Fault-Diagnosis Sensor Selection for Fuel Cell Stack Systems Combining an Analytic Hierarchy Process with the Technique Order Performance Similarity Ideal Solution Method

Multi-Criteria Decision Making (MCDM) methods have rapidly developed and have been applied to many areas for decision making in engineering. Apart from that, the process to select fault-diagnosis sensor for Fuel Cell Stack system in various options is a multi-criteria decision-making (MCDM) issue. However, in light of the choosing of fault diagnosis sensors, there is no MCDM analysis, and Fuel Cell Stack companies also urgently need a solution. Therefore, in this paper, we will use MCDM methods to analysis the fault-diagnosis sensor selection problem for the first time. The main contribution of this paper is to proposed a fault-diagnosis sensor selection methodology, which combines the rank reversal resisted AHP and TOPSIS and supports Fuel Cell Stack companies to select the optimal fault-diagnosis sensors. Apart from that, through the analysis, among all sensor alternatives, the acquisition of the optimal solution can be regarded as solving the symmetric or asymmetric problem of the optimal solution, which just maps to the TOPSIS method. Therefore, after apply the proposed fault-diagnosis sensor selection methodology, the Fuel Cell Stack system fault-diagnosis process will be more efficient, economical, and safe.

Differentially private density estimation with skew-normal mixtures model

The protection of private data is a hot research issue in the era of big data. Differential privacy is a strong privacy guarantees in data analysis. In this paper, we propose DP-MSNM, a parametric density estimation algorithm using multivariate skew-normal mixtures (MSNM) model to differential privacy. MSNM can solve the asymmetric problem of data sets, and it is could approximate any distribution through expectation–maximization (EM) algorithm. In this model, we add two extra steps on the estimated parameters in the M step of each iteration. The first step is adding calibrated noise to the estimated parameters based on Laplacian mechanism. The second step is post-processes those noisy parameters to ensure their intrinsic characteristics based on the theory of vector normalize and positive semi definition matrix. Extensive experiments using both real data sets evaluate the performance of DP-MSNM, and demonstrate that the proposed method outperforms DPGMM.

Differentially Private Density Estimation with Skew-Normal Mixtures Model

The protection of private data is a hot research issue in the era of big data. Differential privacy is a strong privacy guarantees in data analysis. In this paper, we propose DP-MSNM, a parametric density estimation algorithm using Multivariate Skew-Normal Mixtures (MSNM) model to differential privacy. MSNM can solve the asymmetric problem of datasets, and it is could approximate any distribution through Expectation-Maximization (EM) algorithm. In this model,we add two extra steps on the estimated parameters in the M step of each iteration. The first step is adding calibrated noise to the estimated parameters based on Laplacian mechanism. The second step is post-processes those noisy parameters to ensure their intrinsic characteristics based on the theory of vector normalize and positive semi definition matrix. Extensive experiments using both real datasets evaluate the performance of DP-MSNM, and demonstrate that the proposed method outperforms DP-GMM.

Kinematics and Dynamics Analysis of McPherson Suspension Based on Planar 1/4 Vehicle Model

The nonlinear asymmetric problem of McPherson suspension has become a challenging problem in the process ofestablishing the system model. This paper presents a planar 1/4-vehicle model that not only takes into account thevertical vibration of the sprung mass (chassis), but also includes: ix spring mass (wheel assembly) sliding and rotation;ii longitudinal wheel mass And its moment of inertia; iii tire damping and lateral defl ection. This dynamic kinematicmodel provides a solution to two important shortcomings of the traditional 1/4 vehicle model: it explains geometricmodeling and tire modeling. This paper provides a systematic development of the planar model and a completemathematical equation. This analysis model can be applied to hardware in the rapid calculation of ring applications. Inaddition, the model also gives a repeatable Simulink simulation implementation. The model has been compared withthe actual Adams / View simulation to analyze the vibration and rebound motion of the wheel, as well as two relatedmotion parameters: the dynamic characteristics of the camber and the pitch change.