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Decentralized Ledger technologies: Exploring the Landscape and Diverse applications of Blockchain 4

Decentralized Ledger Technologies: Exploring the Landscape a...

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4th international conference on computer, Communication, Control and Information Technology, C3IT 2024

作者： Sharma, Nandini Khenwar, Medha Agrawal, Shobit Sonika G.L Bajaj Group of Institutions Dept. of Computer Science & Engineering Mathura India

ISBN: (纸本)9798350389128

The purpose of this paper is to explore and illuminate the diverse applications of blockchain technology across various sectors, including banking, crowdsourcing, finance and insurance, healthcare, copyright management, e-government, the public sector, distribution systems, logistics and supply chain management, and education. By examining its uses, advantages, and disadvantages, this paper aims to provide a comprehensive overview of how blockchain is revolutionizing these fields. Known for its unparalleled integrity and security, blockchain offers a reliable and secure framework that operates without the need for third parties. This paper not only aims to enhance the understanding of blockchain's current applications but also to identify emerging trends and potential new uses, providing valuable insights for future researchers. © 2024 IEEE.

关键词： Distributed ledger

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Machine Learning-Driven Rate Adaptation Strategies for Cross-Layer Routing in MANETs 3

Machine Learning-Driven Rate Adaptation Strategies for Cross...

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3rd international conference on Intelligent Data Communication technologies and Internet of Things, IDCIoT 2025

作者： Sathish, K. Chitra, D. Rajesh Sharma, R. Sungheetha, Akey Rajavimalanaathan, L. Ellappan, V. Saveetha University TamilNadu Chennai India Department of ECE Mahendra Engineering College Tamil Nadu Namakkal India Department of CSE Alliance University Bangalore India

ISBN: (纸本)9798331527549

A Machine Learning-Driven Rate Adaptation Strategy for Cross-Layer Routing in Mobile Ad-Hoc Networks (MANET) represents the main contribution of the research which solves QoS challenges in real-time applications. The protocol uses machine learning algorithms to detect dynamic changes in network conditions which include link quality assessment and queue status monitoring and congestion monitoring. This network design unites data from physical along with MAC and network layer components to reach optimal resources utilization. Real-time traffic patterns together with node mobility data get processed by machine learning models which lead to adaptive congestion control and rate adaptation decisions. Through its approach the protocol identifies several node-disjoint paths which boost network resistance to link failures. computer simulation results prove that the protocol delivers superior packet delivery performance and lower end-to-end delay and enhanced adaptability under changing traffic conditions and mobile node environments. The new methodology surpasses conventional methods by offering strong backing for applications that require delayed tolerance and vast bandwidth needs while handling modern MANETs so well through a complete performance solution. © 2025 IEEE.

关键词： Mobile ad hoc networks

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Realm of Medical Image Processing Under the Light of Artificial Intelligence 1

Realm of Medical Image Processing Under the Light of Artific...

引用

1st international conference on Healthcare Innovations, Software and engineering technologies, HISET 2024

作者： Tamboli, Asif I. Shah, Samarth Saxena, Gaurav Wagh, S.J. Prashanth, Addagatla Diallo, Mamadou Yero Department of Radio-Diagnosis Karad India Chandigarh University Department of Computer Science Mohali India Government Engineering College Department of Computer Science Karad India Institute of Aeronautical Engineering Electronics and Communication Engineering Hyderabad India Sharda University Computer Science & Engineering Gr.Noida India

ISBN: (纸本)9798350360707

Over the previous century, a fundamental breakthrough in medical imaging processing as well as storage occurred, with the switch from traditional detectors in radiography to digital detectors. As a result, medical imaging digitalization constitutes a big achievement and promises considerable breakthroughs in cancer. Thus, goal of study is to analyze the advanced imaging process in medical field using artificial intelligence (AI). AI, on the other hand, has the potential to go beyond these applications by producing picture-based biomarkers that are able to accurately predicting survival or response to therapy, thereby extracting far more information from photographic images than used to be conceivable. Such biomarkers might be incorporated into existing prognostic as well as predictive models used in clinical treatment, functioning as integrative biomarkers. So, the study helps in understanding importance of medical imaging processes and further helps in diagnosing minor diseases and eliminates it without human intervention with help of AI. © 2024 IEEE.

关键词： Medical image processing

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Developing a Comprehensive Hybrid Model Utilizing Convolutional Neural Networks and Random Forest for the Advanced Classification of Tomato Rot Disease Severity Stages

Developing a Comprehensive Hybrid Model Utilizing Convolutio...

引用

2024 IEEE international conference on Emerging technologies in computer Science for Interdisciplinary applications, ICETCS 2024

作者： Satyarthi, Abhishek Upadhyay, Deepak Bharti, Dilip Kumar Manwal, Manika Kukreja, Vinay Sharma, Rishabh AI DS IIMT College of Engineering Greater Noida India Graphic Era Hill University Uttarakhand Dehradun248002 India Computer Science and Engineering-Data Science ABES Engineering College Ghaziabad India Graphic Era Deemed to Be University Uttrakhand Dehradun India Chitkara University Institute of Engineering and Technology Chitkara University Punjab India

ISBN: (纸本)9798350372502

This study proposed a relatively new hybrid model integrating Convolutional Neural Networks (CNN) and Random Forest (RF) for the classification of tomato fruit rot diseases into five different levels, according to graded severity levels. Breaking with the norm of the primitive and one-sided machine learning techniques in the strong categorization and the precise diagnosis of plant diseases, this research stands out for applying the deep learning potential of convolutional neural networks and the multifaceted strength of random forest for the extraction of features and the classification accordingly. The newly proposed mixed methodology, including data acquisition, preprocessing, training, and validation, indicates the hybrid model with excellent performance where the accuracy measurement was 93.5%. Besides, this portrays a significant change because it is already better compared to the current models, and it evidences its potential in the fight against weather variability and the improvement of disease management. The study results suggest that the integration of deep and ensemble learning methods in the agricultural sector is possible, wherefore their perspectives can become a base for future practical applications as a worthwhile goal. The work is substantial and represents a significant contribution to the field of agricultural informatics and plant pathology in that there is a robust tool for early disease detection and severity classification that will directly lead to quick and informative management decisions. © 2024 IEEE.

关键词： Convolutional neural networks

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'Vulnerabilities in Smart Contracts: A Detailed Survey of Detection and Mitigation Methodologies'

'Vulnerabilities in Smart Contracts: A Detailed Survey of De...

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2024 IEEE international conference on Emerging technologies in computer Science for Interdisciplinary applications, ICETCS 2024

作者： Kumar, Nayantara K Honnungar, Niranjan V Sharwari Prakash, M. Lohith, J.J. B.M.S. College of Engineering Dept. of Computer Science and Engineering Bangalore India

ISBN: (纸本)9798350372502

In the ever-changing world of blockchain technology, the emergence of smart contracts has completely transformed the way agreements are executed, offering the potential for automation and trust in decentralized systems. Despite their built-in security features, smart contracts still face persistent vulnerabilities, resulting in significant financial losses. While existing studies often approach smart contract security from specific angles, such as development cycles or vulnerability detection tools, this paper adopts a comprehensive, multidimensional perspective. It delves into the intricacies of smart contract security by examining vulnerability detection mechanisms and defense strategies. The exploration begins by conducting a detailed analysis of the current security challenges and issues surrounding smart contracts. It then delves into established frameworks for classifying vulnerabilities and common security flaws. The paper examines existing methods for detecting, and repairing contract vulnerabilities, evaluating their effectiveness. Additionally, it provides a comprehensive overview of the existing body of knowledge in smart contract security-related research. Through this systematic examination, the paper aims to serve as a valuable reference and provide a comprehensive understanding of the multifaceted landscape of smart contract security. © 2024 IEEE.

关键词： Smart contract

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Efficient Parallel Processing of Stereoscopic Video Streams for Low-Latency applications 15

Efficient Parallel Processing of Stereoscopic Video Streams ...

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15th international conference on Computing Communication and Networking technologies, ICCCNT 2024

作者： Manjunath, H.R. Gaikwad, V.S. Kuppuraj, T. Singh, Takveer Jana, D Little Femilin Kansal, Amit School of Engineering and Technology Physics Karnataka Bangalore India Vishwakarma Institute of Technology Computer Engineering Pune India Karpagam Academy of Higher Education Department of Computer Applications Coimbatore India Chitkara University Centre of Research Impact and Outcome Punjab Rajpura140417 India Prince Shri Venkateshwara Padmavathy Engineering College Department of Science and Humanities Chennai India Quantum University Research Centre Quantum University India

ISBN: (纸本)9798350370249

Streams for video conferencing and interactive streaming applications. By using exploiting the spatial and temporal redundancies of stereoscopic video sequences, the proposed technique leverages GPUs to technique and encodes the video streams in parallel, decreasing the full latency from video shooting to encoding for transmission. This technique utilizes parallel processing to lessen latency by means of processing more than one frame simultaneously, utilizing facts systems to make the most interface dependencies and calculating the audio-video synchronization in a single bypass. The technique also uses motion estimation techniques to reduce the range of layers of the video coding, and a temporal scalability scheme to lessen temporal artifacts. Moreover, the technique applies the excessive-performance encoding of the LHE codec to enhance the compression performance and latency for stereoscopic video streaming. Ultimately, the resulting latency of the proposed approach is validated to be superior to frame-with the aid of-frame encoding for actual-time stereo video streaming. © 2024 IEEE.

关键词： Actual Compression Enhance Proposed Streaming Superior

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Development of an Algorithm for Converting JSON Formats to XML by Forming its File Data Structure 9

Development of an Algorithm for Converting JSON Formats to X...

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9th international conference on computer Science and engineering, UBMK 2024

作者： Mukhitova, Aigul Yerimbetova, Aigerim Barakhnin, Vladimir Daiyrbayeva, Elmira Al-Farabi Kazakh National University Institute of Information and Computing Technologies The Science Committee of the Ministry of Science and Higher Education of the Republic of Kazakhstan Almaty Kazakhstan Institute of Information and Computing Technologies The Science Committee of the Ministry of Science and Higher Education of the Republic of Kazakhstan Satbayev University Almaty Kazakhstan Federal Research Center for Information and Computational Technologies Novosibirsk State University Novosibirsk Russia Institute of Information and Computational Technologies The Science Committee of the Ministry of Science and Higher Education of the Republic of Kazakhstan Satbayev University Almaty Kazakhstan

ISBN: (纸本)9798350365887

In web development, the basis for successful interaction between different applications and systems is reliable and fast information transfer. To interact with external APIs and web services, reliable means of transferring, storing and structuring information are used: XML (eXtensible Markup Language) and JSON (JavaScript Object Notation). The ability to support namespace in XML, unlike JSON, provides good compatibility and integration between different systems and applications, so many industry standards and protocols prefer to use it as the main format for data exchange. JSON to XML transformations will enable convenient processing and transfer of structured data between different systems and devices. In this study, a JSON to XSD and XML transformation model has been developed to correctly handle data transformation in both directions without losing the transformation of the JSON document structure. © 2024 IEEE.

关键词： Data transfer

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Automated Multi-Page Document Classification and Information Extraction for Insurance applications using Deep Learning Techniques 11

Automated Multi-Page Document Classification and Information...

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11th international conference on Reliability, Infocom technologies and Optimization, ICRITO 2024

作者： Singh, Richa Sharma, Vikrant Kashyap, Rekha Manwal, Manika Ghaziabad India Graphics Era Hill University Computer Science and Engineering Deharadun India Graphic Era Deemed to Be University Computer Science and Engineering Uttarakhand Deharadun India

ISBN: (纸本)9798350350357

Automated document classification and information extraction are important tasks in many industries, including healthcare, finance, and government. In healthcare, patient data is stored in unstructured formats, which makes data retrieval and analysis difficult. In the finance sector, financial documents such as data analysis, regulatory compliance, and fraud detection are also important tasks. In government, the classification and extraction of information from legal and policy documents can enhance decision-making and policymaking processes. Automated document classification and information extraction using computer vision and deep learning, can efficiently extract important information from these unstructured documents, such as medical histories, diagnoses, treatments, insurance applications and improve the process of data analysis, fraud detection, and decision-making process. By using this, businesses and organizations can reduce the time and cost associated with manual document processing, enabling them to focus on more critical tasks. This paper proposes a solution that utilizes OCR, NLP and CNNs to perform these tasks on insurance applications. The system is trained on a large dataset of documents and can classify and extract information from various types of documents, including invoices, receipts, and forms. Our experiments show that the proposed system achieves high accuracy of 90% in document classification and information extraction tasks, making it suitable for use in realworld applications. © 2024 IEEE.

关键词： Deep learning

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Methodology of improving the educational process on the basis of mobile applications in higher educational institutions (with reference to solid state physics)

Methodology of improving the educational process on the basi...

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international conference on Artificial Intelligence, Blockchain, Computing and Security, ICABCS 2023

作者： Lutfillayev, M.X. Narkulov, O.O. Samarkand State University named after Sharof Rashidov Uzbekistan

ISBN: (纸本)9781032669663

This article explores the advantages of mobile applications in improving and increasing the efficiency of the educational process in higher educational institutions. As well as the use of principles, models and modern achievements of mobile technologies in the education system. The analysis of scientific publications of foreign scientists and countries of the Commonwealth of Independent States is given. As an example, computer simulation models of physical processes in the subject "Physics of the Solid State" are given. © 2024, CRC Press/Balkema. All rights reserved.

关键词： Mobile computing

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Federated Learning Enabled Secure Air Transport and Tourism System 15

Federated Learning Enabled Secure Air Transport and Tourism ...

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15th international conference on Computing Communication and Networking technologies, ICCCNT 2024

作者： Sharma, Sachin Tomar, Muskan Tyagi, Ranu Graphic Era Deemed to be University Graphic Era Hill University Department of Computer Science and Engineering Dehradun India Graphic Era Deemed to be University Department of Computer Science and Engineering Dehradun India

ISBN: (纸本)9798350370249

This paper investigates the application of Federated Learning within the booming industry of travel, centering on tasks such as Discuss Transport, Aircraft Passenger Satisfaction Prediction particularly, in conjunction with suggestions, and request estimating. We discuss challenges and openings for utilizing Federated Learning in travel applications, including information differences, security issues, and communication overhead. Also, we survey existing inquire about and writing to illustrate the viability of Federated Learning in improving labor guidelines whereas tending to protection limitations. Through this investigate, we aim to pick up a more profound understanding of Federated Learning's capacity to convert the travel industry by utilizing different information to move forward decision-making and personalized benefit. © 2024 IEEE.

关键词： Airline Passenger Satisfaction Classification Algorithms Neural Network

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