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Papers by rohini hanchate
Optimized Data Retrieval and Data Storage for Healthcare Applications
River Publishers eBooks, Jun 20, 2024
Indigenous Knowledge in Smart Agriculture
River Publishers eBooks, Dec 19, 2023
International Journal of Science and Healthcare Research
Stress management systems are essential to identify and address stress levels that can disrupt ou... more Stress management systems are essential to identify and address stress levels that can disrupt our socioeconomic functioning. According to the World Health Organization (WHO), one in four people experience stress, which can result in mental and socioeconomic issues, poor work relationships, and depression, and in severe cases, suicide. Counselling is crucial to help people cope with stress, and while stress cannot be avoided, preventive measures can be taken to mitigate its effects. Currently, only medical and physiological experts can determine whether someone is experiencing stress. Traditional stress detection methods rely on self-reported answers, which can be unreliable. Automated stress detection can minimize health risks and improve societal welfare. Therefore, there is a need for a scientific tool that can automate stress detection using physiological signals. Stress detection is an important social contribution that potential to improve quality of life. As IT industries bri...
International advanced research journal in science, engineering and technology, Apr 30, 2023
Recent advances in computer vision have led to the development of a robust learning technique tha... more Recent advances in computer vision have led to the development of a robust learning technique that can identify and diagnose plant diseases using photos captured by a camera. This practical approach can help detect various illnesses in different plant species, including apples, corn, grapes, potatoes, tomatoes, and sugar cane. The system's architecture specifically targeted these plants for detection and recognition, and it can detect several plant diseases. To develop deep learning models for plant disease detection and recognition, scientists used 35,000 photos of both disease-free and diseased plant leaves. The system achieved up to 100% accuracy in identifying the type of plant and the diseases affecting it, with the trained model achieving an accuracy rate of 96.5%. The technique involved using convolutional neural networks, computer vision, deep learning, and plant disease recognition.
Medical Image Encryption Using Hybrid Adaptive Elliptic Curve Cryptography and Logistic Map-based DNA Sequence in IoT Environment
IETE Journal of Research
International Journal of Science and Healthcare Research
Artificial Intelligence research in the area of computer vision teaches machines to comprehend an... more Artificial Intelligence research in the area of computer vision teaches machines to comprehend and interpret visual data. Machines can accurately identify and classify objects using digital images from cameras and videos, deep learning models, and then respond to what they “see”. The detection of document manipulation is an area where these technologies are crucial. Everyone in India is given a PAN (Permanent Account Number), which is a 10-character alphanumeric code, especially those who pay taxes. Various organizations make use of identity documents like PAN cards. The PAN Card given by the employee or client may be genuine or fraudulent. This review paper’s main goal is to use computer vision to determine whether the provided PAN card image is authentic or altered (fake). Our goal is to create a method that uses machine learning techniques to categorize PAN cards. Keywords: Machine Learning, Convolutional Neural Network, Fraud, Image Processing
Design and Implementation of Lane Detection using Hough Transformation
2023 2nd International Conference on Applied Artificial Intelligence and Computing (ICAAIC)
Predictive and Descriptive Analysis for Healthcare Data
Handbook of Intelligent Healthcare Analytics, May 6, 2022
International Journal of Computer Applications, 2014
In this article the new hybrid data clustering approach, Gravitational Genetic KHM, based on Gene... more In this article the new hybrid data clustering approach, Gravitational Genetic KHM, based on Genetic algorithm (GA), Gravitational Search Algorithm (GSA) and K-harmonic Means (KHM) is proposed. Data Clustering is used to group similar set of objects into set of disjoint classes, object in class are highly similar than the objects in other classes. Among various clustering methods, KHM is one of the most popular clustering techniques. KHM is applied widely and works well in many fields, but this method runs in local optima. In the proposed approach the merits of Genetic Algorithm are used to escape the KHM clustering from local optima and to overcome the slow convergence speed of GSA. This paper is presented as work-in-progress in which the work model is proposed and some intermediate results are discussed which in turn will be compared with existing hybrid algorithms. The results are tested on several datasets.
A Lightweight Secure Data Sharing Scheme for Low Power Devices using Mobile Cloud Computing
International Journal for Research in Applied Science and Engineering Technology
International Journal of Computer Applications, 2014
Clustering is a process of extracting reliable, unique, effective and comprehensible patterns fro... more Clustering is a process of extracting reliable, unique, effective and comprehensible patterns from database. Various clustering methods are proposed to accomplish exactness and accuracy of clusters. K-Means is well known clustering algorithm but it easily converge to local optima. To overcome this drawback, an improved algorithm called K-Harmonic Mean (KHM) was proposed, which is independent of cluster center initialization. This article presents study of hybridization KHM with other clustering algorithms. In order to improve the clustering accuracy the authors proposed new hybrid KHM model.
Optimized Data Retrieval and Data Storage for Healthcare Applications
River Publishers eBooks, Jun 20, 2024
Indigenous Knowledge in Smart Agriculture
River Publishers eBooks, Dec 19, 2023
International Journal of Science and Healthcare Research
Stress management systems are essential to identify and address stress levels that can disrupt ou... more Stress management systems are essential to identify and address stress levels that can disrupt our socioeconomic functioning. According to the World Health Organization (WHO), one in four people experience stress, which can result in mental and socioeconomic issues, poor work relationships, and depression, and in severe cases, suicide. Counselling is crucial to help people cope with stress, and while stress cannot be avoided, preventive measures can be taken to mitigate its effects. Currently, only medical and physiological experts can determine whether someone is experiencing stress. Traditional stress detection methods rely on self-reported answers, which can be unreliable. Automated stress detection can minimize health risks and improve societal welfare. Therefore, there is a need for a scientific tool that can automate stress detection using physiological signals. Stress detection is an important social contribution that potential to improve quality of life. As IT industries bri...
International advanced research journal in science, engineering and technology, Apr 30, 2023
Recent advances in computer vision have led to the development of a robust learning technique tha... more Recent advances in computer vision have led to the development of a robust learning technique that can identify and diagnose plant diseases using photos captured by a camera. This practical approach can help detect various illnesses in different plant species, including apples, corn, grapes, potatoes, tomatoes, and sugar cane. The system's architecture specifically targeted these plants for detection and recognition, and it can detect several plant diseases. To develop deep learning models for plant disease detection and recognition, scientists used 35,000 photos of both disease-free and diseased plant leaves. The system achieved up to 100% accuracy in identifying the type of plant and the diseases affecting it, with the trained model achieving an accuracy rate of 96.5%. The technique involved using convolutional neural networks, computer vision, deep learning, and plant disease recognition.
Medical Image Encryption Using Hybrid Adaptive Elliptic Curve Cryptography and Logistic Map-based DNA Sequence in IoT Environment
IETE Journal of Research
International Journal of Science and Healthcare Research
Artificial Intelligence research in the area of computer vision teaches machines to comprehend an... more Artificial Intelligence research in the area of computer vision teaches machines to comprehend and interpret visual data. Machines can accurately identify and classify objects using digital images from cameras and videos, deep learning models, and then respond to what they “see”. The detection of document manipulation is an area where these technologies are crucial. Everyone in India is given a PAN (Permanent Account Number), which is a 10-character alphanumeric code, especially those who pay taxes. Various organizations make use of identity documents like PAN cards. The PAN Card given by the employee or client may be genuine or fraudulent. This review paper’s main goal is to use computer vision to determine whether the provided PAN card image is authentic or altered (fake). Our goal is to create a method that uses machine learning techniques to categorize PAN cards. Keywords: Machine Learning, Convolutional Neural Network, Fraud, Image Processing
Design and Implementation of Lane Detection using Hough Transformation
2023 2nd International Conference on Applied Artificial Intelligence and Computing (ICAAIC)
Predictive and Descriptive Analysis for Healthcare Data
Handbook of Intelligent Healthcare Analytics, May 6, 2022
International Journal of Computer Applications, 2014
In this article the new hybrid data clustering approach, Gravitational Genetic KHM, based on Gene... more In this article the new hybrid data clustering approach, Gravitational Genetic KHM, based on Genetic algorithm (GA), Gravitational Search Algorithm (GSA) and K-harmonic Means (KHM) is proposed. Data Clustering is used to group similar set of objects into set of disjoint classes, object in class are highly similar than the objects in other classes. Among various clustering methods, KHM is one of the most popular clustering techniques. KHM is applied widely and works well in many fields, but this method runs in local optima. In the proposed approach the merits of Genetic Algorithm are used to escape the KHM clustering from local optima and to overcome the slow convergence speed of GSA. This paper is presented as work-in-progress in which the work model is proposed and some intermediate results are discussed which in turn will be compared with existing hybrid algorithms. The results are tested on several datasets.
A Lightweight Secure Data Sharing Scheme for Low Power Devices using Mobile Cloud Computing
International Journal for Research in Applied Science and Engineering Technology
International Journal of Computer Applications, 2014
Clustering is a process of extracting reliable, unique, effective and comprehensible patterns fro... more Clustering is a process of extracting reliable, unique, effective and comprehensible patterns from database. Various clustering methods are proposed to accomplish exactness and accuracy of clusters. K-Means is well known clustering algorithm but it easily converge to local optima. To overcome this drawback, an improved algorithm called K-Harmonic Mean (KHM) was proposed, which is independent of cluster center initialization. This article presents study of hybridization KHM with other clustering algorithms. In order to improve the clustering accuracy the authors proposed new hybrid KHM model.