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5th International Conference on Data Intelligence and Cognitive Informatics, ICDICI 2024

作者： Rathi, Snehal Wamanacharya, Shubham Shah, Samkit Khedkar, Vijayshri BTACT'S Vishwakarma Institute of Information Technology Department of Computer Engineering Pune India Symbiosis Institute of Technology Department of Computer Science & Engineering Pune India

ISBN: (纸本)9798350389609

Climate change still implies risks for economic security, such as for agriculture and its productivity and, therefore, national economic potential. Although similar approaches have been used in publications concerning individual crops or soil types, the application of climatology parameters in agriculture and it limited indices have not been optimal. Owing to the recognized limitations of traditional linear productivity models, this thesis subjects' agricultural productivity to a Cobb-Douglas multi-factorial modeling approach through intensive levels of data decomposition. The proposed approach enabled the researchers to adjust the impact of climate parameters during students' evaluations in the secondary education curricula. Additionally, frameworks which relate temperature variations and crop growth do exist, and therefore the temperature and agriculture performance model effects determinants were determined using complex analysis of temperature relations and crop outputs. This highlights the various factors affecting production, its structure, and the relative importance of some conditions in agriculture and explains their dynamics depending on the changes in growth factors. Hence, a set of factors employed in the modeling resulted mainly from economic conditions, production system structures and advanced agricultural technology applications in the economy as prediction © 2024 IEEE.

关键词： Agricultural Data Analysis Climate Impact on Agriculture Crop Growth Days Growth Degree Days (GDD) R Programming

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Dimensional Measurement System Using Canny Edge Detection Algorithm

Dimensional Measurement System Using Canny Edge Detection Al...

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2023 International Conference on Recent Advances in Science and engineering technology, ICRASET 2023

作者： Bhatele, Priyanka Shivankar, Ishan Chogule, Shrey Saraswat, Shivansh Patel, Shraddha Sabut, Shreya Nale, Shreya Vishwakarma Institute of Technology Depatment of Information Technology Pune India Vishwakarma Institute of Technology Depatment of Computer Engineering Pune India Vishwakarma Institute of Technology Department of Electronics & Telecomminication Enginnering Pune India Vishwakarma Institute of Technology Department of Computer Engineering Pune India Vishwakarma Institute of Technology Depatment of Chemical Engineering Pune India

ISBN: (纸本)9798350306927

In the realm of industrial and scientific applications, accurate dimensional measurement plays a pivotal role in ensuring quality control and process optimization. This is a vital topic of computer vision problems. This study presents a project that uses reference markers to measure height and width of objects from their pictures rather than using conventional methods. Project model managed to achieve around 99.9% accuracy, whereas this was not provided in other works. © 2023 IEEE.

关键词： Python

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An Exploration of Deep Learning Techniques for the Detection of Grape Diseases

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Recent Advances in computer Science and Communications 2024年第2期17卷 1-12页

作者： Pandey, Kavita Chandak, Abhimanyu Department of Computer Science & Engineering and Information Technology Jaypee Institute of Information Technology Noida India

Plant diseases are one of the major contributors to economic loss in the agriculture industry worldwide. Detection of disease at early stages can help in the reduction of this loss. In recent times, a lot of emphasis has been done on disease detection due to the overall increase in production as well as the loss of grape number. With deep learning, having a promising future and having the advantages of automatic learning and feature extraction, the use of these techniques has now been widely spread. This paper reviewed the existing deep-learning techniques available for grape disease detection. Firstly, covering the various steps in a grape disease detection model ranging from the various sources of image acquisition, the different image augmentation techniques and the various models used, and the parameters required to evaluate. Secondly, the study summarizes the im-portant findings of all literature available on the theme. The paper also tries to highlight the various challenges faced by the researchers and the common trend among them, so that future research on the topic can achieve higher performance. © 2024, Bentham Science Publishers. All rights reserved.

关键词： Losses

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Global-local term fusion for optimised community Q&A topic modelling

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International Journal of Innovative Computing and Applications 2024年第1期15卷 50-69页

作者： Prabha, Sneh Sardana, Neetu Department of Computer Science and Engineering and Information Technology Jaypee Institute of Information Technology Noida India

Community question and answer (Q&A) websites have become invaluable information and knowledge-sharing sources. Effective topic modelling on these platforms is crucial for organising and navigating the vast amount of user-generated content. To address these challenges, we propose a novel global-local term fusion with optimised community (GLOCOM) Q&A topic modelling approach that leverages both local and global term importance to enhance topic modelling on community Q&A websites. GLOCOM combines term frequency-inverse document frequency for local importance and entropy for global importance. Further, we employ fuzzy clustering to enhance the representation of multifaceted topics. Furthermore, clustering results are optimised using a genetic algorithm (GA) to refine cluster assignments and centroids. We compared the proposed model with baseline models LDA and FLSA. GLOCOM has performed consistently well for all topic numbers. It has shown an improvement of 8.86% in silhouette score as compared to LDA and excelled for datasets with size > 3 MB. Copyright © 2024 Inderscience Enterprises Ltd.

关键词： Inverse problems

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Identity-Based Access Control in IoT: Enhancing Security through Mutual Cryptographic Authentication and Context Awareness 3

Identity-Based Access Control in IoT: Enhancing Security thr...

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3rd IEEE International Conference on Mobile Networks and Wireless Communications, ICMNWC 2023

作者： More, Priyanka Sakhare, Sachin Mahalle, Parikshit Smt. Kashibai Navale College of Engineering Department of Computer Engineering Vishwakarma Institute of Information Technology Pune India Vishwakarma Institute of Information Technology Department of Computer Engineering Pune India Vishwakarma Institute of Information Technology Department of Artificial Intelligence and Data Science Pune India

ISBN: (纸本)9798350317022

The proposed methodology strengthens security and privacy in IoT networks through mutual cryptographic authentication, employing Elliptic Curve Cryptography, Diffe Hellman for key exchange, and encryption methods for robust identity verification. Context awareness, considering factors like device type, communication type, successful transfers, and device behaviour, enhances access control decisions dynamically. This approach bolsters network security, defending against unauthorized access and potential threats. Identity-based access control streamlines access rights management, dynamically setting permissions for scalable network expansion. Combining cryptographic authentication and context sensitivity, this methodology emerges as a potent tool for securing IoT networks, ensuring data integrity, and preserving user privacy. Its versatility makes it applicable across diverse loT scenarios, offering a flexible and scalable access control solution. Overall, devices get authenticated with each other through identity based on clusters formed by context parameters and access rights are set to the cluster head. The cluster head is dynamically updated from time to time considering the context parameters. © 2023 IEEE.

关键词： context clustering decryption Elliptic Curve Cryptography encryption identity-based access control

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Satellite Image Processing for Cloud Detection and Movement Analysis 8

Satellite Image Processing for Cloud Detection and Movement ...

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8th International Conference on I-SMAC (IoT in Social, Mobile, Analytics and Cloud), I-SMAC 2024

作者： Dhore, M.L. Kate, Sumedh Khandelwal, Dipkul Khandetod, Arya Kharade, Aishwarya Vishwakarma Institute of Technology Department of Computer Engineering Pune India

ISBN: (纸本)9798350376425

The rapid development of satellite technology has resulted in an exponential growth in the availability of high-resolution satellite images, which presents both opportunities and challenges for image processing and classification. The study provides a comprehensive overview of the state-of-the-art techniques for satellite image processing and classification, with an emphasis on recent developments in machine learning and deep learning approaches. Understanding environmental dynamics, tracking weather trends, and assisting with disaster relief operations all depend on satellite imaging. Unfortunately, clouds frequently obscure these photos, making it challenging to precisely follow atmospheric conditions and analyse the Earth's surface. In order to improve weather forecasting and catastrophe management, the research work creates a satellite image processing system that uses machine learning to identify clouds, eliminate them, and forecast their *** fields, including disaster management, agriculture, urban planning, environmental conservation, climate research, renewable energy, forestry, and geospatial intelligence, are greatly impacted by satellite image processing and cloud detection. Through the provision of enhanced, unobstructed satellite imagery and precise cloud movement forecasts, the project improves capacities for natural resource monitoring and management, better urban development, climate research assistance, energy production optimisation, forest protection, and defence operations support. Accurate satellite data analysis facilitates more informed decision-making, which in turn improves environmental management, readiness for disasters, and strategic planning in these vital areas. © 2024 IEEE.

关键词： Optical flows

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PerceptiGuard: Unveiling DeepFakes Through Enhanced Media Perception

PerceptiGuard: Unveiling DeepFakes Through Enhanced Media Pe...

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2024 IEEE Silchar Subsection Annual Conference, SILCON 2024

作者： Phatangare, Sheetal Tekade, Om Thakare, Prathamesh Wankhade, Abhishek Wankhade, Purva Vishwakarma Institute of Technology Department of Computer Engineering Pune India

ISBN: (纸本)9798331540821

This research presents a comprehensive approach to developing a multi-modal deepfake detection system leveraging advanced deep learning architectures. The primary objectives include the creation of a robust detection model, evaluation across various manipulation techniques, and integration into practical applications. Utilizing state-of-the-art neural networks, the system aims to enhance detection accuracy and offer a user-friendly interface for real-world deployment. The proposed architecture incorporates preprocessing steps such as video splitting, detection, and face cropping, followed by feature extraction and video classification using a combination of ResNet and LSTM networks. The model's performance is assessed through confusion matrix evaluation, ensuring reliability across diverse deepfake scenarios. © 2024 IEEE.

关键词： Generative adversarial networks

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Classification Models of Music Recommendation System for Mental Health Improvement: A Comparative Study 1

Classification Models of Music Recommendation System for Men...

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1st International Conference on AIML-Applications for engineering and technology, ICAET 2025

作者： Agarkar, Aarti Amod Ghuge, Kalyani Dindore, Shriram Dhakne, Suvidha Dhakate, Atharva Mane, Arya Vishwakarma Institute of Technology Computer Engineering Department Pune India Vishwakarma Institute of Technology CSE - AIML Department Pune India

ISBN: (纸本)9798350355611

Artificial Intelligence (AI) became part of our daily life. Due to the increased capability of computation power, AI significantly impacts human life and changing the social systems as well. On one side AI making our life easier but at the same time we are facing challenges like mental health issues. Lot of people are facing anxiety, insecurity and depression. Music is one of the remedy for improving mental health. In this paper, we focus on the music recommendation system for mental health improvement. The input imbalanced data is balanced to reduce its imbalance ratio. The output dataset is used to train the classification models including Random Forest, Support Vector Machine (SVM), Decision Trees, logistic regression, XGBOOST and ADABOOST. The comparative results are presented based on the experimentation. Results shows that XGBOOST outperforms other classification models with an accuracy of 98.1%. © 2025 IEEE.

关键词： Electronic health record

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A Comprehensive Visual Debugger For Error Resolution in C++ 15

A Comprehensive Visual Debugger For Error Resolution in C++

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15th International Conference on Computing Communication and Networking Technologies, ICCCNT 2024

作者： Uke, Shailaja Patankar, Abheerav Patil, Aaditya Patwardhan, Srujan Phand, Swaraj Vishwakarma Institute of Technology Department of Computer Engineering Pune India

ISBN: (纸本)9798350370249

This paper introduces a sophisticated visual debugger that seamlessly integrates C++ code analysis with C # WPF visualisation for an enhanced debugging experience. The tool operates by extracting symbol information from target C++ source files during debugging sessions, utilizing PDB files, specifically tailored for the Visual Studio environment. The core functionality of the tool involves the extraction and storage of symbol information within a meticulously designed stack frame and stack trace classes. Leveraging C++ capabilities, the project captures not only call stack information but also variables and data structures associated with each stack frame, providing a comprehensive view of the program's execution state. To facilitate interoperability and visualization, the project employs a marshalling mechanism to seamlessly transfer the extracted data from the C++ backend to a C# WPF frontend. The Windows Presentation Foundation application serves as an intuitive and interactive interface, presenting the call stack alongside associated variables and data structures in a visually appealing manner. This tool is positioned to significantly enhance the debugging process for developers working in C++ within the Visual Studio environment. By seamlessly integrating symbol extraction, data structuring, marshalling, and visualization, it provides a holistic and efficient solution for diagnosing complex code scenarios. The resulting visualization aids developers in gaining a deeper understanding of their code's execution flow, enabling quicker identification and resolution of issues during the debugging process. © 2024 IEEE.

关键词： Interoperability

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Online News: Event Detection and Community Identification 8th

Online News: Event Detection and Community Identification

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8th International Conference on information and Communication technology for Intelligent Systems, ICTIS 2024

作者： Kulkarni, Radhika V. Suryawanshi, Snehal Shirsath, Aditya Sonone, Swati Phapale, Siddhi Department of Computer Engineering Vishwakarma Institute of Technology Pune India

ISBN: (纸本)9789819766833

Nowadays, reading online news is very common among people. The amount of information on the web is growing at a rapid pace, which is driving up the consumption of online news. As a result, a system to gather and disseminate significant real-world events from massive amounts of web data is now required. In addition, a lot of businesses rely their judgements on global events that happen every day. One of the most important tasks is event recognition, which is finding news articles about the same occurrence and grouping them together. This method improves user navigation and gives news pieces a conceptual structure. To group linked news documents, it makes use of TF-IDF analysis, time-series analysis, and community detection. For interactive investigation and analysis, the system interfaces with an easy-to-use website that offers sentiment analysis and 3D visualizations for improved interpretability. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

关键词： Community detection Event detection News stream

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