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Intelligent and Real-Time Intravenous Drip Level Indication 4th

Intelligent and Real-Time Intravenous Drip Level Indication

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4th International Conference on IoT Based Control Networks and Intelligent Systems, ICICNIS 2023

作者： Krishnapriya, V.S. Suresh, Namita Srilakshmi, S.R. Abhishek, S. Anjali, T. Department of Computer Science and Engineering Amrita School of Computing Amrita Vishwa Vidyapeetham Amritapuri India

ISBN: (纸本)9789819965854

The ability of medical technology to diagnose and cure illnesses more successfully has revolutionised the healthcare sector. However, there is still a gap in monitoring intravenous (IV) drip bottles in real time. Real-time monitoring of IV bottles is crucial to prevent backflow of blood from the patient to the empty drip bottle, which can lead to severe consequences, including the patient's death. To address this issue, an Internet of Things (IoT)-based IV drip monitoring system has been proposed. The system incorporates a device that detects the fluid solution level and informs medical personnel via a buzzer and a website that shows the IV drip fluid levels of each patient in real time. This feature enables nurses to monitor each patient’s fluid intake and take necessary actions, thereby avoiding potential risks associated with overconsumption. © 2024, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Bottles

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Enhancing Digital Image Security using Visual Cryptography Integrated with AES and RSA Encryption Techniques 3

Enhancing Digital Image Security using Visual Cryptography I...

引用

3rd IEEE Delhi Section Flagship Conference, DELCON 2024

作者： Adabala, Prajna Aasritha Gowtham, Rajani Sai Venkata Jaishitha, Thambi Rishisri, Vadluri Sai Kavitha, C.R. Amrita School of Computing Amrita Vishwa Vidyapeetham Department of Computer Science and Engineering Bengaluru India

ISBN: (纸本)9798331518592

Visual cryptography (VC) designed to secure visual information such as images and text by dividing it into multiple shares. A key advantage of visual cryptography is its ability to decrypt information without the need for computational devices, using simple human visual perception. The paper is centered on visual cryptography with examples such as Visual Secret Sharing, Advanced Encryption Standard (AES), and Rivest-Shamir-Adleman (RSA) during the encryption and decryption stages. The specific algorithms' efficiency in increasing security and improving image quality is discussed. The quality and overall accuracy of the reconstructed images are measured by the Peak Signal-to-Noise Ratio (PSNR). The benchmark images are used to compare the results in terms of encryption and decryption time and PSNR value. The findings signify the integration of AES and RSA in improving security without compromising image quality and computational complexity. © 2024 IEEE.

关键词： AES Decryption Encryption RSA Visual Cryptography

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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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Exploring Different Methods of Scanners and Parsers

Exploring Different Methods of Scanners and Parsers

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2024 International Conference on Advances in Modern Age Technologies for Health and engineering science, AMATHE 2024

作者： Asmitha, M. Panda, Niharika Amrita School Of Computing Department Of Computer Science And Engineering Amrita Vishwa Vidyapeetham Bengaluru India

ISBN: (纸本)9798350371567

Compiler design represents the intersection of art and science, where intricate algorithms and creative problem-solving converge to translate abstract human-readable code into machine-executable instructions. At the heart of this complex process lie the essential components of the scanner and parser, working in harmony to decode the syntax and semantics of programming languages. In this exploration of compiler design, embark on a journey into the realms of scanning and parsing, unraveling the intricacies that transform code into executable software. The scanner is the lexical analyzer, serves as the gate-keeper in the compiler's journey. Its main task is to meticulously break-down the source code into manageable units called as the tokens. From identifying keywords to recognizing variables and constants, the scanner lays the groundwork for the subsequent phases of the compilation process. In this study we are going to focus on how any model of scanners work based on given input. The parser, responsible for syntax analysis, ensures that these sequence of tokens adheres to the grammatical rules of the particular programming language which is being used. This study focus on how a token is treated in Bottom up and Top down like left recursion, left factoring, augmentation, parse tree, DFA etc. The choice of parsing algorithm, whether LL(1) A top down approach or SLR, LALR bottom up parser impacts the efficiency and accuracy of this process. This process follows checking first, follow, parse table, shift reduce conflicts the acceptance. Compiler design is more than a technical endeavor, it is a craft that demands precision, creativity, and a deep understanding of both programming languages and the intricacies of hardware architecture. The scanner and parser stand as gatekeepers at the entrance to a realm where human intent transforms into machine action, making compiler design a captivating field where innovation and standards converge. © 2024 IEEE.

关键词： Semantics

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News Topic Categorization on Telugu Dataset Using Deep Learning Models 15

News Topic Categorization on Telugu Dataset Using Deep Learn...

引用

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

作者： Deepika, M. Sree Subramanyam, N. Sri Lekhya Pranav, P. Shiva Reddy, Pulaputhuru Subramanyam Venugopalan, Manju Amrita Vishwa Vidyapeetham Amrita School of Computing Department of Computer Science and Engineering Bengaluru India

ISBN: (纸本)9798350370249

The digital age has ushered in an unprecedented era of data proliferation across various domains, with the news sector being no exception, accumulating vast amounts of information, often measured in petabytes. Manual classification of such voluminous data is impractical, particularly considering the complexity of languages like Telugu, belonging to the Dravidian family, renowned for its intricate morphological characteristics. Natural Language Processing (NLP) offers a promising avenue for tackling textual data, leveraging diverse word embedding techniques to enrich model representations. Notably, prior research in this domain has predominantly relied on count-based algorithms for word embeddings. However, in this investigation, we explore alternative approaches, specifically custom-built Deep Learning models integrated with word embeddings, to optimize the classification of newspaper articles. Through a series of methodical experiments, we endeavor to identify the most effective model architecture for this task, aiming to enhance the accuracy and efficiency of article categorization in Telugu. The proposed model has experimented with word embeddings such as FastText and GloVE with deep learning models like LSTM, Bi-LSTM, CNN. Among the models experimented, FastText in combination with CNN have reported the highest F1-Score of 0.93. © 2024 IEEE.

关键词： Categorization Deep Learning News data Word Embedding

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IoT Sensor Data Stream Compression with Hybrid Compression Algorithms 15

IoT Sensor Data Stream Compression with Hybrid Compression A...

引用

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

作者： Garikipati, Karthik Muppala, Tejaswi Vinitha Chowdary, A. Sahay, Apurvanand Amrita School of Computing Amrita Vishwa Vidyapeetham Department of Computer Science and Engineering Bengaluru India

ISBN: (纸本)9798350370249

The recent world advancement in technology especially in the use of IoT devices has posed some serious complications in terms of how effectively we can convey data, this is normally a result of the limited bandwidth and power capacity. In this paper, we look into the need for efficient data compression in IoT devices and come up with a new approach to compress the data stream needed for IoT sensors. In this paper, we propose to integrate Dynamic Huffman Coding with Run Length Encoding smoothly as one novel network coding strategy to decrease the load carried by the communication channels and at the same time ensure the originality of the transmitted data. The proposed method is based on the use of RLE to remove a lot of redundant data and dynamic Huffman coding for further data compression. When compared with other central algorithms like dynamic Huffman, static Huffman, RLE, LZW, ZLIB, LZMA, and BZ2 this hybrid approach provided more efficient compression ratios and consumed less power. Compression can be considered an essential paradigm for IoT devices because it can minimize the restrictions associated with the prevention of limited bandwidths and power sources that are characteristic of such devices, which results in improved data sending and a longer lifespan of devices. As substantiated by the findings from our experiments, this approach holds a high degree of effectiveness and, therefore, is suitable for the IoT domain with a scarcity of resources in particular. The contributions of this research support the promotion of compression strategies while considering the IoT-specific needs thus enhancing standard system outcomes and durability. © 2024 IEEE.

关键词： Bandwidth Constraints BZ2 Data Compression Dynamic Huffman Coding Hybrid Techniques Internet of Things (IoT) IoT Sensors LZMA LZW Power Constraints RLE Run-Length Encoding Static Huffman Coding ZLIB

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Evaluation of RPL and SDN-WISE in UAV assisted WSN data collection 2

Evaluation of RPL and SDN-WISE in UAV assisted WSN data coll...

引用

2nd International Conference on computer Vision and Internet of Things, ICCVIoT 2024

作者： Deepankumar, S. Rengaraj, R. Gupta, Boggarapu Mithil Raj Kumar Nalinadevi, K. Department of Computer Science and Engineering Amrita School of Computing Amrita Vishwa Vidyapeetham Coimbatore India

ISBN: (纸本)9781837242672

This paper evaluates the performance of the Routing Protocol for Low-Power and Lossy Networks (RPL) and the Software-Defined WIreless SEnsor network (SDN-WISE) approach in a IPv6 over Low-Power Wireless Personal Area Networks (6LoWPAN) network scenario. In this network scenario a mobile sink acting as an Unmanned Aerial Vehicle (UAV) is used for data collection in Wireless Sensor Networks (WSNs). A novel methodology is presented for generating efficient paths for the mobile UAV sink. It involves leveraging the K means clustering algorithm for finding the centroids which can cover the sensors within the transmission range. The Ant Colony Optimization technique is then used for traversing the centroids to solve the Travelling Salesmen problem (TSP). Key performance metrics such as average end-to-end delay, packet delivery ratio and energy consumption are analysed under varying conditions and sensor node densities. The study provides valuable insights into optimising UAV-assisted WSNs for enhanced performance and longevity in real-world applications. © The Institution of engineering & Technology 2024.

关键词： Ant colony optimization

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Detection and Classification of Respiratory Syndromes in Original and modified DCGAN Augmented Neonatal Infrared Datasets 5

Detection and Classification of Respiratory Syndromes in Ori...

引用

5th International Conference on Innovative Data Communication Technologies and Application, ICIDCA 2024

作者： Sarath, S. Nair, Jyothisha J. Department of Computer Science and Engineering Amrita School of Computing Amrita Vishwa Vidyapeetham Amritapuri India

In the current pandemic scenarios, a non-invasive method for determining a neonate's respiratory rate and categorizing them using a deep learning technique is highly pertinent. Acquiring an infrared neonatal dataset for detecting and classifying respiratory syndromes is challenging. The limited number of infrared videos and images representing different types of syndromes is a tremendous challenge to the accuracy of the deep learning model. This paper uses the Deep Convolutional Generative Adversarial Networks(DCGAN) with gradient penalty for the data augmentation. The Discriminator in a standard DCGAN architecture is a convolutional neural network (CNN) that receives an image as input and outputs a single scalar value that indicates the likelihood that the input image is real or fake. Adding a gradient penalty adds a regularisation term to the loss function. This modification helps to stabilize training by preventing mode collapse and generating higher-quality images. The augmented dataset helped to make the original imbalanced dataset more balanced and increased the size of the original dataset. When the accuracies of the deep learning models trained on the original and balanced augmented neonatal datasets were compared in this work, the model based on the balanced augmented dataset performed better. © 2024 The Authors. Published by Elsevier B.V.

关键词： Generative adversarial networks

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Cutting-Edge Steel Damage Classification Powered by Cloud Technology 15

Cutting-Edge Steel Damage Classification Powered by Cloud Te...

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

作者： Reddy, Pennabadi Devendra Reddy, K Satya Sampath Gnaneswarachary, P. Reddy, P. Hemanth Prashanth, Mrudula Rajagopal, Shinu M. Amrita School of Computing Amrita Vishwa Vidyapeetham Department of Computer Science and Engineering Bengaluru India

ISBN: (纸本)9798350370249

In this era of rapid technological advancement, the detection of metal damage has become increasingly crucial across various industries. The proposed work 'Cutting-Edge Steel Damage Classification Powered by Cloud Technology' aims to build an advanced system for real-time steel damage classification utilizing AWS services includes Rekognition, Lambda, and API Gateway that enables users to upload multiple images simultaneously for damage detection and classification, which will be an innovative approach to industrial defects detection which leads to their prevention. Such benefits of fast, accurate and scalable defect detection make it a critical asset for businesses expecting for exact and real-time solutions in every aspect. This study uses F1 score, precision, recall, and assumed threshold are as evaluation parameters. The use of AWS services is not just helping with model training and deployment, but it also provides failover mechanism and scaling capabilities to accommodate the varying workload demands. The model has the advantage of having rapid training time: 1.005 hours this shows the cloud infrastructure scalability and computational efficiency in dealing with the tasks requiring machine learning of complex nature. © 2024 IEEE.

关键词： Amazon API Gateway Amazon S3 AWS Lambda AWS Rekognition Cloud computing Damage Classification Grazing Pitted Steel detection

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