The blockchain trilemma—balancing decentralization,security,and scalability—remains a critical challenge in distributed ledger technology.Despite significant advancements,achieving all three attributes simultaneousl...The blockchain trilemma—balancing decentralization,security,and scalability—remains a critical challenge in distributed ledger technology.Despite significant advancements,achieving all three attributes simultaneously continues to elude most blockchain systems,often forcing trade-offs that limit their real-world applicability.This review paper synthesizes current research efforts aimed at resolving the trilemma,focusing on innovative consensus mechanisms,sharding techniques,layer-2 protocols,and hybrid architectural models.We critically analyze recent breakthroughs,including Directed Acyclic Graph(DAG)-based structures,cross-chain interoperability frameworks,and zero-knowledge proof(ZKP)enhancements,which aimto reconcile scalability with robust security and decentralization.Furthermore,we evaluate the trade-offs inherent in these approaches,highlighting their practical implications for enterprise adoption,decentralized finance(DeFi),and Web3 ecosystems.By mapping the evolving landscape of solutions,this review identifies gaps in currentmethodologies and proposes future research directions,such as adaptive consensus algorithms and artificial intelligence-driven(AI-driven)governance models.Our analysis underscores that while no universal solution exists,interdisciplinary innovations are progressively narrowing the trilemma’s constraints,paving the way for next-generation blockchain infrastructures.展开更多
A Recommender System(RS)is a crucial part of several firms,particularly those involved in e-commerce.In conventional RS,a user may only offer a single rating for an item-that is insufficient to perceive consumer prefe...A Recommender System(RS)is a crucial part of several firms,particularly those involved in e-commerce.In conventional RS,a user may only offer a single rating for an item-that is insufficient to perceive consumer preferences.Nowadays,businesses in industries like e-learning and tourism enable customers to rate a product using a variety of factors to comprehend customers’preferences.On the other hand,the collaborative filtering(CF)algorithm utilizing AutoEncoder(AE)is seen to be effective in identifying user-interested items.However,the cost of these computations increases nonlinearly as the number of items and users increases.To triumph over the issues,a novel expanded stacked autoencoder(ESAE)with Kernel Fuzzy C-Means Clustering(KFCM)technique is proposed with two phases.In the first phase of offline,the sparse multicriteria rating matrix is smoothened to a complete matrix by predicting the users’intact rating by the ESAE approach and users are clustered using the KFCM approach.In the next phase of online,the top-N recommendation prediction is made by the ESAE approach involving only the most similar user from multiple clusters.Hence the ESAE_KFCM model upgrades the prediction accuracy of 98.2%in Top-N recommendation with a minimized recommendation generation time.An experimental check on the Yahoo!Movies(YM)movie dataset and TripAdvisor(TA)travel dataset confirmed that the ESAE_KFCM model constantly outperforms conventional RS algorithms on a variety of assessment measures.展开更多
近年来,以Chat GPT为代表的大语言模型(large language model,LLM)技术发展迅速.随着模型参数规模的持续增长,构建和应用大模型对数据存储规模和存储访问效率提出了更高要求,这对传统存储系统带来了严峻挑战.首先分析了大模型在数据准...近年来,以Chat GPT为代表的大语言模型(large language model,LLM)技术发展迅速.随着模型参数规模的持续增长,构建和应用大模型对数据存储规模和存储访问效率提出了更高要求,这对传统存储系统带来了严峻挑战.首先分析了大模型在数据准备、模型训练和推理阶段的存储访问特征,深入探讨了传统存储系统在大模型场景下面临的主要问题和瓶颈.针对这些挑战,提出并实现了一种高性能、可扩展的分布式元数据设计Scale FS.通过目录树元数据与属性元数据解耦的架构设计,并结合深度与广度均衡的目录树分层分区策略设计,Scale FS实现了高效的路径解析、负载均衡和系统扩展能力,能够高效管理千亿级文件.此外,Scale FS设计了细粒度元数据结构,优化了元数据访问模式,并构建了面向文件语义优化的元数据键值存储底座,显著提升了元数据访问效率并减少了磁盘I/O操作.实验结果表明,Scale FS的每秒操作次数(operations per second,OPS)是HDFS的1.04~7.12倍,而延迟仅为HDFS的12.67%~99.55%.在千亿级文件规模下,Scale FS的大部分操作性能优于HDFS在十亿级文件规模下的表现,展现出更高的扩展性和访问效率,能够更好地满足大模型场景对千亿级文件存储及高效访问的需求.展开更多
In recent years,perovskite solar cells(PSCs)have garnered significant attention as a potential mainstream technology in the future photovol-taic(PV)market.This is primarily attributed to their salient advantages inclu...In recent years,perovskite solar cells(PSCs)have garnered significant attention as a potential mainstream technology in the future photovol-taic(PV)market.This is primarily attributed to their salient advantages including high efficiency,low cost,and ease of preparation.Nota-bly,the power conversion efficiency(PCE)of PSCs has experienced a remarkable increase from 3.8%in 2009 to over 26%at present.Conse-quently,the adoption of roll-to-roll(R2R)technology for PSCs is considered a crucial step towards their successful commercialization.This arti-de reviews the diverse substrates,scalable deposition techniques(such as solution-based knife-coating and spraying technology),and optimiza.tion procedures employed in recent years to enhance device performance within the R2R process.Additionally,novel perspectives are presented to enrich the existing knowledge in this field.展开更多
文摘The blockchain trilemma—balancing decentralization,security,and scalability—remains a critical challenge in distributed ledger technology.Despite significant advancements,achieving all three attributes simultaneously continues to elude most blockchain systems,often forcing trade-offs that limit their real-world applicability.This review paper synthesizes current research efforts aimed at resolving the trilemma,focusing on innovative consensus mechanisms,sharding techniques,layer-2 protocols,and hybrid architectural models.We critically analyze recent breakthroughs,including Directed Acyclic Graph(DAG)-based structures,cross-chain interoperability frameworks,and zero-knowledge proof(ZKP)enhancements,which aimto reconcile scalability with robust security and decentralization.Furthermore,we evaluate the trade-offs inherent in these approaches,highlighting their practical implications for enterprise adoption,decentralized finance(DeFi),and Web3 ecosystems.By mapping the evolving landscape of solutions,this review identifies gaps in currentmethodologies and proposes future research directions,such as adaptive consensus algorithms and artificial intelligence-driven(AI-driven)governance models.Our analysis underscores that while no universal solution exists,interdisciplinary innovations are progressively narrowing the trilemma’s constraints,paving the way for next-generation blockchain infrastructures.
文摘A Recommender System(RS)is a crucial part of several firms,particularly those involved in e-commerce.In conventional RS,a user may only offer a single rating for an item-that is insufficient to perceive consumer preferences.Nowadays,businesses in industries like e-learning and tourism enable customers to rate a product using a variety of factors to comprehend customers’preferences.On the other hand,the collaborative filtering(CF)algorithm utilizing AutoEncoder(AE)is seen to be effective in identifying user-interested items.However,the cost of these computations increases nonlinearly as the number of items and users increases.To triumph over the issues,a novel expanded stacked autoencoder(ESAE)with Kernel Fuzzy C-Means Clustering(KFCM)technique is proposed with two phases.In the first phase of offline,the sparse multicriteria rating matrix is smoothened to a complete matrix by predicting the users’intact rating by the ESAE approach and users are clustered using the KFCM approach.In the next phase of online,the top-N recommendation prediction is made by the ESAE approach involving only the most similar user from multiple clusters.Hence the ESAE_KFCM model upgrades the prediction accuracy of 98.2%in Top-N recommendation with a minimized recommendation generation time.An experimental check on the Yahoo!Movies(YM)movie dataset and TripAdvisor(TA)travel dataset confirmed that the ESAE_KFCM model constantly outperforms conventional RS algorithms on a variety of assessment measures.
文摘In recent years,perovskite solar cells(PSCs)have garnered significant attention as a potential mainstream technology in the future photovol-taic(PV)market.This is primarily attributed to their salient advantages including high efficiency,low cost,and ease of preparation.Nota-bly,the power conversion efficiency(PCE)of PSCs has experienced a remarkable increase from 3.8%in 2009 to over 26%at present.Conse-quently,the adoption of roll-to-roll(R2R)technology for PSCs is considered a crucial step towards their successful commercialization.This arti-de reviews the diverse substrates,scalable deposition techniques(such as solution-based knife-coating and spraying technology),and optimiza.tion procedures employed in recent years to enhance device performance within the R2R process.Additionally,novel perspectives are presented to enrich the existing knowledge in this field.
