System logs are vital for diagnosing system failures, with log parsing converting unstructured logs into structured data. Existing methods fall into two categories: non-deep-learning approaches cluster logs based on s...
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The use of technology and information devices contributes to global warming. This issue has also become a concern for UN institutions, as stated in international environmental agreements, which aim to stabilize greenh...
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Online streaming feature selection(OSFS),as an online learning manner to handle streaming features,is critical in addressing high-dimensional *** real big data-related applications,the patterns and distributions of st...
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Online streaming feature selection(OSFS),as an online learning manner to handle streaming features,is critical in addressing high-dimensional *** real big data-related applications,the patterns and distributions of streaming features constantly change over time due to dynamic data generation ***,existing OSFS methods rely on presented and fixed hyperparameters,which undoubtedly lead to poor selection performance when encountering dynamic *** make up for the existing shortcomings,the authors propose a novel OSFS algorithm based on vague set,named *** main idea is to combine uncertainty and three-way decision theories to improve feature selection from the traditional dichotomous method to the trichotomous ***-Vague also improves the calculation method of correlation between features and ***,OSFS-Vague uses the distance correlation coefficient to classify streaming features into relevant features,weakly redundant features,and redundant ***,the relevant features and weakly redundant features are filtered for an optimal feature *** evaluate the proposed OSFS-Vague,extensive empirical experiments have been conducted on 11 *** results demonstrate that OSFS-Vague outperforms six state-of-the-art OSFS algorithms in terms of selection accuracy and computational efficiency.
Parkinson's Disease is a neurological progressive disorder that affects the nervous system of a human being, which effects the parts of the body. Tremors, imbalance, slowed movement, stiffness, difficulty in walki...
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Predicting stock market trends is vital due to its economic impact and benefits. In global finance, stock movements are influenced by numerous factors, especially news and sentiment. High volatility, driven by politic...
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The performance of photovoltaic(PV)systems is in-fluenced by various factors,including atmospheric conditions,geographical locations,and spatial and temporal ***,the optimization of PV systems relies heavily on the gl...
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The performance of photovoltaic(PV)systems is in-fluenced by various factors,including atmospheric conditions,geographical locations,and spatial and temporal ***,the optimization of PV systems relies heavily on the global maximum power point tracking(GMPPT)*** this paper,we adopt virtual reality(VR)technology to visual-ize PV entities and simulate their *** integra-tion of VR technology introduces a novel spatial and temporal dimension to the shading pattern recognition(SPR)of PV sys-tems,thereby enhancing their descriptive ***-more,we introduce an interactive GMPPT(IGMPPT)method based on VR *** method leverages interactive search techniques to narrow down search regions,thereby en-hancing the search *** results demonstrate the effectiveness of the proposed IGMPPT in representing the spatial and temporal characteristics of PV systems and improv-ing the efficiency of GMPPT.
The accurate identification of students in need is crucial for governments and colleges to allocate resources more effectively and enhance social equity and educational fairness. Existing approaches to identifying stu...
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Traditional blockchain key management schemes store private keys in the same location,which can easily lead to security issues such as a single point of ***,decentralized threshold key management schemes have become a...
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Traditional blockchain key management schemes store private keys in the same location,which can easily lead to security issues such as a single point of ***,decentralized threshold key management schemes have become a research focus for blockchain private key *** security of private keys for blockchain user wallet is highly related to user identity authentication and digital asset *** threshold blockchain private key management schemes based on verifiable secret sharing have made some progress,but these schemes do not consider participants’self-interested behavior,and require trusted nodes to keep private key fragments,resulting in a narrow application scope and low deployment efficiency,which cannot meet the needs of personal wallet private key escrow and recovery in public *** design a private key management scheme based on rational secret sharing that considers the self-interest of participants in secret sharing protocols,and constrains the behavior of rational participants through reasonable mechanism design,making it more suitable in distributed scenarios such as the public *** proposed scheme achieves the escrow and recovery of personal wallet private keys without the participation of trusted nodes,and simulate its implementation on smart *** to other existing threshold wallet solutions and keymanagement schemes based on password-protected secret sharing(PPSS),the proposed scheme has a wide range of applications,verifiable private key recovery,low communication overhead,higher computational efficiency when users perform one-time multi-key escrow,no need for trusted nodes,and personal rational constraints and anti-collusion attack capabilities.
The future Sixth-Generation (6G) wireless systems are expected to encounter emerging services with diverserequirements. In this paper, 6G network resource orchestration is optimized to support customized networkslicin...
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The future Sixth-Generation (6G) wireless systems are expected to encounter emerging services with diverserequirements. In this paper, 6G network resource orchestration is optimized to support customized networkslicing of services, and place network functions generated by heterogeneous devices into available *** is a combinatorial optimization problem that is solved by developing a Particle Swarm Optimization (PSO)based scheduling strategy with enhanced inertia weight, particle variation, and nonlinear learning factor, therebybalancing the local and global solutions and improving the convergence speed to globally near-optimal *** show that the method improves the convergence speed and the utilization of network resourcescompared with other variants of PSO.
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