Inefficient task scheduling schemes compromise network performance and increase latency for delay intolerant tasks. Cybertwin based 6G services support data logging of operational queries for appropriate resource allo...
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Non-malleable code is an encoding scheme that is useful in situations where traditional error correction or detection is impossible to *** ensures with high probability that decoded message is either completely unrela...
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Non-malleable code is an encoding scheme that is useful in situations where traditional error correction or detection is impossible to *** ensures with high probability that decoded message is either completely unrelated or the original one,when tampering has no ***,standard version of non-malleable codes provide security against one time tampering *** ciphers are successfully employed in the construction of non-malleable *** construction fails to provide security when an adversary tampers the codeword more than *** non-malleable codes further allow an attacker to tamper the message for polynomial number of *** this work,we propose continuous version of non-malleable codes from block ciphers in split-state *** construction provides security against polynomial number of tampering attacks and it preserves *** the tam-pering experiment triggers self-destruct,the security of continuously non-malleable code reduces to security of the underlying leakage resilient storage.
Differential Evolution (DE) is a potent stochastic evolutionary optimization algorithm garnering increasing research attention. Over the years, it has been found applicable in solving diverse real-world problems. DE e...
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Purpose:Assistive technology has been developed to assist the visually impaired individuals in their social *** designed to enhance communication skills,facilitate social engagement and improve the overall quality of ...
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Purpose:Assistive technology has been developed to assist the visually impaired individuals in their social *** designed to enhance communication skills,facilitate social engagement and improve the overall quality of life,conversational assistive technologies include speech recognition APIs,text-to-speech APIs and various communication tools that are *** real-time *** natural language processing(NLP)and machine learning algorithms,the technology analyzes spoken language and provides appropriate responses,offering an immersive experience through voice commands,audio feedback and vibration ***/methodology/approach:These technologies have demonstrated their ability to promote self-confidence and self-reliance in visually impaired individuals during social ***,they promise to improve social competence and foster better *** short,assistive technology in conversation stands as a promising tool that empowers the visually impaired individuals,elevating the quality of their social ***:The main benefit of assistive communication technology is that it will help visually impaired people overcome communication barriers in social *** technology helps them communicate effectively with acquaintances,family,co-workers and even strangers in public *** enabling smoother and more natural communication,it works to reduce feelings of isolation and increase overall quality of ***/value:Research findings include successful activity recognition,aligning with activities on which the VGG-16 model was trained,such as hugging,shaking hands,talking,walking,waving and *** originality of this study lies in its approach to address the challenges faced by the visually impaired individuals in their social interactions through modern *** adds to the body of knowledge in the area of assistive technologies,which contribute to the empowerment and social in
The missing readings in various sensors of air pollution monitoring stations is a common issue. Those missing sensor readings may greatly influence the performance of monitoring and analysis of air pollution data. To ...
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We studied the weekly number and the growth/decline rates of COVID-19 deaths of the period from October 31, 2022, to February 9, 2023, in Italy. We found that the COVID-19 winter wave reached its peak during the three...
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Community question answering (CQA) forums are Internet-based platforms where users ask questions about a topic and other expert users try to provide solutions. Many CQA forums such as Quora, Stackoverflow, Yahoo!Answe...
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The transition from traditional energy or electrical grids to smart energy or electrical grids has significantly transformed energy management. This evolution emphasizes decentralization, efficiency, and sustainabilit...
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The transition from traditional energy or electrical grids to smart energy or electrical grids has significantly transformed energy management. This evolution emphasizes decentralization, efficiency, and sustainability in energy systems. However, it also introduces numerous risks, including cyber-physical system vulnerabilities and challenges in energy trading. The application of blockchain and Machine Learning (ML) offers potential solutions to these issues. Blockchain enhances energy transactions by making them safer, more transparent, and tamper-proof, while ML optimizes grid performance by improving predictions, fault detection, and anomaly identification. This systematic review examines the application of blockchain and ML in peer-to-peer (P2P) energy trading within smart grids and analyzes how these technologies complement each other in mitigating risks and enhancing the efficiency of smart grids. Blockchain enhances security by providing privacy for transactions and maintaining immutable records, while ML predicts market trends, identifies fraudulent activities, and ensures efficient energy use. The paper identifies critical challenges in smart grids, such as unsecured communication channels and vulnerabilities to cyber threats, and discusses how blockchain and ML address these issues. Furthermore, the study explores emerging trends, such as lightweight blockchain systems and edge computing, to overcome implementation challenges. A new architecture is proposed, integrating blockchain with ML algorithms to create resilient, secure, and efficient energy trading markets. The paper underscores the need for global standardization, improved cybersecurity measures, and further research into how blockchain and ML can revolutionize smart grids. This study integrates current knowledge with a forward-looking perspective, providing valuable insights for researchers, policymakers, and stakeholders in the energy sector to collaboratively build a future of efficient and int
Medical imaging, a cornerstone of disease diagnosis and treatment planning, faces the hurdles of subjective interpretation and reliance on specialized expertise. Deep learning algorithms show improvements in automatin...
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It is a significant and challenging task to detect the informative features to carry out explainable analysis for high dimensional data,especially for those with very small number of *** selection especially the unsup...
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It is a significant and challenging task to detect the informative features to carry out explainable analysis for high dimensional data,especially for those with very small number of *** selection especially the unsupervised ones are the right way to deal with this challenge and realize the ***,two unsupervised spectral feature selection algorithms are proposed in this *** group features using advanced Self-Tuning spectral clustering algorithm based on local standard deviation,so as to detect the global optimal feature clusters as far as *** two feature ranking techniques,including cosine-similarity-based feature ranking and entropy-based feature ranking,are proposed,so that the representative feature of each cluster can be detected to comprise the feature subset on which the explainable classification system will be *** effectiveness of the proposed algorithms is tested on high dimensional benchmark omics datasets and compared to peer methods,and the statistical test are conducted to determine whether or not the proposed spectral feature selection algorithms are significantly different from those of the peer *** extensive experiments demonstrate the proposed unsupervised spectral feature selection algorithms outperform the peer ones in comparison,especially the one based on cosine similarity feature ranking *** statistical test results show that the entropy feature ranking based spectral feature selection algorithm performs *** detected features demonstrate strong discriminative capabilities in downstream classifiers for omics data,such that the AI system built on them would be reliable and *** is especially significant in building transparent and trustworthy medical diagnostic systems from an interpretable AI perspective.
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