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Quantum computing for Climate Change: A Comprehensive Review of Current Applications, Challenges, and Future Directions 15

Quantum Computing for Climate Change: A Comprehensive Review...

引用

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

作者： Ashwani, Siddhant Tripathy, Aayushi Jeeban Karna, Siwani Reddy Jahanve, Poluru Rajagopal, Shinu M. Amrita Vishwa Vidyapeetham Amrita School of Computing Department of Computer Science and Engineering Bengaluru India

ISBN: (纸本)9798350370249

The need for creative ideas to address the growing challenges posed by climate change has become critical. This paper explores the various uses of quantum computing for mitigating climate change, with an emphasis on energy optimization, improved climate modeling, and weather forecasting. Environmental modeling, chemistry, material science, carbon capture techniques, and other significant applications have also been discussed. Finding important approaches, results, and associated technological constraints is the current state of study. Examining relevant case studies, the review suggests strategic directions for future research on climate change enabled by quantum computing. It serves as an essential tool for scientists, policymakers, and researchers, enabling a deeper comprehension of the potential of quantum computing in environmental science and encouraging multidisciplinary cooperation for the long-term mitigation of climate change. © 2024 IEEE.

关键词： and energy optimization carbon capture climate change climate modeling energy optimization quantum computing

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Deep Learning for Autism Detection Using Eye Tracking Scanpaths 2

Deep Learning for Autism Detection Using Eye Tracking Scanpa...

引用

2nd IEEE International Conference on Interdisciplinary Approaches in Technology and Management for Social Innovation, IATMSI 2024

作者： Supritha, R. Bharathi Mohan, G. Amrita Vishwa Vidyapeetham Amrita School of Computing Department of Computer Science and Engineering Chennai India

ISBN: (纸本)9798350360523

Autism spectrum disorder (ASD) is a neurodevelopmental condition marked by difficulties in social interaction, communication, and limited repetitive behaviors, with symptoms varying significantly among individuals. Eye tracking holds promise in autism detection due to its unique ability to capture and analyze visual attention patterns, providing insights into the cognitive processes and atypical visual behaviors associated with ASD. Eye-tracking technology offers a unique perspective, allowing the observation and quantification of visual attention patterns, which may reveal distinctive features associated with ASD. These visualizations represent how individuals, particularly those with ASD, explore and engage with stimuli. In this research, we propose a novel approach using deep learning models, specifically DenseNet-201, EfficientNet B7, ResNet-50, and MobileNetV2, to analyze eye-tracking scan paths for ASD detection. The dataset focuses on visualizations of eye-tracking scan paths, primarily involving individuals with ASD. The study yielded promising results, with the deep learning models achieving accuracies of 94.97%, 94.74%, 84.21%, and 92.45%, respectively. DenseNet-201 demonstrated the highest accuracy at 94.97%. The research contributes to advancing early diagnosis and intervention strategies for individuals with ASD. © 2024 IEEE.

关键词： Eye tracking

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A Secure Approach for Strengthening Session Management with Custom Session Handlers 2

A Secure Approach for Strengthening Session Management with ...

引用

2nd International Conference on Self Sustainable Artificial Intelligence Systems, ICSSAS 2024

作者： Kumaran, U. Gurupriya, M. Reddy, Annem Gnaneswara Nithin, G. Bhanusri, Kodati Amrita School of Computing Amrita Vishwa Vidyapeetham Department of Computer Science and Engineering Bengaluru India

ISBN: (纸本)9798350368413

Session management is the underlying security mechanism that is instrumental in protecting the security and integrity of web applications' user sessions. The research is dedicated to the examination of session administration solutions in web applications to provide secure user sessions and minimize the risks of session hijacking and session fixation. It touches on session management before and after user login, breaking it down into session maintenance. The custom session handler offers passive protection against session hijacking via session management using a MySQL database. This approach provides a safe way of creating and managing sessions, validating them as well as handling session expiration and performance optimization. The implementation intends to strengthen session securities of users, therefore, increasing the safety and reliableness of web applications © 2024 IEEE.

关键词： Enhancing security Session management Vulnerabilities Web applications

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A Sustainable Privacy-Preserving Aggregation Authentication Protocol for Smart Grid 1

引用

2nd International Conference on Smart Grid Energy Systems and Control, SGESC 2023

作者： Chaudhary, Dharminder Soni, Tanmay Singh, Soumyendra Durgarao, M.S.P. Gupta, Surisetty Mahesh Chandra Department of Computer Science and Engineering Amrita School of Computing Amrita Vishwa Vidyapeetham Chennai India

ISBN: (数字)9789819976300

ISBN: (纸本)9789819976294

Smart grid (SG) is an advanced framework for controlling computers, automation, new technologies, and smart equipment that is more efficient and dependable. Smart grid possesses advanced self-healing capabilities and enables electricity customers to become active participants. Both security and privacy are two very important attributes of SG communication. The proposed model is efficient for communication between smart grids which uses a privacy-preserving aggregation mechanism. The model structure uses super increasing sequences to organize data and then encrypts it using the homomorphic Paillier approach. Data aggregation is done directly on cipher at local gateways without following any decryption for data transfers from users to smart grid operation center. The aggregate outcome of the source data may be accessed at the operation center that saves time. Finally, our findings demonstrate that the proposed method supports batch verification that makes it cost-effective in terms of computing and communication as compared to existing architectures. The proposed design is fast symmetric encryption, and it is suitable for massive user groups, and it can be adopted to support the flexible and rapid growth of residential scales in smart grids. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd 2024.

关键词： Smart power grids

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Implementation and Analysis of TCP CUBIC Congestion Control System in Mininet 9

Implementation and Analysis of TCP CUBIC Congestion Control ...

引用

9th IEEE International Conference for Convergence in Technology, I2CT 2024

作者： Sunder, S Navin Akathya, Ve Ram Seshadri, Samarth Rajagopal, Shinu M. Bhaskaran, Sreebha Amrita Vishwa Vidyapeetham Amrita School of Computing Department of Computer Science And Engineering Bengaluru India

ISBN: (纸本)9798350394474

In the realm of data transfer dynamics, an intricate comprehension of congestion control is imperative for the seamless optimization of network performance. This study rigorously delves into the complexities, unveiling discernible disparities between sending rates and throughput. Emphasizing the critical role of congestion control, the research highlights escalating retransmissions and congestion as pronounced inefficiencies. The proposed methodology encompasses a thorough examination of packet loss, network utilization, and queuing delays, paired with the implementation of effective congestion control strategies. Post-implementation, the results demonstrate a significant enhancement in network performance, characterized by adaptive sending rates and minimized inefficiencies. This research underscores congestion control's pivotal role in optimizing performance, offering valuable insights for achieving an efficient and responsive network. © 2024 IEEE.

关键词： Data transfer

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Chatbot to chat with medical books using Retrieval-Augmented Generation Model 3

Chatbot to chat with medical books using Retrieval-Augmented...

引用

3rd IEEE North Karnataka Subsection Flagship International Conference, NKCon 2024

作者： Bhavani Peri, Sai Deepa Santhanalakshmi, S. Radha, Radha Department of Computer Science & Engineering Amrita School of Computing Amrita Vishwa Vidyapeetham Bengaluru India

ISBN: (纸本)9798350364569

This research paper presents a novel AI tool aimed at revolutionizing medical education by addressing the specific needs of medical students, fostering effective learning, and managing stress. The implementation leverages cutting-edge technology known as Large Language Models (LLMs), with a focus on utilizing ChatGPT4, Streamlit, and Trulens. The digital assistant serves as a friendly and accurate resource, responding promptly to complex medical queries, thereby optimizing study time. The study meticulously examines the balance between technical innovation and practical benefits, emphasizing the project's goal of not only creating a sophisticated tool but also providing tangible assistance to medical *** report outlines the successful development and deployment of the AI-powered study buddy, showcasing its potential to significantly improve learning environments, particularly in demanding fields such as medicine. Notably, the project empha-sizes the importance of groundedness in its chatbot, achieving an impressive accuracy rate of approximately 84% for a single textbook. The integration of Streamlit, ChatGPT4, and Trulens contributes to creating a seamless and user-friendly experience for medical *** research underscores the broader implications of AI in education, demonstrating how advancements in technology can positively impact learning outcomes. By reducing the time spent on information retrieval, the AI study buddy empowers medical students to concentrate more on core learning objectives, ultimately facilitating their journey to becoming proficient and successful medical practitioners. © 2024 IEEE.

关键词： Medical education

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Securing Smart Home IoT devices using Hyperledger Fabric 15

Securing Smart Home IoT devices using Hyperledger Fabric

引用

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

作者： Pranesh, R. Lalith Guptha, B. Aswinkumar, K. Pramoth, B. Abirami, K. Amrita Vishwa Vidyapeetham Amrita School of Computing Department of Computer Science and Engineering Coimbatore India

ISBN: (纸本)9798350370249

The rapid growth of Smart Home applications has broadened the scope for a wide range of security concerns. Blockchain technology, specifically Hyperledger Fabric, offers a promising solution. The proposed model explores its application, leveraging the Fablo toolkit to enhance the security of Smart Home IoT devices. The decentralized nature of Hyperledger Fabric, with features such as its consensus mechanism and chaincode, helps mitigate common security issues like unauthorized access and device tampering. The resultant tamperproof network, coupled with favorable metrics like latency and transaction throughput, underscores the robustness of the proposed model. Our model promises low latency and high transaction throughput. The metrics assist the model in securely and efficiently handling a large number of transactions without compromising on speed and security. © 2024 IEEE.

关键词： Smart homes

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XAI - Empowered Ensemble Deep Learning for Deepfake Detection 15

XAI - Empowered Ensemble Deep Learning for Deepfake Detectio...

引用

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

作者： Kumar, Amidela Anil Dheepthi Priyangha, S.J. Meghana, P. Dheeraj, Muppalla Aarthi, R. Amrita Vishwa Vidyapeetham Amrita School of Computing Department of Computer Science and Engineering Coimbatore India

ISBN: (纸本)9798350370249

Recent technologies have evolved rapidly, allowing the creation of fake videos/images that are realistic. These artificial media pieces have provoked grave worries about the possibilities of their misuse in different areas like politics, journalism, and communication. Consequently, the demand for deepfake detection methods is increasing. In response to this growing threat, there is an increasing demand for robust deepfake detection methods. This paper proposes an ensemble-based approach for deepfake detection, leveraging deep learning techniques. Specifically, we employ a combination of CNN models, including VGG, Xception, RegularizedConvNet, and RegularizedConvDenseNet, designed for image classification. Our approach integrates predictions from multiple models to enhance detection accuracy and reliability. Specifically, the base is formed by the ensemble of RegularizedConvNet and RegularizedConvDenseNet, which cooperate to prevent the spread of deepfakes and protect digital integrity. Experimental results show that our Ensemble method achieve better detection values with accuracy of 94.5% and AUC of 0.98. © 2024 IEEE.

关键词： Deep reinforcement learning

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Adaptive Malware Detection in Android: An Active Learning and XGBoost Approach 5

Adaptive Malware Detection in Android: An Active Learning an...

引用

5th IEEE Global Conference for Advancement in Technology, GCAT 2024

作者： Prattipati, Anshitha Saravanan, S. Veluchamy, S. Amrita Vishwa Vidyapeetham Amrita School of Computing Department of Computer Science and Engineering Chennai India

ISBN: (纸本)9798350376685

The growing dependence on mobile devices like smartphones has caught the consideration of cybercriminals. It creates numerous chances for intruders to infiltrate and compromise them. This current continuing challenge demands the need for more efficient and effective methods to shield Android users by recognizing various malwares. Though researchers and companies strive for a steady and consistent approach to increase the classification algorithms accuracy to categorize malicious Android applications, the search for the ultimate answer continues. Hence, we introduce an active learning-based classifier to advance the accuracy of classification in Android mal-ware. In our proposed system, we find the prediction probability of each test instance. If this probability falls below a certain threshold, we generate a similar test instance, incorporate it into the original dataset and retrain the model to get better accuracy of the classification. We evaluated the proposed system on CIC-Maldroid2020 dataset which comprises of 17,341 instances with five various android application categories consisting of Adware, Banking, SMS, Riskware, and Benign. This experiment results imply that the XGBoost (eXtreme Gradient Boosting) algorithm outperforms the various other five machine learning algorithms. Further, the active learning component of our proposed system improves accuracy from 95.34% to 98.5%. © 2024 IEEE.

关键词： Active learning

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An Integrated Mobile Applications for Enhancing Women's Safety - A Comprehensive Approach 2

An Integrated Mobile Applications for Enhancing Women's Safe...

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2nd IEEE International Conference for Women in Innovation, Technology and Entrepreneurship, ICWITE 2024

作者： Ashwini, K. Perla, Sree Neha Amrita Vishwa Vidyapeetham Amrita School of Computing Department of Computer Science and Engineering Chennai India

ISBN: (纸本)9798350383287

Women's safety is a critical concern in today's society, necessitating innovative solutions that leverage technological advancements. This Proposed paper proposes two different applications, namely Womenify for the user especially women and Wopo for police which is combined with computer-aided dispatch (CAD) software to enhance women's safety and improve police response time. This research paper lays the groundwork for a comprehensive technical solution and presents valuable insights for creating safer communities for women. The proposed Womenify application will enable users to scan their surroundings using GPS tracking, access crime data in required areas to know whether the place is safe or not, and can also trigger emergency alerts. On the police side, the Wopo application provides patrolling schedules and real-time notifications. Further, the developed app can also be integrated with CAD software, using real-time data, ensuring easy accessibility for illiterate or unemployed women, expanding features, incorporating advanced technologies like predictive policing, and collaborating with law enforcement agencies. The effectiveness and functionality of the proposed application are evaluated through a feedback-based evaluation process which yielded positive results, indicating their effectiveness in enhancing women's safety. © 2024 IEEE.

关键词： Law enforcement

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