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IET Blockchain 2025年第1期5卷

作者： Arafat, Yeasir Siam, Abu Sayem Md. Chowdhury, Md Muzadded Hasan, Md Mehedi Jobayer, Sayed Hossain Shatabda, Swakkhar Islam, Salekul Mukta, Saddam Department of Computer Science and Engineering United International University Dhaka Bangladesh Department of Computer Science and Engineering BRAC University Dhaka Bangladesh Electrical and Computer Engineering Department North South University Dhaka Bangladesh Department of Software Engineering LUT University Lappeenranta Finland

This research presents a blockchain-based framework for secure and efficient medical image sharing, prioritizing data integrity and privacy. The framework involves two key phases: image compression with feature extraction and image encryption with storage on the InterPlanetary File System (IPFS). Medical images are compressed using the JPEG algorithm to reduce file size while maintaining diagnostic value. A deep neural network-based subject sensitive hashing (SSH) algorithm ensures feature map integrity by extracting consistent features from both original and compressed images. Encrypted images, along with SSH-generated hashes, are securely stored in the IPFS server. The encryption key and hash sequence are used for secure image retrieval, with smart contracts validating access requests based on the hash sequence. This multi-stage feature extraction approach demonstrates robust image integrity, security, and privacy, as verified by experimental results. Achieving an average correctness rate of 98% across multiple datasets, the framework significantly enhances healthcare data management by addressing the challenges of secure, scalable, and private medical image sharing. This research contributes to the development of more efficient, reliable, and privacy-conscious solutions for medical image handling in healthcare systems. © 2025 The Author(s). IET Blockchain published by John Wiley & Sons Ltd on behalf of The Institution of engineering and Technology.

关键词： Data integrity

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Clinical Decision Support System for Diabetes Classification with an Optimized CNN using PSO

Clinical Decision Support System for Diabetes Classification...

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2023 IEEE International Conference on Artificial Intelligence, Blockchain, and Internet of Things, AIBThings 2023

作者： Khan, Faiq Ahmad Jamil, Akhtar Hameed, Alaa Ali Moetesum, Momina National University of Modern Languages Department of Electrical Engineering Islamabad Pakistan National University of Compter and Emerging Sciences Department of Computer Science Islamabad Pakistan Istinye University Department of Computer Engineering Istanbul Turkey Islamabad Pakistan

ISBN: (纸本)9798350322347

Diabetes, a pervasive chronic metabolic disorder, affects a substantial portion of the global population. The timely and precise diagnosis of diabetes is pivotal for effective management and improved patient outcomes. In this study, we introduce an innovative approach aimed at augmenting the classification performance of Convolutional Neural Networks (CNNs) in diabetes diagnosis. Utilizing the Particle Swarm Optimization (PSO) algorithm, we fine-tune the CNN model to enhance the accuracy and efficiency of diabetes classification. Our comprehensive experiments, conducted on the Pima Indians Diabetes dataset, substantiate the effectiveness of our optimized CNN. These findings underscore the potential of integrating CNN and PSO optimization methodologies to significantly boost the accuracy of diabetes diagnosis, thereby facilitating more accurate assessments and tailored treatment strategies for patients. We evaluated the proposed model using standard metrics such as precision, recall, F1-score, and overall accuracy, with results demonstrating that the PSO-based optimized CNN model outperforms the custom CNN, achieving the highest precision, recall, F1-score, and overall accuracy. © 2023 IEEE.

关键词： Decision support systems

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Variable-Length XP-HARQ for URLLC 16

Variable-Length XP-HARQ for URLLC

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16th International Conference on Wireless Communications and Signal Processing, WCSP 2024

作者： Feng, Jiahui Shi, Zheng Fu, Yaru Wang, Hong Yang, Guanghua Ma, Shaodan The School of Intelligent Systems Science and Engineering Jinan University China The School of Science and Technology Hong Kong Metropolitan University Hong Kong Nanjing University of Posts and Telecommunications China University of Macau The Department of Electrical and Computer Engineering China

ISBN: (纸本)9798350390643

A variable-length cross-packet hybrid automatic repeat request (VL-XP-HARQ) is proposed to accommodate ultrareliable low-latency communications (URLLC). The spectral efficiency (SE) is firstly derived in terms of the outage probabilities, with which the SE is proved to be upper bounded by the ergodic capacity (EC). Moreover, to facilitate the maximization of the SE, the asymptotic outage probability is obtained at high signal-to-noise ratio (SNR), with which the SE is maximized by properly choosing the number of new information bits while guaranteeing outage requirement. By applying Dinkelbach's transform, the fractional objective function is transformed into a subtraction form, which can be decomposed into multiple sub-problems through alternating optimization. By noticing that the asymptotic outage probability is a convex function, each sub-problem can be easily relaxed to a convex problem by adopting successive convex approximation (SCA). Finally, numerical results are presented for verification. © 2024 IEEE.

关键词： Spectrum efficiency

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Matrix Completion over Finite Fields: Bounds and Belief Propagation Algorithms

Matrix Completion over Finite Fields: Bounds and Belief Prop...

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2023 IEEE International Symposium on Information Theory, ISIT 2023

作者： Soleymani, Mahdi Liu, Qiang Mahdavifar, Hessam Balzano, Laura University of California San Diego Halicioglu Data Science Institute United States University of Michigan Ann Arbor The Department of Electrical Engineering and Computer Science United States

ISBN: (纸本)9781665475549

We consider the low rank matrix completion problem over finite fields. This problem has been extensively studied in the domain of real/complex numbers, however, to the best of authors' knowledge, there exists merely one efficient algorithm to tackle the problem in the binary field, due to Saunderson et al. [1]. In this paper, we improve upon the theoretical guarantees for the algorithm provided in [1]. Furthermore, we formulate a new graphical model for the matrix completion problem over the finite field of size q, Fq, and present a message passing (MP) based approach to solve this problem. The proposed algorithm is the first one for the considered matrix completion problem over finite fields of arbitrary size. Our proposed method has a significantly lower computational complexity, reducing it from O(n2r+3) in [1] down to O(n2) (where, the underlying matrix has dimension n × n and r denotes its rank), while also improving the performance. © 2023 IEEE.

关键词： Message passing

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The Current State of Research on Malware Written in the Rust Programming Language 11

The Current State of Research on Malware Written in the Rust...

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11th International Conference on Information Technology, ICIT 2023

作者： Praveen, Meghna Almobaideen, Wesam Rochester Institute of Technology Department of Electrical Engineering and Computing Dubai United Arab Emirates The University of Jordan Department of Computer Science Amman Jordan

ISBN: (纸本)9798350320060

Malware is conventionally written in the C/C++ programming languages. However, a recent trend has been observed where other languages are being used to write malware. One such language is the Rust programming language. In this paper, we conduct a systematic literature review to identify the current state of research on malware written in the Rust programming language. We outline the research gaps and challenges faced by researchers when studying malware written in the Rust programming language. The study found that while the industry is doing well in terms of researching and developing tools and techniques, much of it is not openly available. Moreover, there is a lack of academic research in this field, highlighting the need for academia to conduct more research to keep up with the evolving threat of malware. The study concludes that open research initiatives should be encouraged to ensure that the latest developments in malware research are accessible to all. The material in this paper is not endorsed, reviewed or approved by the Rust Foundation. © 2023 IEEE.

关键词： C++ (programming language)

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Multiplicative resonant enhancement of chemical detection

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Physical Review Applied 2024年第5期22卷 054006页

作者： Wenchao Ma Raphaël Pestourie Zin Lin Alan Aguirre-Soto Hadley D. Sikes Steven G. Johnson Department of Chemistry School of Computational Science and Engineering Bradley Department of Electrical and Computer Engineering School of Engineering and Sciences Department of Chemical Engineering Department of Mathematics

Optical resonances can increase the sensitivity of measurements to material perturbations and also accelerate photochemical reactions. Here, we show that these two effects can be combined multiplicatively, to enhance the detection via weak or low-concentration photochemical reactions far beyond what could previously be attained. For an optical resonance with quality factor Q, the sensitivity of our detection scheme is enhanced by ∼Q2 (where ∼ denotes approximate proportionality), as demonstrated by both theoretical arguments and numerical simulations of a simple optical-grating resonance coupled with reaction-diffusion equations. Such an approach opens a door to further improvements by careful design of the resonance: even a three-parameter optimization of the grating resonance yields an additional ≈7 times improvement.

关键词： Analytical chemistry Fano resonance Metrology Nanophotonics Optimization problems Photochemistry Devices Reaction diffusion systems

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Literature Survey on Face Recognition of Occluded Faces 7

Literature Survey on Face Recognition of Occluded Faces

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7th International Conference on Circuit Power and Computing Technologies, ICCPCT 2024

作者： Anil, J. Suresh, L. Padma Muthukumar, P. Krishna Veni, S.H. Asha, P. Prasad, Rajesh Nooral Islam Centre for Higher Education Department of Electrical and Electronics Engineering Tamil Nadu Thuckalay India Baselios Mathews II College of Engineering Sasthamcotta Department of Electrical and Electronics Engineering Kerala Kollam690 520 India Saveetha Institute of Medical and Technical Sciences Tiruvallur Saveetha School of Engineering Department of Electrical and Electronics Engineering Tamilnadu Chennai602105 India Baselios Mathews II College of Engineering Sasthamcotta Department of Computer Science and Engineering Kerala Kollam690 520 India Sathyabama Institute of Science and Technology Department of Computer Science and Engineering Tamil Nadu Chennai India Stella Mary's College of Engineering Department of Electrical and Electronics Engineering Tamil Nadu India

ISBN: (纸本)9798350372816

In this paper, a study of the recent advancements in occluded face recognition is made. Recently, this has become very relevant due to the outburst of corona virus. Because of the seriousness of the spread of the disease, every person wore a mask, and it became challenging for automated systems to identify the person. So, it became the need of the hour to find new techniques for occluded face detection. In the years 2021 to 2022, many papers have been published in this regard. Researchers all over the world have contributed significantly towards occluded face recognition. Also, the advancement of deep learning has helped researchers a lot in implementing innovative techniques to deal with the challenges in face recognition, especially occluded faces, which is considered one of the most difficult challenges to overcome. This paper intends to push the limits further and encourage researchers to find more innovative techniques for occlusion-independent face recognition. In this paper, the recent publications in this field are studied. This paper gives an insight into different algorithms which use Convolutional Neural Networks, Deep Learning, Attention mechanism, Dictionary representation, Simultaneous segmentation, Joint segmentation and identification, etc., for occluded face detection and recognition. Incorporating these strategies in face recognition has substantially improved the recognition rate, specifically for occluded face recognition. Additionally, the databases for training occluded face recognition algorithms lack adequate data. This paper also gives an insight into the recent databases available for training occluded face recognition algorithms. Also, different methods for obtaining synthesised occluded faces are discussed. © 2024 IEEE.

关键词： Convolutional neural networks

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Online Demand Peak Shaving with Machine-Learned Advice in Cyber-Physical Energy Systems

Online Demand Peak Shaving with Machine-Learned Advice in Cy...

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2023 IEEE International Conference on Dependable, Autonomic and Secure Computing, 2023 International Conference on Pervasive Intelligence and Computing, 2023 International Conference on Cloud and Big Data Computing, 2023 International Conference on Cyber science and Technology Congress, DASC/PiCom/CBDCom/CyberSciTech 2023

作者： Fengl, Minxi Li, Wei Qin, Boyu Zomaya, Albert Y. Centre for Distributed and High Performance Computing School of Computer Science The University of Sydney Australia Xi'an Jiaotong University State Key Laboratory of Electrical Insulation and Power Equipment Department of Electrical Engineering China

ISBN: (纸本)9798350304602

With the deep integration of cyber tools, control algorithms are increasingly employed in cyber-physical energy systems to enhance management, cost efficiency, and robustness. Effective demand load management is crucial in cyber-physical energy systems as it directly impacts operational costs. Failure to adequately manage spiky or seasonal demand loads can lead to significant expenses on monthly utility bills. In this study, we propose AMPAMOD, a randomized online algorithm with machine-learned advice, to optimize battery operations and mitigate highly dynamic peak loads. AMPAMOD utilizes limited advice from machine learning algorithms to guide our online algorithm and ensure cost-effective peak load management. The theoretical analysis shows that our solution has minimal advice complexity, a linear computational cost, and an improved competitive ratio. Finally, we conduct extensive trace-driven experiments on real-world datasets. AMPAMOD achieves a peak shaving success rate of over 90%, outperforming baselines by at least 50%. These experimental results confirm theoretical findings and demonstrate the potential of AMPAMOD. © 2023 IEEE.

关键词： Cyber Physical System

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Directional Beam Based LED Deployment for a Short Range Indoor LED Light Communication System

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Journal of Optical Communications 2022年第3期43卷 411-420页

作者： Sharma, Ram Charan Kumari, A. Aggarwal, Mona Ahuja, Swaran Department of Electrical Electronics and Communication Engineering NorthCap University Haryana Gurgaon India Department of Electrical Electronics and Communication Engineering School of Engineering NorthCap University Gurgaon India Department of Computer Science and Engineering School of Engineering NorthCap University Gurgaon India

There is now an increasing awareness about the possibility of health hazards due to excessive electromagnetic radiations around us within the indoor environment. Hence, the alternative communication technologies such as indoor mobile communication system based on LED lighting are gaining more attention in the present scenario. The dual use of LEDs i. e. for illumination as well as for setting up of an indoor communication network infrastructure simultaneously makes it an attractive preposition. The LED lighting based communication system is qualified to be part of green technology networks. This paper investigates the optimal LED placement strategy for such a system to optimize the overall communication system parameters including the transmit power optimization. It is observed that the overall optimization of LEDs improve the signal to noise ratio and also a significant reduction in root mean square delay at lower semi-angle values besides improving the mobile coverage area. © 2019 Walter de Gruyter GmbH, Berlin/Boston.

关键词： Light emitting diodes

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Product Verification using Blockchain Technology: A Systematic Review

Product Verification using Blockchain Technology: A Systemat...

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2023 International Conference on science, engineering and Business for Sustainable Development Goals, SEB-SDG 2023

作者： Igbekele, Emmanuel O. Aideloje, Joshua Adebiyi, Abayomi A. Adebiyi, Ayodele Landmark University Department of Computer Science Omu-Aran Nigeria Durban University of Technology Department of Electrical Power Engineering Durban South Africa

ISBN: (纸本)9798350324785

Diverse products have flooded so many markets today through unscrupulous vendors all in a bid to make outrageous profits. Hence, the need for products to be verified by extant bodies. There are several means for products to be verified, however, some of those means have also been circumvented. The use of blockchain technology to prevent product replication in supply chain management is a rapidly growing area of research and development. With its features of immutability and decentralization, blockchain technology has the potential to provide secure and tamper-proof tracking and verification of products. This systematic review aims to examine the existing research on the use of blockchain technology in preventing product replication and to identify the effectiveness and challenges of its implementation in industry. The review show that while blockchain technology holds significant potential in preventing product replication, its effectiveness compared to traditional methods and implementation challenges must be addressed. © 2023 IEEE.

关键词： Blockchain

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