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Designing Quantum-Resilient Blockchain Frameworks: Enhancing Transactional Security with Quantum Algorithms in Decentralized Ledgers

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international Journal of advanced computer science and Applications 2025年第4期16卷 618-628页

作者： Kale, Meenal R. Baker El-Ebiary, Yousef A. Sathiya, L. Burugari, Vijay Kumar Yulduz, Erkiniy Muniyandy, Elangovan Alanazi, Rakan Department of Humanities Yeshwantrao Chavan College of Engineering Hingna Nagpur India Faculty of Informatics and Computing UniSZA University Malaysia Department of CSE Panimalar Engineering College Chennai India Dept of Computer Science and Engineering Koneru Lakshmaiah Education Foundation Vaddeswaram Andhra Pradesh Guntur India Automatic Control and Computer Engineering Department Turin Polytechnic University in Tashkent Tashkent Uzbekistan Department of Biosciences-Saveetha School of Engineering Saveetha Institute of Medical and Technical Sciences Chennai India Applied Science Research Center Applied Science Private University Amman Jordan Department of Information Technology Faculty of Computing and Information Technology Northern Border University Rafha Saudi Arabia

Quantum computing is progressing at a fast rate and there is a real threat that classical cryptographic methods can be compromised and therefore impact the security of blockchain networks. All of the ways used to secure blockchain like Rivest–Shamir–Adleman (RSA), Elliptic Curve Cryptography (ECC) and Secure Hash Algorithm 256-bit (SHA256) are the characteristic of the traditional cryptographic techniques vulnerable to attack by quantum algorithms: Shor’s and Grover’s algorithms: can efficiently break asymmetric encryption and speed up brute force attacks. Because of this vulnerability, there exists a need to develop an advance quantum resilient blockchain framework to protect the decentralized ledgers from the future threats of the quantum. This research proposes Post-Quantum Cryptography (PQC), Quantum Key Distribution (QKD) and Quantum Random Number Generation (QRNG) as a formidable architectural integration, to fortify security of blockchain. Classical encryption is replaced with PQC, QKD with secure key exchange by detecting eavesdropping, and QRNG with improving cryptographic randomness to remove the predictable key vulnerability. Only with a small loss of transaction efficiency, we increase transaction encryption accuracy, key exchange security, and resistance to quantum attacks. In this quantum enhanced blockchain design, the idea is to preserve the decentralization, transparency and security and at the same time overcome the future quantum threat. By going through rigorous analysis and comparative evaluation, we demonstrate that the approach saves blockchain networks from the emerging quantum risks to make sure that the decentralized finance, smart contracts and cross chain transactions. © (2025), (science and information Organization). All rights reserved.

关键词： Quantum cryptography

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Modularity-Driven Influence: An Enhanced LPA Framework for Community Detection and Maximization in Social Networks

Modularity-Driven Influence: An Enhanced LPA Framework for C...

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2025 international conference on computer, Electrical and Communication engineering, ICCECE 2025

作者： Manoj Jayanth, N. Nithin, M. Kushwanth, M.V. Reddy, K. Akash Shukla, Ankita Nagarjuna College of Engineering and Technology Department of Information Science and Engineering Karnataka Bengaluru India

ISBN: (纸本)9798331513894

It is quite an uphill task to identify social network communities as well as to diffuse impact because of their complex architecture as well as evolving nature of their relationships. In this paper, we present an advanced version of the Modularity-Driven Label Propagation Algorithm, Enhanced Label Propagation Algorithm (ELPA) which has provided solutions to these issues through the adoption of modularity optimization and the local influence effectiveness measure. The modularity component ensures accurate and coherent community discovery, while the Local Influence Effectiveness (LIE) metric optimizes effective node selection and network impact propagation. The productivity and the impact distribution of the method have surpassed the results of the Louvain method which is often used on large databases of networks. The findings suggest that this new LPA is of a linearly increasing runtime with better impact diffusion making it appropriate for the use in viral marketing, public health activities and the dissemination of specific information. By integrating computational scale with analytical precision, the methodology advanced in this study offers a robust and efficient strategy for the current evolution of social networks research. © 2025 IEEE.

关键词： Expectation maximization algorithm

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Experimental results on FMCW radar based Human Recognition using only Doppler information 21

Experimental results on FMCW radar based Human Recognition u...

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21st international conference on Electrical engineering/Electronics, computer, Telecommunications and information Technology (ECTI-CON)

作者： Petchtone, Patipon Worasawate, Denchai Pongthavomkamol, Tiwat Fukawa, Kazuhiko Chang, Yuyuan Kasetsart Univ Fac Engn Dept Elect Engn Bangkok Thailand Natl Sci & Technol Dev Agcy Natl Elect & Comp Technol Ctr Pathum Thani Thailand Tokyo Inst Technol Sch Engn Tokyo Japan

ISBN: (纸本)9798350381566;9798350381559

The demand of indoor human identification systems that prioritize privacy has led to an increased interest in wireless sensing devices such as radar. Several studies have identified distinctive characteristics of human movement that cause Doppler signatures, which can be used for subject identification. Following them, this paper proposes an alternative machine learning approach for human identification, which uses only Doppler information from each subject by using FMCW radar. Experimental results in the two-subject scenarios show that the proposed method can achieve an accuracy of 96.2% (+/- 1.1%) when data for both training and verification are obtained from the same scenarios, while an accuracy of 67.0% (+/- 2.8%) can be achieved when data for the verification are obtained from different scenarios

关键词： FMCW radar Human Identification Doppler mmWave radar

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Simple Graph Sampling-Based Meta-Learning for Molecular Property Prediction 5

Simple Graph Sampling-Based Meta-Learning for Molecular Prop...

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5th international conference on computers, information Processing and advanced Education, CIPAE 2024

作者： Chushi, Wang Shiyu, Jia Xinyue, Ren Department of Computer Science and Engineering Southwest University of Science and Technology SWUST Mianyang China Department of Nuclear Engineering Southwest University of Science and Technology SWUST Mianyang China Department of Electrical Engineering Southwest Petroleum University SWPU Nanchong China

ISBN: (纸本)9798331527662

We focuses on the challenges and advances in molecular property prediction within the field of drug discovery, particularly when addressing small sample sizes. In seeking to enhance predictive accuracy while reducing costs and time expenditure, novel computational approaches are explored. Notably, the integration of meta-learning and contrastive learning has demonstrated potential, as evidenced in methods. Despite these advancements, persistent issues such as slow model training and sensitivity to data noise undermine practical applicability. Our research introduces a new optimization strategy that incorporates random noise during subgraph sampling in the GS-Meta model to tackle these challenges. The approach significantly increases the robustness and accuracy of molecular property predictions. Our findings, corroborated by robust performance metrics, indicate the promising potential of random noise optimization in molecular property prediction models. Future research should continue to explore these techniques’ generalizability across larger datasets and the impact of different noise injection strategies. © 2024 IEEE.

关键词： Contrastive Learning

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advanced Simulation and Design Methodology of Josephson Traveling-Wave Parametric Amplifiers (JTWPA) for Quantum Electronics Applications 4

Advanced Simulation and Design Methodology of Josephson Trav...

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4th international conference on Innovative research in Applied science, engineering and Technology, IRASET 2024

作者： Oukaira, Aziz Savaria, Yvon Boukadoum, Mounir Lakhssassi, Ahmed Department Of Engineering And Computer Science GatineauQCJ8X 3X7 Canada Polytechnique Montreal Department Of Electrical Engineering MontrealQCH3T 1J4 Canada Department Of Computer Science MontrealQCH3C 3P8 Canada GatineauQCJ8X 3X7 Canada

ISBN: (纸本)9798350309508

This paper examines the use of a quantum electronics Josephson Traveling-Wave Parametric Amplifier (JTWPA). The JTWPA presents distinctive features for amplifying quantum signals through the nonlinear Josephson junction, influenced by quantum effects at microwave energy scales. The study focuses on characterizing this quantum effects-based parametric amplification, offering perspectives in communication and information processing technologies. The results, obtained with the advanced Design System (ADS) pathWave tool suggest promising applications of JTWPA, paving the way for significant advances in quantum electronics. Notably, the findings indicate that at a fixed frequency of 4 GHz and a constant pump current of 1.85 μA, the transmission efficiency of JTWPA decreases by 32% when exporting the design as layouts using the High-Frequency Structural Simulator (HFSS). Consequently, optimization with ADS emerges as a crucial step to assess transmission and information processing before the physical implementation of the JTWPA design. © 2024 IEEE.

关键词： Parametric amplifiers

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Abstract Thinking of Beginning Electrical engineering and computer science Students 26th

Abstract Thinking of Beginning Electrical Engineering and Co...

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26th international conference on Interactive Collaborative Learning (ICL) - Towards a Hybrid, Flexible and Socially Engaged Higher Education / 52nd IGIP international conference on engineering Pedagogy

作者： Gero, Aharon Hadish, Mohammed Ali Kvatinsky, Shahar Technion Israel Inst Technol Haifa Israel

ISBN: (纸本)9783031530210;9783031530227

The Abstract thinking is the capability to deal with relevant information for a given phase while temporarily disregarding the irrelevant details for the current step. Abstract thinking is required in a wide variety of disciplines. It is of special importance in engineering, where examining many topics at different detail levels is needed. However, the literature implies that the abstract thinking of beginning students is insufficient. In light of the above, the research aimed to assess the abstract thinking of beginning electrical engineering and computer science students. The study used closed and open-ended instruments, and involved 64 undergraduate students at the Technion - Israel Institute of Technology. According to the findings, the average abstract thinking of the participants is moderate, with no significant difference between the two groups of students.

关键词： Abstract Thinking Electrical engineering Students computer science Students

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Exploring Future Education: The Innovative Integration and Practice of Multimodal Learning and ChatGPT 5

Exploring Future Education: The Innovative Integration and P...

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5th international conference on computer science, engineering, and Education, CSEE 2024

作者： He, Jun Li, Lixia Yao, Wenhao Gao, Hongying Shaanxi Normal University Faculty of Education Xi'an China Ningxia Police Vocational College Department of Information and Security Engineering Yinchuan China Northwest Normal University School of Educational Technology Lanzhou China Ningxia Medical University School of Medical Information and Engineering Yinchuan China Shaanxi Normal University School of International Studies Xi'an China

ISBN: (纸本)9798350376852

This research comprehensively explores the integrated application of multimodal learning and ChatGPT in the field of education. By reinterpreting the concept of multimodal learning, this paper emphasizes the central role of ChatGPT in expanding the definitions and boundaries of multimodal learning. It elaborates on the integration of ChatGPT with advanced technologies such as virtual reality and augmented reality, and how such integration fosters innovation in teaching methods and strategies. It also discusses the design and implementation of multimodal teaching strategies based on ChatGPT and the optimization of evaluation and feedback mechanisms. Lastly, this research forecasts the future development trends and challenges of multimodal learning and ChatGPT, providing pertinent recommendations. The findings underscore the significant value of combining multimodal learning with ChatGPT in promoting educational innovation and optimization. © 2024 IEEE.

关键词： Integration

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Vertical Aeroponics as a Better Alternative for Sustainable Environment Control, a Simulation Approach 4th

Vertical Aeroponics as a Better Alternative for Sustainable ...

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4th international conference on advanced research in Technologies information Innovation and Sustainability-ARTIIS-Annual

作者： Tomas Munoz, Jose Villaroel, Benjamin Taramasco, Carla Gatica, Gustavo Univ Andres Bello Santiago Chile

ISBN: (纸本)9783031832062;9783031832079

Climate change and soil erosion have impacted our potential for growing our own food. This, combined with the explosive urbanization of the capitals have pushed people to find new and innovative ways to grow their own food to give back to the planet and reduce their carbon footprint. One such way of achieving this is by growing a vertical aeroponic garden in their homes. This research proposes a methodology backed by multiple simulations on how to automate the process of growing crops through the help of multiple sensors and machine learning models which provide feedback and real time data to the user. This simulation compares a raised bed to a vertical garden, concluding a reduce of 76% of water usage, 90% land reduction and 95% reduction of carbon emissions with a yield of 10 lb of food.

关键词： Machine Learning Artificial Intelligence computer Medicine

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Leveraging Large Language Models in a Retriever-Reader Framework for Solving STEM Multiple-Choice Questions 4

Leveraging Large Language Models in a Retriever-Reader Frame...

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4th international conference on Electronic information engineering and computer science, EIECS 2024

作者： Li, Siyue Northeastern University Santa Clara United States

ISBN: (纸本)9798331531409

This research presents a novel Retriever-Reader framework to efficiently solve multiple-choice questions (MCQs) in STEM (science, Technology, engineering, and Mathematics) fields. Unlike previous approaches that primarily rely on either retrieval-based methods or reader-based models, our frame-work integrates both, significantly enhancing problem-solving performance. The Retriever Network selectively extracts relevant context from a customized STEM corpus, while the Reader Network, leveraging a fine-tuned DeBERTa-based language model, interprets this context to accurately solve MCQs. Through advanced model architecture design, data preprocessing, and comprehensive evaluation, our proposed framework outperforms state-of-the-art baseline models in both accuracy and F1 score. This work provides a new perspective on automated problem-solving in STEM domains by integrating multiple modeling techniques. © 2024 IEEE.

关键词： STEM (science, technology, engineering and mathematics)

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Deep learning-based classification,detection,and segmentation of tomato leaf diseases:A state-of-the-art review

Artificial Intelligence in Agriculture

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Artificial Intelligence in Agriculture 2025年第2期15卷 192-220页

作者： Aritra Das Fahad Pathan Jamin Rahman Jim Md Mohsin Kabir M.F.Mridha Department of Computer Science and Engineering American International University-BangladeshDhaka 1229Bangladesh Institute of Information and Communication Technology Shahjalal University of Science and TechnologySylhet 3114Bangladesh Advanced Machine Intelligence Research Lab Dhaka 1207Bangladesh Bangladesh University of Business and Technology DhakaBangladesh

The early identification and treatment of tomato leaf diseases are crucial for optimizing plant productivity,efficiency and *** by the farmers poses the risk of inadequate treatments,harming both tomato plants and *** of disease diagnosis is essential,necessitating a swift and accurate response to misdiagnosis for early *** regions are ideal for tomato plants,but there are inherent concerns,such as weather-related *** diseases largely cause financial losses in crop *** slow detection periods of conventional approaches are insufficient for the timely detection of tomato *** learning has emerged as a promising avenue for early disease *** study comprehensively analyzed techniques for classifying and detecting tomato leaf diseases and evaluating their strengths and *** study delves into various diagnostic procedures,including image pre-processing,localization and *** conclusion,applying deep learning algorithms holds great promise for enhancing the accuracy and efficiency of tomato leaf disease diagnosis by offering faster and more effective results.

关键词： Deep learning Tomato leaf disease Classification Detection Segmentation Imaging

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