Sugar Sector, Possesses Pozzolanic Properties That Increase Soil Strength And Decrease Plasticity. Simultaneously, LDPE Waste Plastic, A Major Pollutant, When Shredded And Blended With Soil, Contributes To Increased Ductility And Load-bearing Capacity Due To Its Tensile Resistance. The Combined Application Of SBA And LDPE Provides A Dual Benefit—mitigating Waste Disposal Problems While Enhancing Soil Performance.This Paper Conducts A Systematic Review Of Previous Research, Experimental Methods, And Real-world Applications That Examine Changes In Features Such As California Burden Ratio (CBR), Unconstrained Compressive Strength (UCS), Boundaries Of Atterberg, And Swelling Behaviour. The Review Suggests That The Optimal Concentrations Of LDPE Plastic (0.5–2%) And The Ash From Bagasse (typically 5–10%) Lead To Substantial Enhancements In Subgrade Stability.The Findings Support The Integration Of Agro-industrial Waste In Pavement Subgrade Treatment, Aligning With Environmental Sustainability And Circular Economy Goals. Further Research Is Suggested For Long-term Performance Analysis Under Varying Climatic And Traffic Conditions.

Author: Aniket Darekar | Dr. D. S. Patil

Area of research: AI And Data Science

Machine Learning And Data Analytics Are Extensively Used For Optimizing The Performance Of Electric Vehicles. As Electric Vehicles (EVs) Become More Prevalent Globally, The Need For Efficient Infrastructure Planning And Energy Management Grows. One Critical Aspect Of This Transition Is Accurately Estimating EV Charging Demand, Which Is Vital For Grid Stability, Charging Station Placement, And Energy Cost Optimization. Traditional Forecasting Methods Often Fall Short Due To The Complex And Dynamic Nature Of EV Usage Patterns. Machine Learning (ML) Offers A Promising Solution By Leveraging Historical And Real-time Data To Make Accurate And Adaptive Demand Predictions. This Paper Presents A Comprehensive Review On Multiple Machine Learning Models Which Are Extensively Used For Estimating EV Charging Demand. The Analysis Of The Benchmark Models Would Allow Researchers In Developing An Optimized Data Driven Model With The Objective Of Attaining High Accuracy.

Author: Neeraj Yadav | Dr. Sanmati Jain

Area of research: AI And Data Science

Machine Learning (ML) Has Revolutionized Data-driven Decision-making Across Sectors Such As Healthcare, Finance, Defense, And Cybersecurity. However, As Its Influence Grows, So Does Its Vulnerability To Adversarial And Poisoning Attacks. Adversaries Exploit The Weaknesses Of ML Models To Manipulate Outputs Or Degrade System Performance, Posing Significant Risks In Critical Applications. As A Result, Developing Machine Learning-based Models To Detect And Counter Such Attacks Has Become Essential For Building Secure And Trustworthy AI Systems. One Major Area Of Research That Has Emerged Is The Detection Of Poisoning For Android Systems Using Neural Networks Due To The Complexity Of Data Set Of Attacks. Several Approaches Have Been Used So Far For The Effective Classification Of Poisoning Attacks. The Paper Investigates The Different Contemporary Neural Network Based Approaches Used Thus Far In The Detection Of Poisoning Attacks. The Approaches Used And Their Findings Have Been Illustrated With Their Salient Points. Moreover, An Analysis In The Form Of Shortcoming In Previous Work Has Been Cited So As To Define A Problem Statement To Work Upon.

Author: Viketan Verma | Dr. Sanmati Jain

Area of research: AI And Data Science

Plant Diseases Like Early And Late Blight Must Be Promptly Identified, And This Requires Automated Blight Detection. These Illnesses Have The Potential To Spread Quickly And Seriously Harm Crops. By Taking Timely And Focused Action To Limit The Effects, Farmers Can Reduce Crop Losses And Ensure Food Security Through Early Detection. If Left Untreated, Blight Diseases Can Cause Significant Output Losses In Crops, Especially In Staple Items Like Tomatoes And Potatoes. Advanced Technologies Like Machine Learning And Image Analysis Enable Automated Detection Systems To Swiftly And Precisely Identify Disease Symptoms, Facilitating Early Intervention To Prevent Or Minimise Crop Losses. Therefore, The Pressing Need To Address The Problems Caused By Plant Diseases, Encourage Sustainable Agricultural Methods, And Support International Efforts To Ensure Food Security Is What Motivates The Need For Automated Blight Detection. Farmers, Customers, And The Environment All Stand To Gain From The Increased Efficiency And Precision Of Disease Management Brought About By The Integration Of New Technologies In Agriculture. This Paper Presents A Review On The State Of The Art Image Processing And Machine Learning, Deep Learning Based Approaches For Detection Of Potato Leaf Blight Disease.

Author: Praveen Kumar Patidar | Dr. Sanmati Jain

Area of research: AI And Data Science

Natural Language Processing Has A Large Number Of Applications Especially For Semantic Web. This Study Provides A Comprehensive Assessment Of Contemporary Machine Learning And Deep Learning Algorithms For Hate Speech Identification. Examples Of Such Occurrences Include Hate Speech, Abusive Language, Threats, And Derogatory Remarks. Hate Speech Constitutes Abuse That Is Not Limited To A Single Gender; It Affects All Individuals. In The Present Context, Comprehending The Dynamic Patterns (incidents, Geographical Predominance, Demography, Etc.) Is Essential For Formulating Ways To Analyse Hate Speech Activities. Social Media Platforms Function As An Information System That Aggregates And Categorises Hate Speech Data From Diverse Sources, Mostly Users. This Aggregated Information Is Analysed To Discern Insightful Patterns From Vast Quantities Of Social Media Data, Which Cannot Be Monitored Continuously. Contextual Interdependence Across Diverse Lexicons In Data Will Be Essential For Identifying Hate Speech. Current Research Reveals A Scarcity Of Studies Focused On Hate Speech Detection Concerning User Behaviour. This Study Addresses Hate Speech As An Online Exponential Issue Aimed At Damaging Targeted Individuals. Such Incidents Exacerbate Social Disparities And Asymmetries By Rendering Online Spaces Unfriendly And Inaccessible.

Author: Akshay Patidar | Dr. Sanmati Jain

Area of research: Computer Science

Machine Learning Has Been Extensively Used For Business Analytics, One Important Application Of Which Happens To Be Estimating Customer Churn. As Markets Become Increasingly Competitive, Retaining Existing Customers Has Proven To Be More Cost-effective Than Acquiring New Ones. In This Context, Machine Learning (ML) Has Emerged As A Powerful Tool For Analyzing Customer Behavior And Predicting Churn With High Accuracy. By Leveraging Vast Datasets And Sophisticated Algorithms, Businesses Can Proactively Identify At-risk Customers And Take Targeted Actions To Retain Them.The Success Of Churn Prediction Largely Depends On The Quality And Relevance Of Input Features. Important Features Include Customer Demographics, Transaction Frequency, Service Usage Patterns, Complaint Records, And Engagement Metrics. Feature Engineering, Which Involves Creating New Features Or Transforming Existing Ones, Is A Critical Step In Improving Model PerformanceThis Paper Presents A Comprehensive Survey Of Statistical Models For Forecasting Churn Rates Along With Associated Challenges That The Sector Faces.

Author: Khushi Soni | Prof. Manisha Kadam

Area of research: Marketing

This Literature Review Examines The Influence Of In- Fluencer Marketing On Consumer Behavior Through Various Empir- Ical And Meta-analyses On Influencer Marketing. Influencers Affect Consumer Attitudes And Purchase Intentions Positively Because Of Personal Perceptions Like Credibility, Levels Of Trust, Message Quality, Levels Of Engagement, Popularity Of The Influencer, And Parasocial Relationships. Two Main Mediators Are Trust And Authenticity, As High Credibility, Including Genuineness And Devotion Towards The Brand Can Build Bund Perceptions And Impulse Buying, Particularly In Millennials And Gen Z Responders. Content Qual- Ity And Influencer Popularity Can Escalate Personal Engagement Towards Influencers And Consequently Branding Effectiveness. Specific Common Characteristics Include Immediate Effects From Influencer Strategies On Consumer Attitudes, Brand Resonance And Purchase Behavior Across Product Categories (i.e., Fashion, Fitness, Technology). Parasocial Connections In Influences Take On The Form Of Consumer Attitudes And Connections And Switch It Into Purchase Action. The Literature Review Provides Limits Related To Influencer Marketing, Limitations Of Declining Effectiveness Of Influencer Content That Are Valued Above Influencer Marketing Or An Authentic Disclose Apart From Simply Promotional Offers). The Literature Review Outlines Ethical And Regulatory Concerns About Authenticity In Influencer Marketing, And Whether The Accent Is On The Message Or Brand, Instead Of Audience. Likewise Accurate To Influencer Marketing On The Growth Of Representing Cultural (and Often Platform-specific) Targets And Differences In Relation To Influencer Marketing Strategies, And The Platforms To Best Utilize Them (for Example, TikTok).

Author: Sneha K | Dr. M. Vijayakumar

Area of research: Material Science

Copper-doped Zinc Oxide (Cu:ZnO) Thick Films Have Gained Significant Attention Due To Their Tuneable Electrical, Optical, And Structural Properties. Doping ZnO With Transition Metals Such As Copper Enhances Its Suitability For A Range Of Applications Including Gas Sensing, Optoelectronic Devices, And Photovoltaics. This Paper Reviews The Synthesis Of Cu:ZnO Thick Films Using Various Deposition Techniques Such As Screen Printing, Sol-gel Processing, Spray Pyrolysis, And Pulsed Laser Deposition (PLD). The Structural And Functional Properties Of These Films And Their Applications In Different Domains Are Explored, Along With A Comparative Analysis Of Techniques.

Author: Prof. Maske S.V | Dr. Kendre D. K.

Area of research: Engineering

Concrete Is A Widely Used Construction Material For Various Types Of Structures Due To Its Durability. For A Long Time It Was Considered To Be Very Durable Material Requiring A Little Or No Maintenance. The Use Of Concrete Is Unavoidable, At The Same Time The Scarcity Of Aggregates Are Also Increasing Nowadays. Utilization Of Industrial Soil Waste Or Secondary Materials Has Been Encouraged In Construction Field For The Production Of Cement And Concrete Because It Contributes To Reducing The Consumption Of Natural Resources. Copper Slag Is One Of The Materials Which Is Considered As Waste Materials In The Production Of Copper, Which Can Be Used As Partial Replacement Of Fine Aggregates In Concrete. To Determine The Strength And Durability Characteristics Of Glass Fibre Reinforced Concrete Containing Copper Slag As Partial Replacement Of Fine Aggregate. Mix Proportioning Has To Be Done For M30 Grade Of Concrete. Sand Is Replaced With Copper Slag In Proportions Of 0%, 10%, 20%, 30%, 40%, 50% & 60%. In All Mixes, The Proportion Of Glass Fibre Is Kept Constant I.e., 0.2% By Volume Of Concrete. Strength Properties Tests Such As Compressive Strength, Split Tensile Strength, And Flexural Strength Were Calculated For Every Mixes Of Concrete And Then Found That Fibre Reinforced Concrete Containing Copper Slag As 40 % Partial Replacement Of Fine Aggregate Gives Optimum Percentage. The Flexural Behavior Of RC Beam And Durability Are Studied For The Optimal Percentage Of Copper Slag. The Durability Tests Like Acid Resistivity, Water Absorption, Porosity And Were Evaluated For Optimal Percentage Of Copper Slag.

Author: U.Gokulnath | Dr.A. Kumar | B. Senthil Naathan

Area of research: Social Science

The Karnataka State Budget 2025–26, Presented By Chief Minister Siddaramaiah, Outlines A Strategic Roadmap Aimed At Balancing Welfare Commitments With Fiscal Discipline. With A Projected Gross State Domestic Product (GSDP) Of ₹30.70 Lakh Crore, The State Estimates A Fiscal Deficit Of ₹90,428 Crore (2.9% Of GSDP) And A Revenue Deficit Of ₹19,262 Crore (0.6% Of GSDP). This Study Aims To Analyze The Fiscal Structure, Sectoral Allocations, Tax Trends, And Welfare Expenditure Using Secondary Data From Government Budget Documents, PRS Legislative Research, And CAG Reports. The Methodology Involves Descriptive And Analytical Techniques Focusing On Budget Indicators, Sectoral Trends, And Policy Impacts. Key Findings Reveal That The Total Budgeted Expenditure Stands At ₹4,09,549 Crore, With ₹3,11,739 Crore Allocated To Revenue Expenditure And ₹68,172 Crore To Capital Outlay. The Five Guarantee Schemes Alone Consume ₹51,034 Crore, Representing 17% Of Revenue Receipts. While Education (₹40,954 Crores), Health (₹18,690 Crores), And Irrigation (22,186 Crores) Have Seen Notable Allocations, Spending Remains Below National Averages In The Education And Health Sectors. Committed Expenditure On Salaries, Pensions, And Interest Payments Accounts For 58% Of Revenue Receipts, Limiting Fiscal Flexibility. The Study Suggests Enhancing Tax Compliance, Monitoring Welfare Program Efficiency, Rationalizing Salaries And Pensions, And Increasing Capital Investments In Underfunded Sectors. In Conclusion, Karnataka's Budget Reflects A Welfare-centric Yet Fiscally Cautious Approach. However, Sustaining This Model Demands Improved Revenue Mobilization And Better Governance Of Public Spending. References Include PRS Legislative Research (2025), Government Of Karnataka Budget Documents (2025), And The CAG State Finance Report (2023).

Author: Dr. Chethan Kumar C

Area of research: Civil Engineering

This Study Presents A Conceptual Analysis Of Structural Audit Practices For Bungalows Using Non-Destructive Testing (NDT) Methods. Structural Health Monitoring (SHM) Plays A Crucial Role In Assessing The Integrity Of Buildings By Detecting Potential Damage Such As Material Degradation, Cracks, And Other Structural Anomalies. In Residential Structures, Especially Bungalows, The Application Of NDT Methods Like Ultrasonic Pulse Velocity (UPV), Rebound Hammer Testing, And Core Concrete Sampling Provides Valuable Insights Into The Condition Of Concrete Without Causing Damage. These Techniques Ensure Effective, Cost-efficient Maintenance Of Buildings While Extending Their Lifespan. The Research Highlights The Growing Adoption Of NDT Methods In Residential Building Maintenance, Particularly In Regions Like Pune, India, Where Many Bungalows Are Decades Old. By Combining Different NDT Techniques, Engineers Can Create A Detailed Evaluation Of A Structure's Condition, Guiding Repair And Reinforcement Decisions. As These Methods Evolve, There Is A Shift Toward Predictive Maintenance, With Machine Learning And AI Integration Offering The Potential For More Accurate Assessments And Earlier Detection Of Degradation. This Study Also Discusses The Potential For Sustainable Practices, Such As Reusing Concrete Materials, Supported By The Data Gathered From NDT Methods. The Findings Suggest That NDT Can Significantly Improve The Management And Longevity Of Bungalow Structures While Reducing Environmental Impacts Associated With Demolition And New Construction.

Author: Ms. Harsada Patil | Ms. Swapnali Patil | Ms. Trupti Nanaware, Ms. Pradnya Madane | Ms. PratikshaPatil, Mr. Sudarshan Kanade6

Area of research: Computer Applications

Human-computer Interaction (HCI) Is Evolving Rapidly From Traditional Input Devices To Natural, Intuitive Interfaces. This Paper Introduces A Touchless Virtual Mouse System Using Python And Computer Vision, Eliminating The Need For Physical Touch. By Employing Hand Gesture Recognition Through Standard Webcams, The System Emulates Mouse Operations Such As Movement, Clicks, And Scrolling In Real-time. This Technology Not Only Improves Hygiene And Accessibility But Also Opens New Pathways For Future Interaction In Fields Like Healthcare, Robotics, And Virtual Reality.

Author: J. Suriya Prakash | Mrs. D. Nandhini

Area of research: Computer Science & Engineering / Information Technology

In The Digital Environment, Specialists Frequently Use A Broken Array Of Tools Since They Need To Talk, Schedule, And Do Duties, Thus Disorganization Occurs, Plus They Miss Opportunities For Automation. Gmail, Microsoft Outlook, Google Calendar, Google Tasks, As Well As Google Drive, Do Integrate Into Worksphere, A Designed Unified Platform For Workspaces. Worksphere, Which Is A Web Application Built Across Platforms And Mobile-first, Was Developed And Deployed With React, Redux, And Node.js In This Paper. Supabase Relies On The Backend For OAuth Token Storage. The Backend Also Influences Data Resolution. Secure API Integrations With Services Like Google And Microsoft Make It Possible The Organization Of Email In Real-time And Visualization Of The Calendar. These Integrations Also Allow Task Management Along With Document Handling. The System Addresses Key Challenges That Exist In Token Lifecycle Management And Email Threading, And Event Execution That Are United. Worksphere Measures Against Tasks That Are Predictable Plus Manages Workflows Of Email, Showing Users Gain Experience Plus Develop Meaningful Productivity. The Study Designs A Flexible Framework, Which Creates Future Online Environments.

Author: Mr. C.Senthilkumaran | K. Pukazhvel

Area of research: Computer Application

We Didn’t Just Build An App. We Built A Coach. A Smart One. It Lives Right In Your Phone And Knows What You’re Doing. No Wearables. No Bands. Just Your Camera And A Bit Of AI Magic. Built With Flutter And Google ML Kit’s Pose Detection, This App Sees Your Movements. Count Push-ups, Squats, Jumping Jacks, And More In Real-time. It Also Checks Your Posturewhether You're Nailing That Yoga Pose Or Not. You Move, It Responds. Simple. But Wait, There’s More. This App Isn’t Just About Exercises. It Calculates Your BMI. Helps Track Your Nutrition. And Turns Workouts Into Game-like Levels. It’s Part Trainer, Part Game, And All Smart. You Get Instant Feedback. Progress Tracking. Motivation. It's Like A Gym, A Trainer, And A Buddyall In One. Fitness Has Changed. And This App Is Proof

Author: P. Navaneetha Krishnan | Mrs. V. Mageswari

Area of research: EEE

Developing Higher-order Thinking Skills (analysis, Evaluation, And Creation) Is Essential In Helping Students Go Beyond Procedural Understanding Toward Meaningful Engagement With Mathematical Concepts. Despite The Emphasis In Curricula On Critical And Creative Thinking, Traditional Mathematics Instruction Often Limits Students To Solving Routine Problems, Offering Few Opportunities For Deeper Reasoning And Exploration. This Research Addresses The Need For Innovative Strategies That Actively Engage Learners In Constructing Mathematical Knowledge, With A Focus On Collaborative Problem-posing. The Study Employed A Pre-experimental Design Using A One-group Pretest-posttest Method To Measure How Collaborative Problem-posing Enhances Students' Higher-order Thinking Skills. The Participants Were Grade 7 Students From A Public Secondary School Who Were Taught About Integers Over A Period Of Three Weeks. Before The Intervention, Students Were Given A Teacher-made Pretest That Assessed Various Levels Of Higher-Order Thinking Skills (HOTS), Aligned With Bloom's Taxonomy, Focusing On Their Ability To Analyze, Evaluate, And Create. The Results Revealed A Significant Increase In Post-test Scores Compared To The Pretest Scores. The P-value In The Three Higher-order Thinking Skills (analyzing, Evaluating, And Creating) Confirms That The Improvement Was Not Due To Chance But Rather The Effectiveness Of The Collaborative Problem-posing Activities.

Author: Christine Joy V. Zarzua | Anna Liza P. Del Rosario

Area of research: Civil Engineering

Textile Industries Play A Major Role In Environmental Pollution, Primarily Due To Their Wastewater, Which Is Often Loaded With Dyes, Chemicals, And Other Harmful Pollutants. Tackling The Treatment Of Textile Wastewater Is No Easy Feat, Given The Variety And Stubbornness Of The Pollutants Involved. Traditional Methods Like Activated Sludge And Coagulation-flocculation Frequently Fall Short Of Meeting Strict Discharge Standards, Highlighting The Need For More Effective Solutions. Enter Nano-membranes—these Innovative Tools For Wastewater Treatment In Industrial Settings Are At The Forefront Of Water Purification Technology. This Study Dives Into How Well Polyethersulfone (PES) Membrane Filtration Works In Eliminating Contaminants From Industrial Wastewater. The Experimental Findings Showed Impressive Pollutant Reductions, Achieving Removal Rates Of 93.5% For BOD, 93.3% For COD, 83.4% For TDS, And 96.3% For Suspended Solids. Heavy Metals Saw An 88.8% Reduction, And Turbidity Removal Hit 93.5%. The Membrane Significantly Enhanced Water Quality, Producing Permeate That Complied With Environmental Discharge Standards. This Study Confirms That PES Membrane Filtration Is Not Just Viable But Also An Efficient Method For Treating Industrial Wastewater, Boasting High Removal Rates For Both Organic And Inorganic Contaminants. Further Research Is Suggested To Fine-tune Membrane Lifespan, Cleaning Methods, And Scalability For Larger Applications.

Author: KV Kesavan | Roopa D

Area of research: Environmental Engineering

Despite Advancements In Recognition, Prediction, And Preventive Measures, Landslides Continue To Cause Significant Social, Economic, And Environmental Damage In The Nilgiris District, Tamil Nadu. This Persistent Issue Stems From The Complexity Of Slope Failure Mechanisms And Our Incomplete Understanding Of The Underlying Factors. In This Study, Four Soil Samples Were Collected From Frequently Affected Landslide Sites In The Nilgiris District And Subjected To Geotechnical Analysis, Including Tests For Cohesion, Angle Of Friction, And Atterberg’s Limits. These Soil Properties Were Then Used As Input Parameters For Slope Stability Analysis Conducted Using Oasys Slope. Additionally, Scanning Electron Microscope (SEM) Imaging And Energy Dispersive X-Ray Analyzer (EDX) Testing Were Performed To Further Characterize The Soil Composition. The Landslide Site’s Satellite Imagery Was Obtained From Google Earth And Converted Into Data Points. Using TCX Converter And Quick Grid, The Slope Profile Was Plotted For Analysis. Rainfall Data From Nearby Rain Gauge Stations Were Also Collected And Incorporated Into The Study. Based On These Inputs, The Factor Of Safety Was Determined, And Site-specific Remedial Measures Were Proposed. The Findings From This Study Can Guide The Design And Implementation Of Appropriate Retaining Structures To Enhance Slope Stability And Mitigate Future Landslides.

Author: S. Navaneetha | S. Raajamurugan

Area of research: CSE

The Identification And Classification Of Marine Species Play A Vital Role In Ecological Studies, Biodiversity Protection, And Sustainable Fisheries Management. Traditional Approaches That Rely On Manual Observation Are Not Only Time-intensive But Also Susceptible To Errors Due To Human Limitations And Challenging Underwater Conditions. These Limitations Underscore The Need For Automated, Intelligent Solutions. The Core Of This Approach Combines CNNs With High-performance Object Detection Algorithms Such As YOLOv8. These Models Are Trained To Recognize Distinct Marine Species From Underwater Images. Since Such Images Often Suffer From Poor Lighting And Color Distortion, The System Integrates A Preprocessing Unit That Applies Image Sharpening, Contrast Boosting, And Noise Removal To Enhance Visual Quality.A Domain-specific Dataset Comprising Labeled Images Of Various Marine Species Was Curated To Train And Validate The System. Multiple Deep Learning Architectures Were Tested Namely ResNet, YOLOv8, EfficientNet, And Faster R-CNN. Evaluation Metrics Such As Accuracy, F1-score, Precision, And Mean Average Precision (mAP) Were Used To Assess Performance.Evaluation Metrics Such As Recall, Precision, Accuracy, And MAP Validate The Effectiveness Of The Method. This Project Proves That AI And Deep Learning Can Significantly Improve Marine Data Collection, Reduce Human Error, And Enable Scalable Biodiversity Monitoring SolutionsThis Work Demonstrates That Integrating AI With Marine Biology Not Only Automates Species Monitoring But Also Supports Large-scale Conservation Efforts And Ecological Analysis.

Author: P.Dinesh Kumar | G.Ananthi | N.Chaithanya | K.Keerthana | R.Nikitha

Area of research: Civil Engineering

Over The Past Few Years, The Structure Has Experienced Effects From These Gusts In Both Directions. These Designs Aim To Enhance The Visual Perspective Of The Projects They Undertake. The Variability In Floor Height Causes A Discontinuity In The Stiffness Of The Structure At The Level Of The Soft Story. This Phenomenon Is Caused By Floor Height Fluctuations. In The Even If Winds Expose This Discontinuity, It Could Potentially Cause Buildings To This Study Aimed To Perform A Static Analysis Of Three-dimensional Building Frames, Which Included G+7 Storeys, Floating Columns, And Soft Storey Elements. Elements. The Other Sixty-four Examples Feature Floating Columns At A Single Level, With The Soft Storey Varying Directly From The Ground (G) Story To The G+7 Storey. Eight Of The Instances Include Centre Floating Columns On Any One Of The Storeys, While Sixty-four Of The Other Cases Have Floating Columns At A Certain Level. This Instance Considers A Total Of Seventy-three Instances. Furthermore, We Construct A Simple Example Where Neither The Storeys Nor Any Of The Column’s Float, Adhering To The Previously Stated Conditions. In Addition To The Previously Stated Conditions, We Construct A Simple Example Where Neither The Floors Nor Any Of The Columns Float. We Have Adjusted The Floor Heights To Achieve The Desired Appearance. We Conducted The Analysis Using The Maximum Node Displacements (resultant), Maximum Moments, Maximum Shear Force, Maximum Axial Force, And Maximum Storey Drift. It Is Necessary To Do An Analysis Of The Findings In Order To Arrive At Technical Conclusions.

Author: P Veera | Venkata Satyanarayana | Sri B.Ramesh

Area of research: Finance

This Paper Presents A Lightweight Machine Learning Model For Enterprise Fraud Risk Management (EFRM) In Small And Medium Enterprises (SMEs). Traditional Fraud Detection Systems Are Often Too Resource-intensive For SMEs, Which Face Constraints In Computational Power. We Propose A Model Using Decision Trees, Optimized For Accuracy And Efficiency, Tested On A Synthetic Fraud Detection Dataset. The Results Show That The Model Achieves 85% Accuracy, 80% Precision, And 75% Recall, Demonstrating Its Potential For Efficient Fraud Detection Without Heavy Computational Demands. This Approach Offers SMEs An Accessible Solution For Fraud Risk Management.

Author: Rutuja Pratibha | Sahil Ambre

Area of research: M.Tech

It Is Very Important To Reduce The Development Times From The Initial Concept Development Stage To The Mass Production Stage In Automotive Engineering. Much Trial And Error Occur From The Initial Design To Mass Production To Verify The Performance And Durability And Other Design Criteria. Computational Simulations For Reducing Such Trials And Errors Are Generally Utilized And Have Proven To Be Useful Tools In Many Areas. The Ability Of Using CAD/CAE Has Become One Of The Core Technologies Nowadays Because Of Shortened Development Periods. The Compressor Mounting Bracket Was Studied In This Paper. This Study Is Mainly Concentrated On The Optimization Of Material Of The Model Automobile Engine Mounting Bracket, Optimization Will Help In Reducing The Unwanted Material Investment, Simplifying The Design And Reduce The Production Time, In This Work 4 Different Materials Are Used For Optimization, All The Observations Are Discussed Below, The Optimized Models Have Irregular Shapes, And Are Not Ready For Manufacturing, These Models Are To Be Redesigned Excluding The Portions That Are Removed During Optimization.

Author: Mrs.SAGARAPU GANGA BHAVANI | Mr.N.JAYA RAM | Dr.C.V.SUBBA REDDY

Area of research: Web Technologies

The School Website And Admin Portal Project Aims To Provide An Integrated Digital Platform For Educational Institutions To Manage And Present School-related Information Efficiently. The System Consists Of Two Key Components: A Publicfacing Website And A Secure Admin Portal, Both Connected To A Centralized Database. The School Website Serves As The Digital Identity Of The Institution, Offering Accessible Information To Students, Parents, And Visitors. It Includes Menus Such As Home, About, Academics, Gallery, Admission, And Contact, Displaying Real-time Updates Directly Fetched From The Database. The Admin Portal Is Designed For School Administrators To Manage Backend Operations Such As Maintaining Gallery Images, Publishing Achievements And Announcements, Managing Student And Staff Records, And Handling Admissions And Enquiries. Admins Can Update Content Across Modules Like Sports, Transport, Examination, Events, And More. These Updates Are Instantly Reflected On The Public Website Through The Shared Database.This Project Improves Administrative Efficiency, Enhances Communication Between The Institution And Its Stakeholders, And Ensures That The School's Digital Presence Remains Current And Informative. The Accompanying User Interface (UI) Diagram Visually Outlines The Layout And Navigation Structure Of Both The Website And Admin Portal, Highlighting The Relationship Between Various Menus And The Functionalities They Support.

Author: Mr.P. LOGAIYAN | G. BALACHANDRAN

Area of research: Civil Engineering

Smart Concrete Is Transforming Construction By Combining Self-sensing And Self-healing Characteristics, Allowing For Real-time Structural Health Monitoring. However, Because Of Different Material Compositions And Environmental Conditions, It Is Difficult To Estimate Its Attributes, Such As Strength, Durability, And Crack Resistance. The Use Of Sophisticated Computational Techniques Like Machine Learning (ML) And Deep Learning (DL), Which Are Subsets Of Artificial Intelligence (AI), Is Growing. These Techniques Offer Potent Answers By Evaluating Enormous Datasets To Precisely Predict Tangible Behavior. These Models Increase Prediction Accuracy And Lessen The Need For Expensive Laboratory Testing, Increasing The Viability Of Smart Concrete For Next-generation Infrastructure. Convolutional Neural Networks (CNNs) Improve Fracture Identification Through Image Analysis, While Artificial Neural Networks (ANNs) And Support Vector Machines (SVMs) Are AI Models That Are Excellent At Predicting Mechanical Features. By Evaluating Data From Embedded Sensors And Historical Records, AI Optimizes Mix Designs And Predicts Probable Faults. Case Studies Show That AI Is Beneficial, With ANN-based Self-healing Concrete Achieving 93% Accuracy In Repair Prediction And CNN-powered Bridge Monitoring Reducing Inspection Expenses By 25%. These Achievements Demonstrate AI's Significance In Making Building More Intelligent And Sustainable. Despite Its Potential, Problems Exist, Such As Data Scarcity, Model Interpretability, And Computing Demands. Future Research Focuses On Explainable AI (XAI) For Increased Transparency, Hybrid Models That Combine Physics And Machine Learning, And Edge AI For Real-time Decision-making. As AI Evolves, Its Combination With Smart Concrete Will Result In Safer, More Durable Infrastructure, Opening The Door For Intelligent Cities And Resilient Buildings. AI And Smart Concrete Have The Potential To Reinvent Current Construction By Combining Innovation And Pragmatism For A More Sustainable Future.

Author: Mr.Anuj Ramteke | Mrs. Aboli Ravikar

Area of research: Civil Engineering

This Paper Investigates The Integration Of 5D Building Information Modeling (BIM) With Microsoft Project (MSP) And Autodesk Navisworks For Quality Management And Project Lifecycle Optimization. A Case Study Of The Pride Purple Square Commercial Building In Pune, India, Forms The Basis Of This Comparative Analysis. 3D Models Were Created In Revit, Integrated With 4D Scheduling And 5D Cost Estimation In Both MSP And Navisworks Environments. The Study Highlights How BIM-based Workflows Improve Visualization, Cost Control, And Clash Detection Compared To Conventional Approaches. Results Show That Navisworks Offers Superior Clash Detection And 4D/5D Simulation Capabilities, While MSP Provides Robust Scheduling Features. Recommendations For Improved BIM Adoption In India Are Also Discussed.

Author: Shrirang Milind Chikhalkar | Pushpak Gajanan Jawanjal | Riya Anil Wankhede | Sagar Nandkishor Sonawane | Rohan Vilas Ambekar

Area of research: CSE

In Recent Years, Mental Stress Has Become A Growing Concern Due To Its Impact On Both Physical Health And Daily Performance. Traditional Methods Of Detecting Stress Often Rely On Physiological Sensors Or Self-reported Assessments, Which Can Be Intrusive, Expensive, Or Unreliable. In This Study, We Introduce A Novel, Non-invasive Approach That Uses Mobile Video To Analyze Human Gait And Identify Early Signs Of Mental Stress. The System Extracts Body Movement Features From Walking Sequences Using Pose Estimation Techniques And Calculates Specific Gait Parameters Such As Step Width, Hip Motion, And Stride Consistency. A New Composite Vector Is Proposed To Represent Behavioral Changes In Walking Patterns Typically Associated With Mental Stress. These Features Are Then Evaluated Using Machine Learning Algorithms To Classify Stress Levels. The Proposed Method Is Designed To Function In Real-time, Requires Only A Smartphone Camera, And Does Not Rely On Wearable Devices. This Makes It A Practical And Accessible Tool For Mental Health Monitoring, Especially In Everyday Environments Where Privacy And Convenience Are Crucial. The System Also Accounts For Variations In Walking Speed, Camera Angle, And Lighting, Ensuring Consistent Performance Across Diverse Scenarios.

Author: Dharanish.C | Yuvaraj.N | Jayendar.M.V | Dharshakram.S | Vignesh.R

Area of research: Computer Applications

With The Growing Reliance On Cloud Storage For Handling Sensitive And Confidential Data, Traditional Authentication Mechanisms Such As Passwords And Static Keys Are Proving To Be Increasingly Vulnerable To Security Breaches. Cyberattacks Exploiting Stolen Credentials, Phishing, And Brute-force Techniques Have Made It Clear That A More Robust And Multi-layered Approach Is Essential. This Project Introduces An Advanced Authentication And Access Control Framework That Leverages Physical Tokens And Dynamic Key Generation To Provide Significantly Enhanced Security For Cloud File Access. The Proposed System Utilizes A Two-factor Authentication Mechanism Where Access To Encrypted Files Stored In The Cloud Is Granted Only When Both A Physical Token And A Dynamic Cryptographic Key Are Successfully Verified. The Physical Token—such As A USB Security Key, Smart Card, Or Hardware Token—contains A Unique Identifier That Is Registered And Verified During Access Attempts. Simultaneously, A Dynamic Key Is Generated Using Time-based Algorithms (e.g., TOTP - Time-based One-Time Password), Which Must Match A Server-side Generated Key, Ensuring Real-time Synchronization And Reducing The Risk Of Replay Attacks. To Ensure Data Confidentiality And Integrity, All Files Are Encrypted With The AES-256 Algorithm Before Being Uploaded To The Cloud. This Ensures That Even If The Cloud Storage Is Compromised, The Contents Of The Files Remain Unintelligible Without Proper Decryption Keys. The Encryption Keys Themselves Are Securely Managed And Can Only Be Accessed During A Valid Authentication Session Involving The Correct Token And Dynamic Key. The System Thus Creates A Secure Boundary Around The File Access Workflow, Offering A Strong Defense Against Unauthorized Access And Data Leaks. Moreover, The Use Of Dynamic Keys Introduces A Temporal Element To Security, Where Access Credentials Expire Quickly, Minimizing The Window Of Vulnerability. The Physical Token Ensures That Access Cannot Be Achieved Remotely Without Possession Of The Registered Device. This Combination Of "something You Have" (the Token) And "something That Changes" (the Dynamic Key) Aligns With Modern Zero-trust Security Models And Offers A Practical And Scalable Solution For Both Individuals And Organizations Storing Sensitive Information In The Cloud. In Conclusion, The Project Presents A Comprehensive And Future-proof Security Mechanism For Cloud File Access That Addresses Majorvulnerabilities Present In Conventional Systems. By Integrating Physical Hardware Authentication With Dynamic Time-sensitive Key Verification And Strong Encryptionprotocols, The Systemsignificantly Raises The Standard For Data Security In Cloud Environments. It Is Especially Suitable For Sectors That Demand High Confidentiality Such As Healthcare, Finance, Defense, And Enterprise IT Services. This Multi-layered Security Approach Ensures That Even If One Authentication Method Is Compromised, Unauthorized Users Cannot Access The Stored Files. The Dynamic Key Changes With Every Access Attempt, Adding An Extra Layer Of Protection Against Brute-force Attacks And Unauthorized Duplication. This System Can Be Widely Used In Various Industries, Including Healthcare, Finance, Government, And Corporate Sectors, Where Secure Storage And Controlled Access To Sensitive Data Are Critical. Financial Institutions Can Use It To Safeguard Confidential Transactions And Client Data. Government Agencies Can Implement It For Classified Document Storage, While Corporations Can Secure Intellectual Property And Business-critical Files. Its Implementation Ensures That Only Authorized Individuals With The Correct Physical Token And Dynamic Key Can Retrieve And Decrypt Files, Reducing The Risk Of Data Breaches And Cyber Threats. The Development Of This Project Leverages HTML And Bootstrap (CSS) For The Front-end, Ensuring A Visually Appealing And Responsive Design. On The Backend, Java And MySQL Have Been Employed To Establish A Robust Foundation For Data Management And System Functionality.

Author: Mr.P.Logaiyan | Janaki .V

Area of research: Computer Application

In Modern Collaborative Environments, Safeguarding Shared Data Is Critical. This Project Presents A Secure File Management System That Employs Onion Encryption, Dynamic Re-encryption, And Access Revocation Policies To Ensure Data Confidentiality. The System Automatically Re-encrypts Files And Rotates Encryption Keys Upon Access Or Permission Changes, Rendering Previously Authorized Data Inaccessible To Revoked Users. RSA Encryption Is Used To Verify User Identities Before Granting Access, Preventing Unauthorized Entry. A Dedicated Module Manages Periodic Key Rotation And Integrity Verification To Detect And Prevent Data Tampering. Crucially, All Encryption And Re-encryption Operations Occur Without Exposing Plaintext, Enhancing Security During Key Updates Or Access Changes. This Solution Offers Robust Protection Against Unauthorized Access And Ensures Compliance With Privacy Standards, Making It Ideal For Organizations Seeking Secure Data Collaboration. The Development Of This Project Leverages HTML And Bootstrap (CSS) For The Front-end, Ensuring A Visually Appealing And Responsive Design. On The Backend, Java And MySQL Have Been Employed To Establish A Robust Foundation For Data Management And System Functionality.

Author: Dr.A.Karunamurthy | V.Sujatha

Area of research: Information Security

This Project Titled “Geo-Temporal Encrypted File Vault With Secure Access Control And Self-Destruction”, Ensures The Increasing Demand For Highly Secure And Controlled File Transactions, This System Introduces An Advanced Geo-Temporal Encrypted File Vault, Integrating Geofencing, Time Based Access Control, Elliptic Curve Cryptography (ECC), And Automated Self- Destruction Mechanisms. The System Ensures That Files Can Only Be Accessed Within A Specific Geographic Location And Time Window, Preventing Unauthorized Access. The Encryption Process Leverages ECC-based Public-key Cryptography To Ensure Lightweight Yet Robust Security. Multi-factor Authentication (MFA) Using Passcodes Or OTP Verification Enhances Access Control. Upon Successful Authentication, Access Details Such As Geolocation, Timestamps, And User Credentials Are Logged And Securely Sent To The File Owner For Auditing. To Maintain Data Confidentiality And Prevent Residual Exposure, Files Are Automatically Deleted After Access. This System Is Ideal For Secure Document Handling In Corporate, Legal, And Classified Environments, Ensuring Zero Unauthorized Access, Strong Data Encryption, And Automatic Risk Mitigation Through Self-destruction Mechanisms. The Development Of This Project Leverages HTML And Bootstrap (CSS) For The Front-end, Ensuring A Visually Appealing And Responsive Design. On The Backend, Java And MySQL Have Been Employed To Establish A Robust Foundation For Data Management And System Functionality. This Project Titled “Geo-Temporal Encrypted File Vault With Secure Access Control And Self- Destruction”, Ensures The Increasing Demand For Highly Secure And Controlled File Transactions, This System Introduces An Advanced Geo-Temporal Encrypted File Vault, Integrating Geofencing, Time Based Access Control, Elliptic Curve Cryptography (ECC), And Automated Self- Destruction Mechanisms. The System Ensures That Files Can Only Be Accessed Within A Specific Geographic Location And Time Window, Preventing Unauthorized Access. The Encryption Process Leverages ECC-based Public-key Cryptography To Ensure Lightweight Yet Robust Security. Multi-factor Authentication (MFA) Using Passcodes Or OTP Verification Enhances Access Control. Upon Successful Authentication, Access Details Such As Geolocation, Timestamps, And User Credentials Are Logged And Securely Sent To The File Owner For Auditing. To Maintain Data Confidentiality And Prevent Residual Exposure, Files Are Automatically Deleted After Access. This System Is Ideal For Secure Document Handling In Corporate, Legal, And Classified Environments, Ensuring Zero Unauthorized Access, Strong Data Encryption, And Automatic Risk Mitigation Through Self-destruction Mechanisms. The Development Of This Project Leverages HTML And Bootstrap (CSS) For The Front-end, Ensuring A Visually Appealing And Responsive Design. On The Backend, Java And MySQL Have Been Employed To Establish A Robust Foundation For Data Management And System Functionality. The System’s Architecture Emphasizes Both Security And Usability, Providing A Seamless User Experience Without Compromising On Protection. By Combining A Responsive Front-end Built With HTML And Bootstrap With A Robust Java-MySQL Backend, The Platform Ensures Efficient File Processing, Secure Data Handling, And Real-time User Interaction. The Audit Trail Generated During Each Access Attempt Not Only Supports Accountability But Also Enables Proactive Threat Detection And Response. This Holistic Approach Makes The Solution Adaptable For Integration Into Existing Enterprise Systems, Offering A Reliable Method For Organizations To Enforce Strict Data Governance Policies.

Author: Mr.P.Rajapandian | Geetha Priya.V

Area of research: Electrical Engineering

The Aim Of This Paper Is To Model And Simulate A 300 KW Solar Photovoltic Power Plant Integrated With Electricity Grid. This System Analyzes The System:s Performance And Address Challenges Assosiated With Solar Inverters And Grid Integration. By Using MATLAB/Simulink, It Provides A Virtual Platform To Design, Test And Optimize PV Systems. It Analyzes The Process Of Converting Sunlight Into Electricity Through PV Panels And Evaluates The Efficiency Of Inverters In Transforming DC Power Into AC For Grid.

Author: Prof. S. K. Awaze | Harsh Mulay | Abhishek Karad | Srusti Nagarale

Area of research: QR Code-Based Authentication And Multi-Factor Authentication

With The Growing Adoption Of Cloud Storage For Secure File Management, Ensuring Data Confidentiality, Integrity, And Controlled Access Has Become Increasingly Important. This Project, "Cloud Security Framework For Encrypted File Sharing With QR Authentication," Introduces A Secure And Scalable System That Integrates AES (Advanced Encryption Standard) Encryption And QR Code-based Authentication To Protect Sensitive Information. Files Are Encrypted Before Being Uploaded To The Cloud, And A Unique Encryption Key Is Generated For Each File, Ensuring Data Remains Secure During Storage And Transmission. QR Code-based Verification Ensures That Only Authenticated Users Can Access And Decrypt The Files. To Further Enhance Data Integrity, The System Leverages Homomorphic Hashing Over An FTP-based Cloud Infrastructure, Enabling Secure And Verifiable File Integrity Checks Without Decrypting The Data. The System Also Maintains Detailed Logs Of File Access Attempts And Approvals, Ensuring Transparency And Accountability. By Combining Encryption, QR-based Authentication, And Cloud Storage With Secure Integrity Validation, This Framework Provides A Robust, Efficient, And Secure Solution For Managing And Sharing Sensitive Files In Cloud Environments. The Development Of This Project Leverages HTML And Bootstrap (CSS) For The Front-end, Ensuring A Visually Appealing And Responsive Design. On The Backend, Java And MySQL Have Been Employed To Establish A Robust Foundation For Data Management And System Functionality.

Author: Dr.A.Karunamurthy | R.Anandhi

Area of research: CONSTRUCTION MATERIAL

Human Hair Is A Waste Material That Is Determined In Bountiful Sum In Day By Day Existence. It Is A Regular Constituent In City Squander Streams And Reasons Ecological Troubles As It's Far A Non-degradable Waste. Fiber Strengthened Cement Give Great Flexure Strength Less Break Improvement. Considering That Concrete Is Frail In Stress For That Reason Some Estimates Ought To Be Embraced To Defeat This Insufficiency. Human Hair Is By Way Of And Massive Solid In Pressure; Henceforth It Thoroughly May Be Applied As A Fiber Fortification Cloth. Human Hair Fiber Is A Preference Non-degradable Problem To Be Had In Riches And At Unassuming Cost. Hair Moreover Diminishes Ecological Issues. Likewise, Growth Of Human Hair Strands Improvements The Coupling Residences, Miniature Breaking Manipulate, Imparts Ductility, Power And Moreover Builds Expanding Competition. The Exploratory Discoveries In Our Investigations Might Guide Destiny Exam Towards The Path For Lengthy Haul Execution To Expanding This Price Of Powerful Form Of Strands For Use In Number One Packages. Exam Had Been Led On Stable Three-D Shapes, Chambers And Mild Emissions Sizes With Growth Of Various Quotes Of Human Hair Fiber I.e., 0% And 3.5% Weight Of Concrete, Best And Coarse Combination And Results Were Contrasted And People Of Plain Concrete Cement Of Mid- Variety Grade. For Each Stage Of Human Hair Included Stable, We Make A Exceptional Cubes Sample That Were Tried For Their Character Mechanical Homes At Relieving Instances Of 7days, 14days And 28days. That Investigation Encourages The More Energizing To Realise The Human Hair Fiber Fortified Execution In Concrete Cement. In This Paper Flexure, Tensile, Water Absorption, Acid Attack Tests Are Performed.

Author: Kamata Singh

Area of research: Civil Engineering

This Research Paper Investigates The Seismic Performance Of Multi-storey Building Frames With Varying Column And Beam Geometries Under Seismic Loads. A G+10 Storey Reinforced Concrete (RC) Building Frame Was Analyzed Using STAAD Pro V8i Software In Seismic Zone III With Medium Soil Conditions. Three Models (Plan A, Plan B, And Plan C) Were Considered, Each With Different Cross-sectional Dimensions For Columns And Beams (230×230 Mm, 300×300 Mm, And 380×380 Mm, Respectively). The Study Evaluated Key Structural Responses, Including Support Reactions, Bending Moments, Shear Forces, Axial Forces, And Displacements. Results Indicate That Increasing Member Dimensions Reduces Displacement And Axial Forces But Increases Bending Moments And Shear Forces. Plan C (380×380 Mm) Exhibited The Least Displacement, While Plan A (230×230 Mm) Showed The Highest. The Findings Highlight The Importance Of Optimizing Member Geometry For Seismic Resilience In Multi-storey Buildings

Author: Arvind Daheriya | Ajay Verma

Area of research: Civil Engineering

Elevated Water Tanks Play A Vital Role In Municipal Water Supply Systems, And Their Structural Integrity Is Crucial To Ensure Public Safety And Health. However, These Structures Are Susceptible To Various Environmental Loads, Including Wind, Which Can Cause Significant Stress And Damage. This Study Presents A Comprehensive Wind Force Analysis Of Intze-type Elevated Water Tanks In India, Considering The Country's Diverse Wind Zones And Terrain Categories. The Primary Objective Of This Research Is To Investigate The Structural Behavior Of Two Commonly Used Tank Configurations: Straight-leg And Inclined-leg Designs. Using Advanced Structural Analysis Software, STAAD-Pro, This Study Evaluates The Lateral Displacements, Wind Forces, And Overall Performance Of Both Tank Configurations Under Various Wind Loads. The Analysis Takes Into Account The Complex Interactions Between Wind, Terrain, And Structural Components, Providing A Detailed Understanding Of The Tank's Behavior. The Results Of This Study Reveal That Lateral Displacements Increase With Height And Wind Zone Intensity, With Inclined-leg Tanks Exhibiting Larger Displacements Than Straight-leg Tanks. This Finding Highlights The Importance Of Minimizing Lateral Displacement To Prevent Sloshing And Structural Failure, Which Can Have Catastrophic Consequences. Furthermore, The Study Shows That Design Wind Forces Increase With Height Due To Increased Exposure And Terrain Factors, Emphasizing The Need For Careful Consideration Of These Factors In Tank Design. The Findings Of This Research Have Significant Implications For The Design And Construction Of Elevated Water Tanks In High-wind Areas. The Study Suggests That Straight-leg Configurations Are A Better Option For Stability, Providing Greater Resistance To Wind-induced Displacements. Additionally, The Research Highlights The Need For Further Studies On Seismic Analysis, Dynamic Load Considerations, And Alternative Structural Materials To Ensure The Safety And Durability Of Water Tanks. By Providing Valuable Insights Into The Structural Behavior Of Elevated Water Tanks Under Wind Loads, This Research Contributes To The Development Of Safer And More Effective Water Tank Designs. The Study's Outcomes Can Be Used By Engineers, Designers, And Policymakers To Improve The Design And Construction Of Water Tanks, Ensuring The Reliability And Sustainability Of Municipal Water Supply Systems.

Author: Swati Patel | Ajay Verma

Area of research: Civil Engineering

This Research Paper Presents A Systematic Methodology For The Hydraulic Design And Optimization Of Culverts, With A Focus On Evaluating Erosion Potential And Control At Inlet And Outlet Structures. The Methodology Is Based On A Comprehensive Review Of Existing Literature And Design Guidelines, As Well As The Results Of Numerical Simulations And Case Studies. The Paper Presents A Detailed Analysis Of The Hydraulic Design Of Culverts, Including The Evaluation Of Flow Characteristics, Hydraulic Loading, And Erosion Potential. The Results Of The Analysis Are Used To Develop A Set Of Design Guidelines And Recommendations For The Hydraulic Design And Optimization Of Culverts. A Case Study Is Presented To Demonstrate The Application Of The Proposed Methodology, Highlighting The Importance Of Iterative Design And Computer-aided Simulation In Achieving Optimal Culvert Design. The Case Study Involves The Design Of A Culvert For A Major Highway Project, And Demonstrates The Effectiveness Of The Proposed Methodology In Reducing Erosion Risks And Improving Water Management. The Findings Of This Research Contribute To The Development Of Best Practices In Culvert Design, With Implications For Improving Water Management, Reducing Erosion Risks, And Enhancing The Overall Sustainability Of Transportation Infrastructure. The Results Of This Research Are Expected To Be Of Interest To Transportation Engineers, Hydraulic Engineers, And Environmental Scientists, And Are Expected To Contribute To The Development Of More Sustainable And Resilient Transportation Infrastructure.

Author: Ankur Chouksey | Prof. Ajay Verma

Area of research: Engineering

The Increase Of The Maneuverability When Parking The Vehicle Is Achieved By Means Of 4-wheel Steering, Meanwhile The Increase Of The Driving Stability At Higher Speeds Is Achieved Through Concordant Steering Front Wheels. A Disadvantage Of This So-called Passive Steering System Is That It Operates Even When Driving In Straight Direction When Single Wheel Of An Axle Hits Surface Irregularity. In This Project We Make Frame From Square Bar. Arrange Steering System At Front And Rear Side. When Steering Wheel Will Be Rotate, Then Bevel Gear Will Be Rotate. Bevel Gear Is Used To Transmit Vertical Motion Into Horizontal Rotating Motion. Bevel Gear Drive Shaft Provides Same Rpm To Pinion. Pinion Will Rotate The Rack. At The Both End Of The Rack Two Pinion Is Meshed. Due To Linear Motion Of The Rack Direct Angular Motion Given To The End Racks. Each Of The End Rack Have The Steering Linkages Are Provided. Power Transmitted By The Bevel Gear Is Directly Give To Rear Axle Steering System Which Have Same Mechanism Like Front Wheels.

Author: Dhaval Chaudhari | Yash Bagmar | Atharva Kulkarni | Saurabh Tawde | Purvesh Mehta, Prof. S.A.Shimple

Area of research: Electronics And Telecommunication

Modern Bridges Need Regular And Careful Monitoring To Stay Safe And In Good Working Condition. Traditional Ways Of Checking Bridges Can Be Slow, Expensive, And Often Happen After Damage Has Already Started. This Paper Talks About A Smart System Using The Internet Of Things (IoT) To Watch Over Bridge Health In Real-time. It Uses Small Wireless Sensors To Track Vibration, Tilt, And Weight. These Sensors Send Data To The Cloud, Where It Is Processed Using Machine Learning. The System Can Find Early Signs Of Damage, Send Alerts, And Help Plan Repairs Before Bigger Problems Occur. This Helps Keep Bridges Safe And Reduces Repair Costs Over Time.

Author: Pallavi Mhetre | Anisha Sontakke | Abhijit Rupnar | Yash Dubbewar

Area of research: Civil Engineering - Concrete

The Production Of Ordinary Portland Cement Concrete Causes Havoc To The Environment Due To The Emission Of CO2 In The Production Of Cement As Well As Mining Which Results In Unrepairable Damage To Nature. Geopolymer Concrete, A Cement Free Concrete Is An Innovative Green Concrete In Which Binding Properties Are Developed By The Interaction Of Alkaline Solutions With A Source Material That Is Rich In Silica And Alumina. Fly Ash, A By- Product Of Coal Obtained From The Thermal Power Plant Is Rich In Silica And Alumina Which On Reacting With Alkaline Solution Produces Aluminosilicate Gel That Acts As The Binding Material For The Concrete. Geopolymer Concrete Develop High Compressive Strength On Heat Curing Promising To Be An Ecofriendly Substitute For Ordinary Portland Cement Concrete In Some Applications. This Paper Briefly Put The Light On The Development Of High Strength Geopolymer Concrete With The

Author: Anup Kumar | Sri.Ch.Ganga Bhavani

Area of research: Civil Engineering

The Design Of Pavements On Black Cotton Soil Has Always Been A Difficult Task For The Engineers As The Structure And Pavement Resting On Black Cotton Soil Cracks Without Any Warning. Black Cotton Soil Is Most Commonly Found In Indian Region. Soil Proportion Changes Depending Upon Their Constituents, I.e., Water Content, Density, Bulk Density, Compressive Strength Etc. The Properties Of Black Cotton Soil Can Be Modified By Stabilizing The Soil With The Use Of Additives Or By Mechanical Means. The Aim Of This Project Is To Find The Optimum Percentage Of Lime Separately And Lime + Bamboo Fibre Separately To Be Added In Black Cotton Soil And Study The Properties Of Soil. In This Project An Attempt Has Been Made To Stabilize The Soil Using Lime And Bamboo Fibre. Initially Lime Is Blended With Black Cotton Soil In Different Proportions (2%, 4%, 6%, 8%). The Experimental Work Included The Tests Carried Out On Virgin Black Cotton Soil And Lime Added Black Cotton Soil Which Are Liquid Limit, Plastic Limit, Modified Proctor, Specific Gravity, Free Swell Index, C.B.R. Test, Unconfined Compressive Strength Test. On The Basis Of The Soaked CBR And Modified Proctor Values, It Is Determined That 6% Of Lime Is An Optimum Percent Which Can Be Added To Stabilize Black Cotton Soil For Road Construction. So, 6% Lime Is Added With Black Cotton Soil And Different Percentages Of Bamboo Fibres (2%, 4%, 6%, 8%). California Bearing Ration, Modified Proctor Test, Unconfined Compressive Strength Test Are Performed On The Soil Mixture Of 6% Lime + Black Cotton Soil + Different Percent Of Bamboo Fibre. On The Basis Of The Soaked CBR, It Is Concluded That If 6% Lime With 8% Of Bamboo Fibre Is Blended In Black Cotton Soil, Engineering Properties Of BCS Can Be Improved To Such An Extent That The Pavements Built On This Soil Can Efficiently Withstand The Loads Applied On It While Vehicular Movement. Hence, According To The Results Obtained From Experimental Study, Pavement Design Is Performed For CBR 5%, 6%, 8%. The Evaluation Of Cost For Each Pavement Design Is Carried Out Which Shows The Decrease In Cost Of Construction Of Pavement As The CBR Values Increases.

Author: Kankate Rohan Popat | Vithal Vilas Kale | Netake Swapnil Sitaram | Prof. S. S. Patil

Area of research: Computer Applications

Every Day, The Number Of Traffic Accidents Rises As The Automobile Population Increases. According To A Survey By The World Health Organization (WHO), 1.3 Million People Die And 50 Million Are Wounded Annually Around The Globe. Most People Die Because They Don’t Get Medical Help At The Scene Of An Accident Or Because It Takes Too Long For Rescuers To Get There. The Time After An Accident Can Be Optimally Used To Make A Difference Between A Life Saved And Life Lost, If Recovery Actions Are Able To Take Place In Time. However, Routing Problems And Traffic Congestion Are Major Factors Hampering Speedy Assistance. By Identifying Sites Where The Possibility Of Accidents Is Higher And The Closest Spot For Ambulance Placement, The Response Time Can Be Greatly Reduced. This Project Aims To Revolutionize Emergency Response Strategies By Shortening The Time It Takes For An Ambulance To Arrive At The Scene Of A Road Accident. It Proposes A Novel Unsupervised Generative Clustering Approach Using Variational Deep Embedding (VaDE), Along With Linear Regression To Predict The Optimal Position For Ambulances Based On Accident Location Addresses. Linear Regression Helps In Forecasting The Closest Possible Ambulance Location By Analyzing Historical Accident Data, Such As Location, Frequency, And Distance. Additionally, This System Includes Real-time Alerts To Both Hospitals And Traffic Departments, Facilitating Route Clearance For Expedited Ambulance Travel. Unlike Traditional Clustering Methods, Variational Deep Embedding (VaDE) Is A 4-step Data Generation Process That Uses Deep Neural Networks And A Gaussian Mixture Model To Optimize Ambulance Positioning Strategies. By Placing Ambulances Near Accident-prone Areas, The Response Time Can Be Significantly Reduced, Saving Valuable Lives. This Combination Of Predictive Models Not Only Enhances Ambulance Placement Strategies But Also Aims To Improve The Overall Emergency Response System.

Author: Dr. A. Karunamuthy | K. Karthikeyan

Area of research: Computer Science

This Paper Introduces An AI-powered Platform Designed To Provide Personalized Career Guidance For STEM Professionals And Students. The Platform Addresses The Challenges Of Generalized Career Advice By Leveraging Advanced Algorithms And Psychological Insights To Offer Tailored Career Recommendations. By Analyzing Individual Characteristics Such As Interests, Skills, And Career Goals, The System Creates A Comprehensive Support Mechanism For Navigating The Complex STEM Job Market. Key Features Include Psychometric Assessments, Curated Resources, And Dynamic Recommendation Systems That Help Users Explore Diverse Career Opportunities. The Platform Aims To Bridge The Gap Between Education And Employment By Empowering Individuals To Make Informed Career Decisions, Ultimately Enhancing Their Ability To Thrive In STEM Fields. The Study Outlines The Technical Design Of The Platform, Its Methodology For Personalized Guidance, And Its Potential To Transform Career Development For STEM Professionals. The System Achieved An 82% Satisfaction Accuracy And Successfully Provided Personalized Career Recommendations To Over 100 Test Users During Beta Testing.

Author: Prof. Madhavi Indalkar | Abhishek Pawar | Raj Nangare | Aadarsh Sharma | Parth Solanke

Area of research: Library Science (Library Building)

Ithin An Educational Institution, The College Library Is A Vital Centre For Community Contact, Student Involvement, And Academic Resources. The Design, Operation, And Changing Function Of College Library Facilities In The Twenty-first Century Are Examined In This Essay. It Looks At How Cutting-edge Architectural Design, Technological Integration, And The Development Of Collaborative Learning Spaces Are Helping Modern Libraries Adapt To The Shifting Needs Of Instructors And Students. This Study Examines Several Library Designs And Evaluates How They Affect Efficiency, Accessibility, And User Experience. Additionally, It Looks Into How To Handle Environmental Issues And Promote Energy Efficiency While Incorporating Sustainable Design Ideas Into The Library Building. This Study Identifies Emerging Trends And Best Practices In Library Building Design By Analyzing Modern College Libraries. Ultimately, This Article Provides A Comprehensive Examination Of The College Library Building's Multifaceted Functions, Highlighting Its Significance In Fostering Academic Achievement And A Vibrant Campus Community. It Provides Information For Educators, Librarians, And Architects Who Plan, Renovate, Or Oversee College Library Buildings.

Author: Dr. Rajesh Rajam

Area of research: MCA

The Main Goal Of The Proposed System Handling Windows System Operations Using Hand Gestures Is To Improve Human-computer Interaction Through The Ability Of Manipulation Of Windows-based Operations Through Natural Hand Movements. This Hand-controlled Interface Makes Use Of Computer Vision Techniques And Machine Learning Models To Identify Dynamic And Static Hand Gestures In Real-time Using A Webcam. Through Such Frameworks Like MediaPipe Hand Tracking And Interacting With Automation Libraries Like The PyAutoGUI, The System Can Map The Recognized Gestures Into System-level Commands Like Opening Of Apps, Handling Files, Changing Volume, And Manipulating The Mouse Pointer. The Intuitive And Touch-less Interaction Pattern Facilitates Accessibility, On The Alternative, Especially For The Users, Who Have Some Physical Limitations Or Are Located In Such Environments, Where The Typical Input Devices Are Inapplicable. The System Is Developed With An Idea Of Modularity And Scalability In Mind Which Makes It Possible To Add A New Set Of Gestures And Capabilities. With Efficient Gesture Recognition And Low Latency Response, As Well As A User-friendly Interface, The Solution Offers A Viable And Novel Way Of Hands-free Computing.

Author: Dr. T. Amalraj Victoire | M.Vasuki | Hari Priya A

Area of research: MCA

Thorn Development In Plants Serves As A Natural Self-defence Mechanism Which Creates Difficulties For People Who Perform Harvesting And Handling Tasks. GeneThorn Nexus Emerged Through Advanced Genetic Engineering Methods To Develop Thornless Plant Varieties. The Process Of Conventional Breeding Requires Substantial Time And Often Leads To Results Which Do Not Maintain Consistent Plant Characteristics Essential For Disease Defense And Yield Production. Through The Application Of CRISPR-Cas9 Gene-editing Technology Scientists Can Delete Genes Which Produce Thorns Without Affecting Other Essential Plant Attributes. Our Implementation Of Digital Tracking Tools Allows Plant Growth Stages To Be Continuously Monitored Alongside The Recording Of Genetic Modifications And General Growth Behavior. The Digital Platform Provides Scientists With Immediate Access To Information While It Simplifies Their Monitoring Responsibilities. The Primary Objective Consists Of Producing Plants That Are Both Safer To Handle And Easier To Manage In Agricultural Fields And Landscaping Areas And Home Gardens. Our Method Focuses On Enhancing Worker Safety Together With Enhanced Productivity And Sustainable Agricultural Development. GeneThorn Nexus Brings Together Scientific Breakthroughs And Technological Solutions To Advance Methods For Developing Thornless Plants.

Author: M.Vasuki | Dr.T. Amalraj Victoire | S. Gulasekaran

Area of research: MCA

A Lot Of People Experience Regular Occurrences Of Back And Knee Pain Throughout Their Daily Routines. This Project Provides Users With A Systematic Approach To Control And Diminish These Two Types Of Pain. Users First Need To Create An Account And Provide Information About Their Symptoms Which Includes Their Pain Intensity And Stiffness And Swelling Levels. The Platform Provides Users With Login Access After Receiving Approval From Administrators. After Users Log Into The Platform, They Have The Ability To Provide Additional Information About Their Condition. The System Analyzes The User-provided Data To Determine The Specific Pain Type And Its Intensity Level. The System Provides Users With An Appropriate Therapy Plan Recommendation And The Estimated Treatment Duration. After Users Complete Their Therapy, They Need To Update Their Symptoms In The System. The System Uses The Updated Data To Compare It Against The Original Data And Determine The Amount Of Progress Made. The Process Includes Administrative Monitoring Along With Report Generation At All Stages. The Systematic Approach Allows Every Patient To Obtain Precise Care According To Their Medical Situation While Receiving Visible Results From Their Treatment. Technology Provides A Straightforward And Beneficial Method For Pain Management And Recovery.

Author: Dr. T. Amalraj Victoire | M. Vasuki | S. Amirtha

Area of research: IOT

This Paper Presents An IoT-based Approach Of School Bus Tracking, With A Focus On Increasing Child Safety And Providing Real-time Communication With Parents. The System Uses RFID Tags As The Primary Means Of Verification, Followed By A Secondary Verification Process Using Cameras. The Camera Captures Images Of Students And Checks Them Against Previously Stored Images, Also Checking Compliance With Mask-wearing Protocols. In Addition, The System Monitors The Students' Temperature Using An IR Sensor. The Proposed System Uses ESP8266 Controllers And SIM800L Modules With Integrated GSM Modem And GPS Receiver. GPS Tracking Enables Precise Determination Of A Vehicle's Location, With Data Transmitted To A Remote Server Over TCP Via A GPRS Service. The System Also Includes A Web-based Application For Data Visualization. Significantly, The Proposed System Shows Superior Accuracy Compared To Previous Methods. It Provides Real-time Data On Various Vehicle Features Including Location, Route, Speed, Passenger List, Driver Compliance And Schedule. The System Uses ESP8266 To Connect GPS, RFID, And Firebase Servers To The Cloud Via WiFi, Enabling Seamless Integration And Efficient Data Transmission. Introducing A Smart School Bus Security System Using IoT Offers Many Benefits, Including Increased Student Safety, Increased Accountability, And Reduced Practices Costs And Better Communication Between Parents, Schools And Transport Agencies.

Author: P.S.Mhetre | Harshad Shivale | Abhishek Tikone | Pratik Waste

Area of research: Electronics And Communication Engineering

Biofloc Technology Has Emerged As A Sustainable And Space-efficient Method For Fish Farming, Particularly Valuable In Regions With Limited Water Resources. However, Its Operation Is Highly Sensitive To Variations In Water Quality Parameters Such As PH, Total Dissolved Solids (TDS), Ammonia Levels, Turbidity, And Temperature. This Paper Presents A Cost-effective, Solar-powered Internet Of Things (IoT)-based Biofloc Monitoring System Integrated With Machine Learning (ML) Techniques To Detect Early Signs Of Fish Mortality In Aquaculture Tanks. Designed For Low-income Fish Farmers In Southern Punjab, Pakistan, The System Continuously Measures Critical Water Quality Parameters Using Affordable Sensors Connected To Arduino UNO And NodeMCU ESP8266 Microcontrollers. Over A Period Of 1.5 Months, Data Was Collected At Two-minute Intervals And Uploaded To The ThingSpeak Cloud Platform. After Preprocessing And Balancing The Dataset Using ADASYN, Several ML Algorithms—including Random Forest, XGBoost, Decision Trees, Support Vector Machines, And Naïve Bayes—were Trained And Evaluated. The Random Forest And XGBoost Classifiers Outperformed Others, Achieving Up To 98% Accuracy In Predicting Fish Mortality. This System Not Only Enhances Operational Efficiency In Biofloc Fish Farming But Also Reduces Fish Mortality And Economic Losses By Issuing Timely Warnings. The Results Demonstrate The Potential Of IoT-ML Integration In Transforming Small-scale Aquaculture Into A More Data- Driven And Sustainable Practice.

Author: Mr. R. Guruprasath | Amrit Raj | Avinash Kumar | Nagaraj K | Sanjay T

Area of research: Civil Engineering

Untreated Pond Water Frequently Has Significant Levels Of Turbidity, Hardness, Nitrates, And Chlorides, Rendering It Unfit For Drinking And Other Uses. Contaminants Such As Suspended Particles, Germs, And Dissolved Salts Can Endanger Human Health And Impair Water Quality. This Study Compares The Efficacy Of Four Filtration Technologies For Improving Pond Water Quality: Microfiltration (MF), Ultrafiltration (UF), Nanofiltration (NF), And Reverse Osmosis (RO). The Findings Indicate That MF And UF Successfully Reduce Turbidity And Suspended Solids, But NF Provides Moderate Purification By Reducing Pollutants To Tolerable Levels. RO Produces The Highest Quality Water By Considerably Eliminating All Contaminants, Making It Suitable For Drinking And Other Delicate Uses. The Study Emphasizes The Necessity Of Choosing The Right Filtration System Based On Water Quality Requirements, Cost, And Efficiency.

Author: Mrs.G.Hemalatha | Mr.T.Sathieshkumar | Mrs.S.Sharmila | Mrs.R.Jeevika

Area of research: Electronics & Telecommunication Engineering

In This Project, We'll Carefully Examine A E-Rakshak The Border Surveillance Robot As We Know Surveillance Is A Difficult Task Of International Border Areas. It Is Not Possible By The Border Guarding Forces To Watch The Border At Each & Every Moment. In This Case The Essential Requirement Is To Have A System Security Control Unit. Nowadays, To Carry Out Risky Jobs The Robots Are Used That Cannot Be Done By The Soldiers. The Main Purpose Of Developing Such A New Technology In This Present System-based Spy Robot Platform With Remote Monitoring & Control Algorithm Through Internet Of Things (IOT) Has Been Developed Which Will Save Human Live, Reduces Manual Error And Protect The Country From Enemies. The System Comprises The Raspberry Pi (small Single- Board Computer), Camera, PIR Sensor And Shooting Gun. The Raspberry Pi Is The Brain Of The System. Android App Control The Moving To A Specific Direction And Camera For Live Streaming Videos Of Required Areas For Tracing And Attacking & The PIR Sensor Are Activated Depend On External Stimuli Via IOT. The User Is Able To Access The System With Control Buttons On The Android App From Control Room.

Author: Mr. H.K.Bhangale | Dukale Pranali | Pund Prashant | Vahadane Pallavi | Burte Vedant