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RRSC-128/64-V1: a two-variant simple, fast, and secure lightweight stream cipher

International Journal of Information Technology (Singapore) 2025年 1-9页

作者： Chatterjee, Runa Chakraborty, Rajdeep Department of Computer Science and Engineering Netaji Subhash Engineering College West Bengal Kolkata 700152 India Department of Computer Science and Engineering Medi-Caps University Madhya Pradesh Indore India

Lightweight cryptography is now emerging as a new method for providing security to resource-constrained devices. Securing those devices from external hackers during data transmission is now becoming an important issue. This paper proposed a lightweight simple stream cipher which provides security and confidentiality of the data among resource-constrained devices. The proposed cipher comes in two variants: 128-bit and 64-bit based on the key size it used. The user can used any of these two variants as per application type and the features of the resources. Although the stream cipher design is simple but it delivers outstanding hardware performance compared to some well-known stream ciphers like Grain, Trivium, Mickey and two Grain-like stream ciphers Planet and Lizard. It proves its efficiency greater than all except Trivium. It also passed the 15 randomness tests of the National Institute of Standards and Technology (NIST). © Bharati Vidyapeeth's Institute of computer Applications and Management 2025.

关键词： Embedded system FPGA Hardware metrics LFSR Lightweight cryptography Lightweight stream cipher NFSR NIST Nonce Randomness Throughput

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A Novel Approach to Super-Resolution and Denoising: Refining Medical Image quality and Diagnostic Textual 2

A Novel Approach to Super-Resolution and Denoising: Refining...

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2nd International Conference on Advances in Computation, Communication and Information Technology, ICAICCIT 2024

作者： Anjum, Ayesha Tabassum, Husna Spoorthi, C.K. Kumar, Sujeet Swetha, S. Veena Department of Computer Science & Engineering HKBK College of Engineering Karnataka India

ISBN: (纸本)9798331541217

One of the promising recent advances in medical imaging is indeed the successful exploration of GANs for applications such as image super-resolution and text enhancement. Most GAN-based approaches, however, have been driven for a single modality: enhancing the qualityof images or text clarity-while simultaneously eliciting little attention towards the two interrelated aspects. A new dual- GAN framework is therefore proposed to overcome this limitation by combining the merits of both Image Super- Resolution GAN and Text Enhancement GAN. In this merged approach, both the resolution of images and the adequacy of the textual annotation improved to enhance diagnostic accuracy as well as improve the visualization of small lesions and tissue structures in medical images. The system works on the principle of cross-domain benefit sharing;enhancement in either quality, the image, or the text, naturally boosts the quality of the other. The performance of the proposed dual-GAN system is measuredthrough some key metrics, such as Peak Signal-to-NoiseRatio (PSNR), Structural Similarity Index (SSIM) and Optical Character Recognition (OCR) accuracy to provide clear evidence of significant improvement in both image andtext qualities as compared with other conventional methods. This innovation improves the process of clinical decision- making in the sense that clearer images and text are more accurate. The approach has tremendous potential for much wider practical applications: document scanning, surveillance, astronomy, and microscopy-all applications where textual and visual clarity are important for precision and analysis. © 2024 IEEE.

关键词： Image annotation

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Advanced Machine Learning Approaches for Infant Cry Classification using Audio Feature Extraction 2

Advanced Machine Learning Approaches for Infant Cry Classifi...

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2nd IEEE International Conference on Integrated Intelligence and Communication Systems, ICIICS 2024

作者： Nukala, Vijay Kumar Motheline, Sathyam Reddy Kolasanakoti, John Wesley Vankayalapati, Sunil Velupula, Venu Dodda, Venkata Reddy Department of Computer Science and Engineering Narasaraopeta Engineering College Narasaraopeta India

ISBN: (纸本)9798331504960

This study develops a machine learning framework to classify infant cries using 457 audio features, including time domain features like Zero-Crossing Rate (ZCR) for frequency analysis and Quadratic Mean RMS for power measurement. Frequency-domain features, notably Mel-Frequency Cepstral Coefficients (MFCCs), alongside Mel-spectrograms and Time Series Imaging (TSI) provide detailed visualization of audio signals. The data is split into 80% training and 20% testing sets with 10-fold cross-validation for tuning. Several machine learning models, including Logistic Regression, Support Vector Classifier, Decision Trees, Random Forests, and XGBoost, are evaluated. Hyperparameter tuning through grid search shows the Random Forest model with MFCC features achieves a peak accuracy of 98.03%. Evaluation using accuracy, confusion matrices, and feature importance highlights MFCC’s role in classification. Results demonstrate the effectiveness of combining machine learning with classical feature extraction for infant cry classification, supporting early health monitoring. Future work includes ensemble techniques to boost performance. © 2024 IEEE.

关键词： Spectrographs

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AI Enhanced Video Sequence Description Generator

AI Enhanced Video Sequence Description Generator

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2024 International Conference on Advances in Data engineering and Intelligent Computing Systems, ADICS 2024

作者： Aravind, R. Ashwin, G. Srinivasan, N. Rajalakshmi Engineering College Department Of Computer Science And Engineering Chennai India

ISBN: (纸本)9798350364828

This paper centers on pushing the boundaries of AI and computer vision through an inventive approach to video captioning, leveraging the powerful Contrastive Language Image Pretraining (CLIP) model. In stark contrast to conventional methods, our proposed system ingeniously merges CLIP's unique ability to comprehend both textual and visual components, establishing a unified embedding space. This integration results in heightened context awareness and semantic depth, revolutionizing the comprehension of video content and outperforming traditional approaches. The AI-enhanced video captioning system represents a significant leap forward in the realm of generating precise and meaningful captions for a wide array of videos. The distinctive feature of our system lies in its preprocessing modules, adept at extracting intricate visual features and encoding nuanced textual descriptions. Additionally, we fine-tune the CLIP model on an extensive dataset of video-caption pairs, allowing it to capture complex relationships between visual and textual elements. This approach ensures that the model not only excels in providing accurate captions for diverse video content but also exhibits a remarkable ability to generalize well to previously unseen data. The result is a robust and contextually relevant captioning system that contributes to the evolution of AI applications in video understanding. © 2024 IEEE.

关键词： computer vision

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Revolutionizing E-Commerce Security: A Secured Infrastructure Utilizing BlockChain 15

Revolutionizing E-Commerce Security: A Secured Infrastructur...

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

作者： Gupta, Ashish Yadav, Harsh Sharma, Shanu ABES Engineering College Department of Computer Science and Engineering Ghaziabad India

ISBN: (纸本)9798350370249

With the increase in technological advancement in the world, there is a huge shift going on as everyone wants to shift online and have a broader market available to them. E-commerce websites are a platform where a lot of orders and transactions are being made daily. Nowadays the market is shifting to an e-commerce platform for a bigger market and profit their business. With this technical advancement, there comes a threat to the information and data that are available, since most of the transactions are being recorded online. Thus, there is always a concern related to the security of user data, which can also be resolved using blockchain. Blockchain Technology which was proposed by Satoshi Nakamoto as a decentralized currency component of bitcoin technology. It also provides security to store data as it is immutable in nature. The main idea is that all the data of the user will be stored on blockchain so that it cannot be breached and all the information about the user remains preserved. In this article, a preliminary analysis is performed on existing work to understand the different types of security issues in the E-Commerce Sector. Further, the applicability of Blockchain is explored to provide a more secure infrastructure for the users and administration using E-Commerce services. To showcase the applicability of blockchain, here an E-Commerce platform is also developed using ShopKart, where the product information and transaction information is kept secure using Smart Contract in Blockchain. Furthermore, the cryptocurrency-based payment gateway is also introduced for the worldwide acceptability of payments. © 2024 IEEE.

关键词： Smart contract

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Bus Route Tracking System 7th

Bus Route Tracking System

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7th IFIP TC 12 International Conference on Computational Intelligence in Data science, ICCIDS 2024

作者： Rubesh Muthuvel, R. Nithish Sankar, B. Kasirajan, P. Dheenathayalan, S. Department of Computer Science and Engineering National Engineering College Kovilpatti India

ISBN: (纸本)9783031699856

This research paper explores the challenges faced by daily bus commuters and presents a transformative live route monitoring system designed to address these issues. The project focuses on local buses and utilizes a user-friendly web application integrated with Google Maps. Key features include personalized notifications, precise real-time tracking, and historical performance data for efficient journey planning. The integration of crowd-sourced insights and multimodal functionality enriches user decision-making, while emergency communication, multilingual support, and energy-efficient tracking contribute to an enhanced overall experience. The project also includes a community engagement platform to encourage collaboration and feedback. Accessibility features and offline functionality ensure inclusivity and convenience, while strategic partnerships with local transport authorities bolster system accuracy. © IFIP International Federation for Information Processing 2024

关键词： Decision making

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Terrestrial-Satellite Communication Techniques and Challenges for 6G 5

Terrestrial-Satellite Communication Techniques and Challenge...

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5th International Conference on IoT Based Control Networks and Intelligent Systems, ICICNIS 2024

作者： Suriya, M. Yogeshwaran, R. Sivaram Kumar, S. Subesh, R. Syam Sundar, M. Sri Eshwar College of Engineering Department of Computer Science and Engineering India

ISBN: (数字)9798331518097

ISBN: (纸本)9798331518097

The introduction of 6G is intended to transform global communication systems by merging terrestrial, aerial, and satellite networks, resulting in a ubiquitous, ultra-reliable, and low- latency communications infrastructure. The strict standards of 6G, however, may not be individually met by the homogeneous wireless networks that are now in place, such as satellite and cellular systems, especially in isolated areas like mountains and seas. The deployment of diverse wireless networks that take advantage of the interconnectivity of satellites, aerial base stations (BSs), and terrestrial BSs across interconnected space, ground, and aerial layers is one potential remedy. © 2024 IEEE.

关键词： Satellite communication systems

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Pneumonia Detection Using Anterior Chest X-Ray Images

Pneumonia Detection Using Anterior Chest X-Ray Images

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2024 IEEE International Conference on Emerging Technologies in computer science for Interdisciplinary Applications, ICETCS 2024

作者： Vallisha, M. Khot, Vishal Nagarathna, N. BMS College of Engineering Department of Computer Science and Engineering Bangalore India

ISBN: (纸本)9798350372502

Pneumonia is a common lung infection in developing and underdeveloped countries. Analysis of anterior chest x-ray is the most commonly used method to diagnose lung infections. Existing methods provide reasonable accuracies at the price of very high model sizes. Such a high memory requirement is contrary to the primary use case of such models, which is for a preliminary check from a place with access to less resources. We propose a lightweight neural network model to detect pneumonia in anterior chest x-ray images. The proposed model is trained to detect pneumonia in chest x-ray images utilizing contrast enhancement and progressive resizing. © 2024 IEEE.

关键词： computer vision

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Optimization of Logistic Regression Model by Feature engineering using Fuzzy Logic 18

Optimization of Logistic Regression Model by Feature Enginee...

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18th INDIAcom;11th International Conference on Computing for Sustainable Global Development, INDIACom 2024

作者： Rohit Kumar, Vivek Abes Engineering College Department of Computer Science and Engineering Ghaziabad India

ISBN: (纸本)9789380544519

In modern era, the Machine learning especially Supervised Machine Learning is iridescent field where many researchers are shaping their research work. Innovations and new ideas in field are growing fast. Still in various fields like medical, financial and other, we need to enhance the predictions of the Logistic Regression classification models. In this research paper, we focused on the optimization of the supervised Logistic Regression model which can predict more accurately when implemented on clinical dataset. Our purpose is to introduce and implement the fuzzy logic for Features engineering technique to optimize the logistic regression model before training of the Logistic regression, which can predict more accurately in the medical data sets. In this paper, we use Coronary Heart Disease (CHD) for implementing the features engineering using fuzzy logic. Final result showed that Optimized Logistic Regression Model prediction of Ten Years Heart risk is improved with accuracy of. 863 when classical Logistic Regression classification model has been compared with it. © 2024 Bharati Vidyapeeth, New Delhi.

关键词： Coronary heart disease Feature engineering Fuzzy logic Logistic regression Machine learning

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Customer Segmentation and Retention Strategies for Bank Using Machine Learning

Customer Segmentation and Retention Strategies for Bank Usin...

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2024 International Conference on Recent Innovation in Smart and Sustainable Technology, ICRISST 2024

作者： Beedhi Reddy, Hemanth Kumar Vijay Anand, M. Saveetha Engineering College Department of Computer Science and Engineering Chennai India

ISBN: (纸本)9798350309140

Customer churn is a pressing problem faced by banks, affecting their revenues and customer satisfaction. To solve this problem, this study explores the use of machine learning, specifically Naive Bayes, Decision Trees, and AdaBoost classifiers, to predict and reduce customer churn. By leveraging these complex algorithms, banks can gain insight into customer behaviour and take proactive steps to retain valuable products as customers. The process starts with pre- processed data, model design and coding. This optimization can solve many problems such as excessive priority, missing data, categorical features, etc. Additionally, Data Analytics (EDA) and visualizations to gain a deeper understanding of customer segmentation;This allows to uncover important trends and good standards. When evaluating performance in the model, Focused on simple metrics such as recall and ROC- AUC scores. These metrics provide insight into the model's ability to accurately identify past customers while minimizing false positives. To improve the performance of model, hyperparameter tuning was performed to ensure that we achieved the highest accuracy. The Model adopt ROC-AUC curve to see the balance between true positive and negative value. This analysis provides a better understanding of the performance model, allowing to make informed decisions and strategies to manage the customer's quality. Actual and estimated loss status is displayed as an estimate of Customer's final model. This valuable information provides banks with the strategies necessary to identify potential credit losers and take the necessary steps to maintain their trust. © 2024 IEEE.

关键词： Sales

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