The double coupled microwave resonance probes and application for diagnosing atmospheric pressure plasma jet

The double-coupled microwave resonance probe(DMRP) based on the hairpin probe is proposed for diagnosing atmospheric plasma jet(n_e10~(17) m~(-3)). In this work, the resonance characteristics of DMRP are investigated by numerical simulation. It shows that two resonance peaks on the reflectance spectrum can be observed, and influenced significantly by some parameters, such as the probe separation, the distance to the handheld radio frequency atmospheric pressure glow discharge plasma jet(RF-APGDPJ) and the plasma electron density less than 1017 m~(-3). Based on two resonance modes of DMRP, the electron densities in the afterglow of RF-APGDPJ at the different rf powers and helium flow rates are diagnosed experimentally by matching the change of FWHM(Df_1-Df_(1,air)and Df_2-Df_(2,air)) measured by vector network analyzer with the simulated relation between the FWHM changes and the plasma density.     

A new nonparametric double exponentially weighted moving average control chart

There are many practical situations where the underlying distribution of the quality characteristic either deviates from normality or it is unknown. In such cases, practitioners often make use of the nonparametric control charts. In this paper, a new nonparametric double exponentially weighted moving average control chart on the basis of the signed-rank statistic is proposed for monitoring the process location. Monte Carlo simulations are carried out to obtain the run length characteristics of the proposed chart. The performance comparison of the proposed chart with the existing parametric and nonparametric control charts is made by using various performance metrics of the run length distribution. The comparison showed the superiority of the suggested chart over its existing parametric and nonparametric counterparts. An illustrative example for the practical implementation of the proposed chart is also provided by using the industrial data set.     

当33atomic％Ce替代Sm时(Sm1-yCey)2Fe17Nx的最大磁能积不下降

本文研究了完全氮化的(Sm1-yCey)2Fe17Nx（y = 0、0.20、0.33、0.40、0.45、0.50、0.67、0.80、1.00）粉末的磁性能和微观结构。当用33atomic％Ce代替Sm时，最大磁能积(BH)max从17.8 MGOe变为17.6 MGOe，几乎没有下降。相应的，性能/稀土价格比率提高了39.2％。 根据能量色散光谱（EDS）分析，Ce倾向于分布在REFe3 / REFe2晶界相中。XPS证实了(Sm1-yCey)2Fe17Nx中Ce离子的价态变化。     

Maximum efficiency point tracking for an ocean thermal energy harvesting system

Limited energy is the most critical factor that restricts the persistent presence of underwater vehicles in the oceans; thus, harvesting the ocean's thermal energy that is stored in the water column between the sea surface and deep water is a particularly promising solution for the current power shortage. This paper has designed a new ocean thermal energy conversion system which using phase change material as energy storage medium, and proposed a novel maximum efficiency point tracking (MEPT) method for energy conversion. This new method, which is integrated with a radial basis function neural network (RBFNN), particle swarm optimization (PSO) and the proportion integration differentiation (PID) control method, could effectively improve the efficiency of energy conversion. Compared with the power generation system that does not use the MEPT method, experimental results show that the proposed method can improve the efficiency of the power generation from less than 19.05% to more than 34.3% and has higher stability (using this method: the efficiency changes from 34.3%-34.7%; without using this method: the efficiency changes from 13.56% -19.05%) when the load changes. This novel method can be used in many conditions, especially when the mathematical model of the generation system is unknown or researchers want to use fewer sensors for maximum efficiency point tracking.     

On the volume power density of radial thermoelectric generators

We examine the volume power density of radial thermoelectric generators (TEGs). Radial, or tubular, TEGs have been considered as an alternative to the usual flat-plate TEGs due to its improved geometric match to typical curved heat sources and high surface power density. However, surface power density is not the only important performance index in realistic situations. Especially for TEGs with inorganic materials that have high raw material prices, volume power density can be important as well. In this note, an analytic model of a radial TEG is studied with a numerical trial-and-error approach for investigating its volume power density. At the same time, an alternative, approximate method of estimating the maximum power of the radial TEG is presented. Using these two approaches, we estimate the volume power density of a skutterudite-based radial TEG and compare the results to those of a flat-plate TEG. The volume power density of the radial TEG is significantly lower than that of the flat-plate TEG. For example, our calculation for a representative case with free convection on the cold side shows that the volume power density of the radial TEG will be 107 W/m³ at best. The result improves with forced convection, and our calculation for a representative case with forced convection on the cold side exhibits the maximum volume power density of 24 100 W/m³ . All these values turn out to be smaller roughly by one order of magnitude than the maximum volume power densities of comparable flat-plate TEGs. Such a low volume power density indicates lower economic feasibility of the radial TEG with expensive inorganic thermoelectric materials. This is also explicitly discussed by presenting the high cost per watt of the radial TEG. It is therefore suggested that radial TEGs with less expensive organic materials may be more acceptable than those with inorganic ones.     

对《称重传感器》国标5.2.1条款

通过对《称重传感器》国标仔细研读和分析,在标准规定的三段最大允许误差限基础上,提出了五段式最大允许误差限和分段点必检的观点,从而满足了5.2.1提出的全量程、全分度的检定要求。     

Analyzing Dynamic Change in Social Network Based on Distribution-Free Multivariate Process Control Method

Social organizations can be represented by social network because it can mathematically quantify and represent complex interrelated organizational behavior. Exploring the change in dynamic social network is essential for the situation awareness of the corresponding social organization. Social network usually evolves gradually and slightly, which is hard to be noticed. The statistical process control techniques in industry field have been used to distinguish the statistically significant change of social network. But the original method is narrowed due to some limitation on measures. This paper presents a generic framework to address the change detection problem in dynamic social network and introduces a distribution-free multivariate control charts to supervise the changing of social network. Three groups of network parameters are integrated together in order to achieve a comprehensive view of the dynamic tendency. The proposed approaches handle the non-Gaussian data based on categorizing and ranking. Experiments indicate that nonparametric multivariate procedure is promising to be applied to social network analysis.     

Improved error performance of a 3/4‐Sezginer space‐time block codes

The Alamouti space‐time block code (STBC) achieves full diversity gain at a rate of 1/2. However, the Alamouti scheme does not provide multiplexing gain. The Silver code offers both diversity and multiplexing gain. It has a minimum normalization determinant of . The Golden code is another STBC that offers both diversity and multiplexing gain. The Golden code is ranked higher than the Silver code because of its lower minimum normalization determinant of , however, the golden code suffers from a high detection complexity in the modulation order of M⁴. The 3/4‐Sezginer code is another STBC, which compromises between the Alamouti scheme and the Golden code in terms of diversity gain and multiplexing gain. The 3/4‐Sezginer code achieves full diversity and half of multiplexing gain. The uncoded space‐time labeling diversity (USTLD) is a recent scheme that improves the error performance when applied to the STBC in multiple‐input multiple‐output (MIMO) systems and will be applied to the 3/4‐Sezginer STBC to improve the error performance in this paper. The theoretical error probability for both the 3/4‐Sezginer STBC and the improved system is formulated using the union bound in this paper. The theoretical error probabilities of both 16‐QAM and 64‐QAM are validated through Monte Carlo simulation. The simulation and theoretical results show that the proposed system with 4 N_R can achieve an SNR gain of 1 dB for 16‐QAM and 1.2 dB 64‐QAM at a bit error rate (BER) of 10^?6.     

Individual-based multi-objective optimal structured treatment interruption for HIV infection

In this paper, based on the measurable quantities from an individual patient that has infection to human immunodeficiency virus (HIV) and his/her condition is near to acquired immune deficiency syndrome (AIDS), individual-based multi-objective optimal treatments have been proposed. Firstly, the most effective parameters of the patient in computing Long-term non-progressor (LTNP) equilibrium are derived using global sensitivity analysis (GSA). To accomplish GSA effectively, Latin hypercube sampling (LHS) and partial rank correlation coefficients (PRCC) are utilized to rank each of the parameters based on each state of the 5-dimensional model. Then, these results are used by Dempster–Shafer (D–S) evidence theory (DSET) to rank the most effective parameters comprehensively. Now, these effective identified parameters are estimated using extended Kalman filter (EKF), which its covariance matrices are optimized based on particle swarm optimization (PSO) algorithm. Thus, the proposed methodology gives a calibrated model corresponding to the individual patient. Based on this calibrated model, the LTNP equilibrium related to the individual patient is derived. Using the derived individual-based LTNP equilibrium optimal structured treatment interruption (STI) strategies are extracted by defining suitable multi-objective optimization problem and solving it through using non-dominated sorting genetic algorithm-II (NSGA-II). The results demonstrate that the proposed optimal treatments are able to effectively reach LTNP equilibrium with using the minimum and maximum drug usage of 3.6% and 35.1% of full drug usage treatment. Meanwhile, the different optimal treatments give the decision-makers enough flexibility to choose the suitable treatment based on existing facilities and necessities.     

Particle filter with one-step randomly delayed measurements and unknown latency probability

In this paper, a new particle filter is proposed to solve the nonlinear and non-Gaussian filtering problem when measurements are randomly delayed by one sampling time and the latency probability of the delay is unknown. In the proposed method, particles and their weights are updated in Bayesian filtering framework by considering the randomly delayed measurement model, and the latency probability is identified by maximum likelihood criterion. The superior performance of the proposed particle filter as compared with existing methods and the effectiveness of the proposed identification method of latency probability are both illustrated in two numerical examples concerning univariate non-stationary growth model and bearing only tracking.