Abstract Multiplex networks provide a powerful data structure for capturing diverse relationships among nodes, and the challenge of community detection within these has recently attracted considerable attention. We propose general flexible generative model—the Mixed Membership Multilayer Stochastic Block Model (MixMSBM), in which layers with meaningful similarities are grouped together. Within each layer group, share same mixed membership assignments nodes to communities, but distinct link...

Abstract A series of nanosized metal–organic frameworks (MOFs) encapsulating different polyoxometalates (POMs) including H 3 PW 4 O 12 , 5 PMo 40 PVMo 10 PV 2 Mo and was synthesized used in the selective oxidation alcohols. The catalyst with a uniform size morphology offered easy accessibility between substrates catalyst. At same time, MOF ensured that POM encapsulated, which could dramatically prevent assembly Furthermore, showed clear chemoselectivity, related to or for surface pores. With...

Wind energy is increasingly considered one of the most promising sustainable sources for its characteristics cleanliness without any pollution. speed forecasting a vital problem in wind power industry. However, individual models ignore significance data preprocessing and model parameter optimization, which may lead to poor performance. In this paper, novel hybrid [k, Bt] -ABBP (back propagation based on adaptive strategy with parameters k Bt) was developed an boosting (AB) that integrates...

Objective. This study focuses on the identification of risk factors, classification stroke level, and evaluation importance interactions various patient characteristics using cohort data from Second Hospital Lanzhou University. Methodology. Risk factors are identified by relationships between response, as well ranking characteristics. Then, after discarding negligible some well-known multicategorical algorithms used to predict level stroke. In addition, Shapley additive explanation method...

Air quality has a significant impact on human health and natural systems worldwide. China, as one of the largest developing countries, faces very much serious air pollution requires attention. While influences or nature have been extensively investigated, few scholars considered two effects simultaneously based same framework. Indeed, coexist in biosphere which they depend for their development impacts occur at time with different synergic effects. Only by considering both we can develop...

Dynamic bad weather such as rain and snow will reduce the qualities of image video, affect on performance visual system seriously. So dynamic restoration technology is a challenging research content. According to optical physical characteristics raindrops/snowflakes, we studied classic video frame difference algorithm detects rain/snow, its basis, identifying initial detection binary connected region, adding constraints area direction angle further distinguish raindrops/snowflakes region. At...

University Journals are an important platform for universities' resource sharing and management, so far the construction of Journal Websites developed rapidly. After establishment sites, facing problem how to promote search engine promotion is a good choice. But then we should consider do optimization(SEO). In this paper, consindering features university journal websites, doing SEO strategies from those aspects: directory structure, keyword strategy, URL pseudo-static, code optimization...

By using the idea of principal component analysis, we propose an approach to applying classical skewness and kurtosis statistics for detecting univariate normality testing high-dimensional normality. High-dimensional sample data are projected directions on which can be constructed. The theory spherical distributions is employed derive null combined constructed from directions. A Monte Carlo study carried out demonstrate performance controlling type I error rates a simple power comparison...

Wood-boring pests are difficult to monitor due their concealed lifestyle. To effectively control these wood-boring pests, it is first necessary efficiently and accurately detect presence identify species, which requires addressing the limitations of traditional monitoring methods. This paper proposes a deep learning-based model called BorerNet, incorporates an attention mechanism using limited vibration signals generated by feeding larvae. Acoustic sensors can be used collect boring from...

Power load forecasting always plays a considerable role in the management of power system, as accurate provides guarantee for daily operation grid. It has been widely demonstrated that hybrid forecasts can improve forecast performance compared with individual forecasts. In this paper, approach, comprising Empirical Mode Decomposition, CSA (Cuckoo Search Algorithm), and WNN (Wavelet Neural Network), is proposed. This approach constructs more valid structure stable results than traditional ANN...

The objective of this paper is to propose an efficient regression algorithm survival analysis - SurvivalBoost.. This based on Random Survival Forests (RSF) and XGBoost. By combining the Elastic-Net penalty type Cox proportional hazards model with XGBoost optimal algorithm, our more suitable for analysis. performance proposed compared model, XGBoost, CoxBoost, RSF Gradient Boosting Desicion Tree-based 4 simulated datasets real datasets. results illustrated superiority algorithm.

Abstract High‐dimensional covariates in lifetime data is a challenge survival analysis, especially gene expression profile. The objective of this paper to propose an efficient algorithm extend the generalized additive model with high‐dimensional covariates. combined (GAM) and Buckley–James estimation, which makes nonparametric extension nonlinear model, where GAM exploited illustrate effect estimation used address regression right‐censored response. In addition, we use...

<para xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> The objective of this paper is to provide a new estimation method for parametric models under progressive Type-I censoring. First, we propose Kaplan-Meier nonparametric estimator the reliability function taken at censoring times. It based on observable number failures, and censored units occurring from scheme This then shown asymptotically follow normal distribution. Next, minimum-distance...

Abstract A fibrous nanosized catalyst with TEMPO supported on silica nanospheres was synthesized and used in the selective oxidation of alcohols into corresponding aldehydes or ketones. The morphologies allowed easy accessibility between substrate catalyst, thus, improved reaction efficiency obtained. pseudo-homogeneous system formed during process, recovery through filtration.

This paper devotes to propose a nuclear-norm-based deep survival algorithm (NN-DeepSurv), study the regression problem of data with right censoring. The nuclear norm method is used impute missing covariates, and it's combined DeepSurv train model. We compare our other state-of-the-art methods: Cox proportional hazards model (Coxph), lasso (Cox-lasso), random forests (RSF), DeepSurv, Xgboost algorithm, on 2 simulated datasets 6 clinical datasets, show superiority performance algorithm.

Variable selection is an effective methodology for dealing with models numerous covariates. We consider the methods of variable semiparametric Cox proportional hazards model under progressive Type-II censoring scheme. The used to influence coefficients environmental By applying Breslow’s “least information” idea, we obtain a profile likelihood function estimate coefficients. Lasso-type penalized estimation as well stepwise method are explored means find important Numerical simulations...

Community detection remains a challenging research hotspot in network analysis. With the complexity of data structures increasing, multilayer networks, which entities interact through multiple types connections, prove to be effective describing complex networks. The layers may not share common community structure. In this paper, we propose joint method based on matrix factorization and spectral embedding recover groups only for but also nodes. Specifically, are grouped via with layer...

Machine learning methods have been extensively used in survival analysis. SurvivalBoost - a machine-learning-based regression algorithm, focused on Elastic-net-Type penalized semiparametric Cox model XGBoost and random forests, has verified its superior prediction performance real simulated datasets. Whereas the interpretability is remain undiscovered. This paper discusses of this algorithm upon using Shapley Additive Explanation (SHAP) value. It illustrated that can be more effective to...

This paper investigates a residual-based maintenance policy for stochastic deteriorating system, which is influenced by Markovian covariates process. The baseline deterioration modeled Gamma process, and the process assumed to be time-homogeneous finite-state Markov chain. A model similar proportional hazards used represent influence of covariates. inspection scheme, depending on degradation level as well state, proposed. We derive optimal threshold, scheme minimize expected average cost. By...