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Review Paper On Disaster Prediction and Monitoring System Using Machine Learning Algorithms

Authors : Vidya Pardeshi, Dr. H. T. Ingale ,  Dr. Anilkumar Vishwakarma, Dr. I.S Jadhav , Dr. V.  D Chaudhari DOI : 10.46335/IJIES.2025.10.7.18 Abstract – Natural disasters like floods, earthquakes, and landslides can cause massive damage and loss of life. Many traditional disaster management systems focus on responding after a disaster happens, rather than predicting it […]

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Advancing Breast Cancer Detection Through Thermal Imaging and Machine Learning: A Comprehensive Review of Techniques and Applications

Authors : Vishakha Dubey, Dr. Shanti Rathore, Dr. Rahul Gedam DOI :  10.46335/IJIES.2025.10.7.17 Abstract – Breast thermography proves to be an evolving diagnostic support method that uses infrared imaging for vascular and metabolic change detection in breast cancer evaluations. This paper conducts an extensive analysis of thermographic imaging progress along with AI-based and ML-based diagnostic […]

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Literature Review on System on Chip (SOC)

Authors : Amrapali N. Nirmal , Dr. H. T. Ingale, Dr. I. S. Jadhav, Dr. V. D. Chaudhari, R. V. Patil DOI :  10.46335/IJIES.2025.10.7.16 Abstract – The System-on-Chip (SoC) design paradigm has revolutionized modern electronics by integrating an entire system into a single chip. SoCs combine various components like processors (CPU/GPU), memory, I/O interfaces, and […]

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AI-Empowered Healthcare Insurance Fraud Detection Using Block chain

Authors :  Gaurav Kumar Singh, Himanshu Kumar, Jafarullah Ansari , Mrs. M. Priyanga , Dr. M. Chandran DOI : 10.46335/IJIES.2025.10.7.15 Abstract – This project introduces an AI-empowered healthcare fraud detection system using blockchain for secure and transparent medical insurance claims. AI models detect anomalies, while blockchain ensures tamper-proof records, reducing fraud and improving claim verification. […]

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Exam.AI : Ensuring Fairness and Integrity in Online Assessment

 Authors : Atul Mairale , Sumit More, Harshjeet Girase, Harshal Mahajan, Kiran Patkari DOI : 10.46335/IJIES.2025.10.7.14  Abstract— From the past 5-year, online examinations have gained immense popularity across educational fields due to COVID-19. However, institutions face significant challenges in terms of proctoring methods. If the current way of life becomes the new normal, there is a […]

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DNA Sequencing and Criminal Identification Using DL

Authors : Dr. Swarupa Amey Wagh DOI : 10.46335/IJIES.2025.10.7.13 Abstract –The Rapid advancements in deep learning have significantly transformed DNA sequencing and forensic identification. Traditional forensic DNA analysis relies on STR profiling, but deep learning techniques offer enhanced accuracy, speed, and automation. This research explores the integration of convolutional neural networks (CNNs), recurrent neural networks […]

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Machine Learning-Driven Identification of Cotton Leaf Diseases for Precision Agriculture

Authors : Tushar Mohite Patil , Sanjay Pandey2, Ravindra Duche DOI :10.46335/IJIES.2025.10.7.12 Abstract – In this study, we propose a machine learning-based method for automatic detection of cotton leaf diseases based on Random Forest classifier. Other features extracted are color based (RGB) and texture based (GLCM) that helps a lot in increasing the classification accuracy. […]

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SVM-Based Facial Expression Recognition: A Focus on Emotion Analysis for Individuals with Intellectual Disabilities

Authors : Ganesh Chandra Akoliya, Sanjay Pandey, Ravindra Duche DOI : 10.46335/IJIES.2025.10.7.11 Abstract –In this study, we develop a FER system for intellectual disability people based on DWT and Gabor filter for feature extraction followed by an SVM classifier for classification of expression. Four different preprocessing techniques such as converting into grayscale, normalizing the image, and data […]

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Performance and Computational Efficiency of Deep Learning Models for Anomaly Detection on the UCSD Dataset

Authors : Mrs. Sangita Mahendra Rajput , Prof. Dr Mangesh D Nikose DOI : 10.46335/IJIES.2025.10.7.10 Abstract – The emergence of deep learning models has significantly improved the accuracy of anomaly detection in surveillance, crowd analysis, and other real-world applications. However, the challenge remains to balance performance with computational efficiency, particularly for real-time applications. This study […]

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Explainable AI for Timetable Scheduling in Education: A Case Study

Authors : Maheshkumar S. Patil , Tukaram K. Gawali, Ishwar S. Jadhav DOI : 10.46335/IJIES.2025.10.7.9 Abstract –Timetable scheduling in educational institutions is a complex optimization problem that involves balancing multiple constraints such as teacher availability, classroom capacity, and student preferences. Traditional approaches often rely on heuristic or rule-based methods, which lack transparency and adaptability. Explainable […]

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