The purpose of a network intrusion detection (NID) is to detect intrusions in the network, which plays a critical role in ensuring the security of the Internet of Things (IoT). Recently, deep ...learning (DL) has achieved a great success in the field of intrusion detection. However, the limited computing capabilities and storage of IoT devices hinder the actual deployment of DL-based high-complexity models. In this article, we propose a novel NID method for IoT based on the lightweight deep neural network (LNN). In the data preprocessing stage, to avoid high-dimensional raw traffic features leading to high model complexity, we use the principal component analysis (PCA) algorithm to achieve feature dimensionality reduction. Besides, our classifier uses the expansion and compression structure, the inverse residual structure, and the channel shuffle operation to achieve effective feature extraction with low computational cost. For the multiclassification task, we adopt the NID loss that acts as a better loss function to replace the standard cross-entropy loss for dealing with the problem of uneven distribution of samples. The results of experiments on two real-world NID data sets demonstrate that our method has excellent classification performance with low model complexity and small model size, and it is suitable for classifying the IoT traffic of normal and attack scenarios.
Metabolic syndrome (MetS) is a major risk factor for cardiovascular diseases. The objective of the study was to evaluate the updated prevalence of MetS and provide a comprehensive illustration of the ...possible temporal changes in MetS prevalence in China from 2011 to 2015.
The data for this study are from the 2011 and 2015 waves of the China Health and Retirement Longitudinal Study (CHARLS). CHARLS is a nationally representative survey targeting populations aged 45 and above from 28 provinces in mainland China. A total of 11,847 and 13,013 participants were eligible for data analysis at the two time points.
The estimated prevalence of MetS in 2015 was 20.41% (95% CI: 19.02-21.8%) by the National Cholesterol Education Program (NCEP) Expert Panel on Detection, Evaluation, and Treatment of High Blood Cholesterol in Adults (ATP III) criteria, 34.77% (95% CI: 33.12-36.42%) by the International Diabetes Federation (IDF) criteria, 39.68% (95% CI: 37.88-41.47%) by the revised ATP III criteria, and 25.55% (95% CI: 24.19-26.91%) by the Chinese Diabetes Society (CDS) criteria. The prevalence was higher among women and elderly adults and in urban and northern populations. Furthermore, the trends in the prevalence decreased significantly between 2011 and 2015 by the ATP III, revised ATP III and CDS criteria. However, trends increased significantly from 2011 to 2015 by the IDF criteria.
A higher prevalence of MetS is found in those who reported being middle aged and elderly, women, residing in northern China or living in urban areas. Additionally, temporal changes in the prevalence of MetS varied according to different criteria. Increased attention to the causes associated with populations who have higher levels of MetS is warranted.
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DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
•Tip cavitation cloud and perpendicular cavitation vortices were predicted.•The dynamic process of perpendicular cavitation vortices was revealed.•The PCV may trigger cavitation instability and ...influence the tip cavitation.
The objective of this work is to simulate and analyze the formations of three-dimensional tip leakage vortex (TLV) cavitation cloud and the periodic collapse of TLV-induced suction-side-perpendicular cavitating vortice (SSPCV). Firstly, the improved SST k–ω turbulence model and the homogeneous cavitation model were validated by comparing the simulation result with the experiment of unsteady cavitation shedding flow around the NACA66-mod hydrofoil, and then the unsteady TLV cloud cavitation and unstable SSPCV in an axial flow pump were predicted using the improved numerical method. The predicted three-dimensional cavitation structures of TLV and SSPCV as well as the collapsing features show a good qualitative agreement with the high speed photography results. Numerical results show that the TLV cavitation cloud in the axial flow pump mainly includes tip clearance cavitation, shear layer cavitation, and TLV cavitation. The unsteady TLV cavitation cloud occurs near the blade trailing edge (TE) where the shapes of sheet cavitation and TLV cavitation fluctuate. The inception of SSPCV is attributed to the tail of the shedding cavitation cloud originally attached on the suction side (SS) surface of blade, and the entrainment affect of the TLV and the influence of the tip leakage flow at the tailing edge contribute to the orientation and development of the SSPCV. The existence of SSPCV was evidently approved to be a universal phenomenon in axial flow pumps. At the part-load flow rate condition, the SSPCV may trigger cavitation instability and suppress the tip cavitation in the neighboring blade. The cavitation cloud on the SS surface of the neighboring blade grows massively, accompanying with a new SSPCV in the neighboring flow passage, and this SSPCV collapses in a relatively short time.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UL, UM, UPCLJ, UPUK
The unique structure of bearingless motors requires extra displacement sensors to monitor rotor movement, unlike conventional synchronous motors. However, this requirement inevitably escalates the ...cost and size of the motor. To address these issues, this paper proposes a novel approach: a bearingless synchronous reluctance motor (BSRM) without displacement sensors, utilizing the whale optimization algorithm–Elman neural network (WOA-ENN). The paper firstly introduces the suspension mechanism and mathematical model of the BSRM, upon which a function containing rotor position information is constructed. Subsequently, a sensorless method based on Elman neural network (ENN) is proposed, optimized using the whale optimization algorithm (WOA). Finally, the feasibility and reliability of the proposed approach are validated through simulations and experiments.
•Deformation is predicted by support vector machine information granulation.•Minimum, average and maximum of surrounding rock deformation are predicted.•Support vector machine parameter optimization ...method is optimized.
The potential arch crown settlement is one of the most hazardous factors in shallow-buried tunnel excavations. Therefore, accurate prediction of arch crown settlement range is essential to minimize the possible risk of damage. Considering the time series regression characteristics of deformation of surrounding rock in shallow-buried tunnels, the Support Vector Machine (SVM) information granulation method was newly applied in this study for deformation prediction of surrounding rock. First, obtain monitoring data of the tunnel arch crown settlement. Second, transform the data of three arch crown settlement into a triangular fuzzy particle. The three parameters, Low, R, and Up in the fuzzy particle represent the minimum, average and maximum value of the settlement of the arch crown in three days. Then, use the SVM to predict the Low, R, and Up values of the tunnel arch crown settlement. Finally, the established prediction model of surrounding rock with SVM information granulation method was applied to the Panlongshan tunnel on the line of the Qinglan expressway in China and prediction results agree well with practical situations, which means the method of SVM information granulation used in this study could provide relatively high accuracy when applied to deformation prediction of surrounding rock in shallow-buried tunnels. Meanwhile, the SVM information granulation method is simple, feasible and easy to implement. The presented method has been validated as an effective method of deformation prediction for surrounding rock, which also has good prospects for further engineering applications.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
This paper proposes a patent citation classification model based on deep learning, and collects the patent datasets in text analysis and communication area from Google patent database to evaluate the ...classification effect of the model. At the same time, considering the technical relevance between the examiners’ citations and the pending patent, this paper proposes a hypothesis to take the output value of the model as the technology similarity of two patents. The rationality of the hypothesis is verified from the perspective of machine statistics and manual spot check. The experimental results show that the model effect based on deep learning proposed in this paper is significantly better than the traditional text representation and classification method, while having higher robustness than the method combining Doc2vec and traditional classification technology. In addition, we compare between the proposed method based on deep learning and the traditional similarity method by a triple verification. It shows that the proposed method is more accurate in calculating technology similarity of patents. And the results of manual sampling show that it is reasonable to use the output value of the proposed model to represent the technology similarity of patents.
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EMUNI, FIS, FZAB, GEOZS, GIS, IJS, IMTLJ, KILJ, KISLJ, MFDPS, NLZOH, NUK, OBVAL, OILJ, PNG, SAZU, SBCE, SBJE, SBMB, SBNM, UKNU, UL, UM, UPUK, VKSCE, ZAGLJ
Several reports in recent years have found an association between gut microbiota and upper urinary urolithiasis. However, the causal relationship between them remains to be clarified.
Genetic ...variation is used as a tool in Mendelian randomization for inference of whether exposure factors have a causal effect on disease outcomes. We selected summary statistics from a large genome-wide association study of the gut microbiome published by the MiBioGen consortium with a sample size of 18,340 as an exposure factor and upper urinary urolithiasis data from FinnGen GWAS with 4,969 calculi cases and 213,445 controls as a disease outcome. Then, a two-sample Mendelian randomization analysis was performed by applying inverse variance-weighted, MR-Egger, maximum likelihood, and weighted median. In addition, heterogeneity and horizontal pleiotropy were excluded by sensitivity analysis.
IVW results confirmed that class
(OR = 0.814, 95% CI: 0.666-0.995,
= 0.045), order
(OR = 0.833, 95% CI: 0.737-0.940,
= 3.15 × 10
), family
(OR = 0.729, 95% CI: 0.581-0.916,
= 6.61 × 10
), genus
(OR = 0.695, 95% CI: 0.551-0.877,
= 2.20 × 10
), genus
(OR = 0.777, 95% CI: 0.612-0.986,
= 0.0380), genus
(OR = 0.711, 95% CI: 0.536-0.944,
= 0.0181), genus
(OR = 0.829, 95% CI: 0.690-0.995,
= 0.0444), and genus
(OR = 0.758, 95% CI: 0.577-0.996,
= 0.0464) had a protective effect on upper urinary urolithiasis, while
(OR =1.26, 95% CI: 1.010-1.566,
= 0.0423) had the opposite effect. Sensitivity analysis did not find outlier SNPs.
In summary, a causal relationship was found between several genera and upper urinary urolithiasis. However, we still need further randomized controlled trials to validate.
Most of variable fractional delay (VFD) filters adopt the well-known Farrow structure that assumes an algebraic polynomial approximation to the varying impulse response. The recently proposed complex ...exponential (CE) structure for VFD filters can achieve a great improvement in design accuracy and a marked reduction in complexity compared with the Farrow structure by using complex exponential functions as the approximants. The least lp-norm design problem of the CE-based VFD FIR filters is considered in this paper, which is viewed as a good tradeoff between the least squares and minimax designs. The iteratively reweighted least squares (IRLS) approach is adopted to solve this problem, in which the least lp-norm approximation is decomposed into a series of weighted least squares (WLS) subproblems. A matrix-based conjugate gradient (CG) algorithm is presented to solve those WLS subproblems, which is very efficient due to the use of matrix variables. Moreover, the filter performance will be improved further by optimizing the shape parameter in the CE structure using a one-dimensional search technique. Design examples are provided to demonstrate the effectiveness of the proposed method. The comparison of the CE structure filters with the Farrow structure filters is included.
•Least lp-norm design of CE-based VFD filters is formulated in matrix form.•A matrix-based IRLS algorithm is devised for optimal design of CE-based VFD filters.•Simulations are provided to demonstrate the superiority of the proposed approach.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
A transient three-dimensional (3D) coupled mathematical model is developed in this paper in order to explore the electromagnetic, flow, and temperature fields, as well as the solidification in the ...electroslag remelting (ESR) process. Maxwell's equations are solved by the Finite Volume Method. The Joule heating and electromagnetic force (EMF), the source terms in the energy and momentum equations, are recalculated during each iteration as function of the phase distribution. The movement of the metal droplets is described by the Volume of Fluid (VOF) approach. Additionally, the solidification of the metal is modeled by an enthalpy-based technique, where the mushy zone is treated as a porous medium with a porosity equal to the liquid fraction. The results show that the electric current tends to go through the metal droplet first. The EMF varies with the falling metal droplet, always blocking the motion of the metal droplet. The zone with the highest temperature appears under the outer radius of the inlet. A larger Joule heating density, as well as a higher average temperature of the molten slag, is obtained when the current increases. Bigger metal droplets form with more heat and momentum, resulting in a deeper liquid metal pool.
•First time to develop a transient 3D coupled mathematical model of the ESR process.•Variation of Joule heating and EMF with the falling metal droplet is demonstrated.•Asymmetrical physical fields are revealed indicating the necessity of a 3D model.•The effect of the current on the heat transfer and MHD flow is clarified.
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